Ships are a fundamental element of water transport traffic scenarios and the primary focus of waterway traffic monitoring. Shipping transportation, as a predominant mode of transportation, has witnessed rapid development in recent years. The automated classification of inland river ships serves as the foundation for the digitization and intelligent management of inland waterway transportation. It is crucial for facilitating the high-quality development of the shipping industry. The predominant approach for inland ship classification relies on visual sensors and synthetic aperture radar, which are limited in providing detailed 3D geometric information and are affected by varying weather and lighting conditions. In this paper, we propose a LiDAR-based ship classification method for inland waterways to address this issue. This method involves background filtering and target detection on the original point cloud, generating a dataset of point clouds of inland ships, and using PointNet to learn and classify ship point cloud features. Moreover, for the first time, we propose a point cloud classification framework for multi-channel feature fusion. The proposed framework fuses LiDAR ring ID, intensity, and geometric features into a unified point cloud representation. Based on the fused point cloud data, an improved model with a point-wise attention mechanism is employed for feature extraction and classification. Our method achieves an accuracy of 97.33%, surpassing the geometric information-only method by 2.94%. This result effectively demonstrates the method’s efficacy in extracting features and classifying LiDAR point cloud ships.

This paper proposes an event-triggered (ET) distributed secondary control method with preassigned finite-time performance (PFTP) constraints for islanded microgrids (MGs). The method ensures fast voltage recovery while also guaranteeing robust transient performance and efficient utilization of communication resources. First, a finite-time extended state observer is designed to estimate the uncertain term in the linearized MG system. Second, a barrier Lyapunov function incorporating a PFTP function is developed to ensure that the system satisfies the preassigned performance constraints. Based on this, a backstepping-based secondary controller with an ET mechanism is established, where a robust compensation term is integrated to mitigate chattering. Third, theoretical analysis demonstrates that all signals remain bounded and the synchronization error converges to a prescribed region within a preassigned finite time, while avoiding the Zeno phenomenon. Finally, the effectiveness of the proposed method is validated through MATLAB/Simulink simulations and hardware-in-the-loop experiments. Its robustness under communication delays is further demonstrated, where enhanced chattering suppression effectively minimizes voltage deviations. Comparative results verify that the proposed method achieves fast voltage recovery with superior transient performance.

The topology of a communication system is crucial in determining data transmission. Although significant research has been conducted on the integration of control and communication, existing studies on communication for control systems predominantly emphasize control aspects and warrant further exploration. Furthermore, there is a lack of research on the impacts of topology changes on control systems. This article aims to establish a connection between control and communication via communication topology, examining how communication topologies affect controllers. This article also analyzes the relationship between communication and control in depth. For static topologies, specific controller forms are derived from a general controller to illustrate the impacts of static topologies on controllers. In dynamic topologies, communication is nondeterministic, so whether a controller can receive data from other nodes is nondeterministic. Therefore, controller forms in which some coefficients are random variables following a probability distribution are derived. We utilize them to establish a close connection between control and communication. Furthermore, extensive simulations are conducted to investigate the impact of different topologies on the control system.

In recent years, traffic congestion have become a common problem in modern transportation systems, causing people to spend more time on the road, increased emissions, and elevated safety risks. Intelligent Transportation Systems (ITS) address these issues by integrating cutting-edge technologies, advanced sensing, innovative deep learning algorithms, and driver participation to enable real-time monitoring and predictive traffic management. However, the collection of sensitive driver spatiotemporal location data required for effective real-time analysis raises privacy concerns. Such detailed reporting can inadvertently expose individual travel patterns, daily routines, and personal habits, making drivers vulnerable to profiling, unauthorized surveillance, and even malicious exploitation. To address these challenges, this paper introduces a secure and privacy-preserving traffic forecasting framework that combines k-anonymity with functional encryption to guarantee protection of individual driver information while enabling accurate aggregation of encrypted reports. The aggregated data are then used to train a deep learning architecture that integrates Convolutional Long Short-Term Memory (Conv-LSTM) for spatial and short-term temporal dependencies with Bidirectional LSTM (Bi-LSTM) for capturing long-term periodic traffic patterns for forecasting. Extensive experiments on real-world datasets demonstrate that the proposed scheme achieves high forecasting accuracy, maintaining mean absolute error below 10% for a 60-minute forecasting horizon, while safeguarding driver privacy.

Unmanned aerial vehicles (UAV), due to their flexibility and extensive coverage, have gradually become essential for substation inspections. Wireless mesh networks (WMN) provide a scalable and resilient network environment for UAVs, where each node can serve as either an access point or a relay point, thereby enhancing the network’s fault tolerance and overall resilience. However, the UAV-WMN combined system is complex and dynamic, facing the challenge of dynamically adjusting node transmission power to minimize end-to-end (E2E) delay while ensuring channel utilization efficiency. Real-time topology changes, high-dimensional state spaces, and large solution spaces make it difficult for traditional algorithms to guarantee convergence and stability. Generic reinforcement learning (RL) methods also struggle with stable convergence. This paper introduces a new Lyapunov function-based proof to address these issues and provide a stable condition for dynamic control strategies. Then, we developed a specialized neural network power controller and combined it with the MATD3 algorithm, effectively enhancing the system’s convergence and E2E performance. Simulation experiments validate the effectiveness of this method and demonstrate its superior performance in complex scenarios compared to other algorithms.

This article proposes an intelligent building energy management (BEM) strategy based on two different time-scale neural networks (NNs) to minimize building electricity expense and maximize building user comfort considering load demand uncertainties and variation in day-ahead and real-time electricity prices. First, in terms of the day-ahead BEM, an intelligent and optimization problem on an hourly time scale is formulated to generate a day-ahead baseline BEM solution. Then, in terms of the real-time BEM, another intelligent and optimization problem in a 5-min time scale is proposed to balance the real-time deviations from the energy demand scheduled one day ahead based on the real-time electricity price. In this article, the NN models are developed to handle the energy management challenge of highly nonlinear building heating, ventilation, and air conditioning (HVAC) systems while physics-based models are developed for building non-HVAC loads. A joint particle swarm optimization and mixed-integer linear programming technique is developed to generate optimal scheduling for building HVAC and non-HVAC loads, in which the thermal coupling issues between HVAC and non-HVAC loads are solved through an iterative approach. Finally, the proposed strategy is evaluated for several different scenarios by considering uncertainties of customers’ comfort requirements and weather prediction. The results demonstrate that the proposed intelligent BEM is economical, efficient, and robust to address the challenge of demand uncertainty and day-ahead and real-time electricity price inconsistency.

With the rapid development of communication and Internet technologies, the Internet of Things (IoT) has become increasingly popular. Although IoT devices can bring more benefits to humans, there are a lot of concerns about the security and privacy of the IoT devices. Even though researchers propose some prevention and detection methods for security purposes, cyber-attacks often happen in IoT devices. Thus, we should have an accountability mechanism for the IoT devices. We should know what happens once the IoT devices have security and privacy issues. In this article, we propose an IoT system that can provide accountability. The proposed IoT system can guarantee that the communication behaviors of IoT devices and the local server can be observed and audited. IoT devices and the local server cannot record incorrect messages, deny that messages were sent out, and forge log entries without notice. We prove our proposed IoT system’s accountability property and evaluate its performance.

This article presents an event-triggered distributed secondary control with predictive compensation based on the model-free predictive control under Denial-of-Service (DoS) attacks in ac/dc-networked microgrids. First, models of ac/dc networked microgrids in both electric network and communication network are established. On this premise, event-triggered distributed secondary control is proposed to solve the problems of strong communication burden and low-power distribution accuracy. Besides, aiming at the impact of DoS attacks on distributed secondary control, a compensation algorithm based on model-free predictive control is designed to estimate the control variables when the DoS attack occurs, which can improve the control performance and maintain the stable operation without a specific system structure system. Then, the convergence of event-triggered distributed secondary control with the condition of whether DoS attacks happen are analyzed. Finally, the effectiveness of the proposed control is verified on the hardware-in-loop (HIL) simulation platform consisting of the RT-LAB simulator, MATLAB/Simulink simulation model, and DSP controller.

Artificial intelligence and Automatic Identification Systems (AIS) play pivotal roles in intelligent maritime navigation for the modern maritime industry. Many artificial intelligence maritime applications based on AIS data have dramatically benefited traditional operations and managements in the field of maritime industry, and also provided state-of-the-art predictive analytics for vessel collisions and route optimization. However, the problem of modeling the interactions of vessels in complex waters still needs to be adequately addressed. In this paper, we focus on using spatiotemporal AIS data to model and forecast multiple vessel trajectories amid dynamic interaction patterns, and we propose a forecast model based on a novel neural network, namely a spatiotemporal multi-graph fusion network (STMGF-Net). The innovative STMGF-Net comprises three crucial modules. First, a Spatiotemporal graph construction module generates interaction graphs of various navigation modes, such as motions, risks, and attributes of vessels, Second, a multi-mode fusion module embeds and fuses the above interaction graphs into STMGF-Net. Finally, squeeze-and-excitation and temporal convolutional networks are introduced as Squeeze-and-excitation temporal convolutional modules to enhance the overall efficiency of the model significantly. Overall, the STMGF-Net can recognize complex spatiotemporal interaction patterns among neighboring vessels so as to capture and integrate these interaction features for achieving high-precision prediction performance in intelligent maritime navigation. In numerical experiments, three water areas of Zhoushan Islands, Yangshan Waters, and Yangtze River Waters are used as training and testing datasets. The results show that STMGF-Net improved prediction errors of average and final distance with increase of 49.637% and 50.622% than classic and state-of-art graph neural networks.

Broad learning system (BLS), which emerges as a lightweight network paradigm, has recently attracted great attention for recognition problems due to its good balance between efficiency and accuracy. However, the supervision mechanism in BLS and its variants generally relies on the strict binary label matrix, which imposes limitations on approximation and fails to adequately align with the data distribution. To address this issue, in this article, two novel flexible label-induced BLS models with the manifold manner are proposed, whose notable characteristics are as follows. First, two proposed label relaxation strategies can both enlarge the margins between different categories and simultaneously enhance the diversity within labels. Second, the integration of manifold geometrical criterion enables the models to capture local feature structures, ensuring the obtained flexible labels align better with the similarity between samples. Third, the proposed models can be optimized efficiently with the alternating direction method of multipliers. Each iteration benefits from a closed-form solution, facilitating the optimization process. Extensive experiments and thorough theoretical analysis are intended to show the advantages of our proposed models compared to other state-of-the-art recognition algorithms.

In this article, an adaptive reinforcement learning (RL) control problem is explored for a class of nonstrict-feedback discrete-time systems. First, different from the existing results, considering the noncausal problem which may exist in the backstepping design procedure, a universal system transformation method is first proposed for a class of nonstrict-feedback discrete-time systems. Second, by defining a compensation term to compensate the controller and utilizing the property of radial-basis-function neural network (RBFNN), an RL-based direct adaptive control strategy is developed via a backstepping method to achieve optimal control, and the multigradient recursive (MGR) algorithm is employed to estimate the weight vector. Finally, the stability of the control system is guaranteed and all signals in the closed-loop system are semiglobal uniformly ultimately bounded (SGUUB) on the basis of the Lyapunov theory. In addition, a universal system transformation is first proposed which breaks through the limitations on the controller design for the discrete-time nonstrict-feedback nonlinear system by using the traditional method. The validity of this strategy is verified by two simulation examples that include a course keeping system of the marine vessel.

In Mesh Wireless Networks (MWNs), the network coverage is extended by connecting Access Points (APs) in a mesh topology, where transmitting frames by multi-hop routing has to sustain the performances, such as end-to-end (E2E) delay and channel efficiency. Several recent studies have focused on minimizing E2E delay, but these methods are unable to adapt to the dynamic nature of MWNs. Meanwhile, reinforcement-learning-based methods offer better adaptability to dynamics but suffer from the problem of high-dimensional action spaces, leading to slower convergence. In this paper, we propose a multi-agent actor-critic reinforcement learning (MACRL) algorithm to optimize multiple objectives, specifically the minimization of E2E delay and the enhancement of channel efficiency. First, to reduce the action space and speed up the convergence in the dynamical optimization process, a centralized-critic-distributed-actor scheme is proposed. Then, a multi-objective reward balancing method is designed to dynamically balance the MWNs’ performances between the E2E delay and the channel efficiency. Finally, the trained MACRL algorithm is deployed in the QaulNet simulator to verify its effectiveness.

Digital twins (DTs), defined as the virtual representation of a real-world entity or system, act as a mirror to provide a way to simulate, predict physical behaviors, and possibly control the real-world entity where applicable. Originating in the industry, advances in computing capacity and recent progress in artificial intelligence (AI)-based analytics make DTs attractive to a broader set of use cases including mobile networks.

6G communication networks are expected to become an integral part of the infrastructure needed for developing a smart society in the future. Addressing the challenges on the road towards realizing 6G network requirements in terms of quality of service, user experience, and security, is therefore of utmost importance. The digital twin (DT) technology can potentially improve the efficiency, reliability, and security of 6G networks. Digital twins for mobile networks (DTMNs) are seen as a key factor in harnessing the full benefits of 6G. Using digital twins can help address several problems, including network optimization, fault diagnosis, and fault management. Furthermore, DTMNs can characterize the physical entities in a 6G network and their relationships to each other, build their virtual models, and use simulation, learning, and reasoning capabilities to make predictions and support informed decision-making,

Buildings account for nearly 40% of primary energy and 36% of greenhouse emissions, which is one of the main factors driving climate change. Reducing energy consumption in buildings toward zero-energy buildings is a vital pillar to ensure that future climate and energy targets are reached. However, due to the high uncertainty of building loads and customer comfort demands, and extremely nonlinear building thermal characteristics, developing an effective zero-energy building energy management (BEM) technology is facing great challenges. This article proposes a novel learning-based and iterative Internet of Things (IoT) system to address these challenges to achieve the zero-energy objective in BEM of connected buildings. First, all buildings in the IoT-based BEM system share their operation data with an aggregator. Second, the aggregator uses these historical data to train a deep reinforcement learning model based on the deep deterministic policy gradient method. The learning model generates precooling or preheating control actions to achieve zero-energy BEM for building heating ventilation and air conditioning (HVAC) systems. Third, for solving the coupling problem between HVAC systems and building internal heat gain loads, an iterative optimization algorithm is developed to integrate physics-based and learning-based models to minimize the deviation between the on-site solar photovoltaic generated energy and the actual building energy consumption by properly scheduling building loads, electric vehicle charging cycles, and the energy-storage system. Finally, the optimal load operation scheduling is generated by considering customers’ comfort requirements. All connected buildings then operate their loads based on the load operation schedule issued by the aggregator. The proposed learning-based and iterative IoT system is validated via simulation with real-world building data from the Pecan Street project.

For achieving the goal of two-way communication and power flows, smart grids are integrated with much state-of-the-art hardware and software. However, these newly added components also introduce a lot of vulnerabilities into the power systems, which results in that malicious users can launch various cyber–physical attacks to steal electricity. The existing electricity theft detection techniques suffer from an implicit assumption that malicious users tamper with smart meter readings to values much less than their actual electricity consumptions. These are called large-amount electricity theft (LET) attacks. Nevertheless, in the real world, some malicious users may be cautious enough to deliberately launch small-amount electricity theft (SET) attacks, where smart meter readings are manipulated to numbers slightly lower than the actual values, mainly to escape detection. To address this limitation, we propose a detector that is able to deal with both LET and SET attacks effectively. This detector applies a cumulative sum (CUSUM) control chart and a Shewhart control chart together to analyze users’ reported readings and measurements of a central observer meter. It consists of an electricity theft detection phase, which aims to detect the existence of LET/SET attacks timely and a malicious user identification phase, which aims to identify malicious users exactly. Extensive experiments are conducted to evaluate the proposed detector, and the results show that it has good performance in terms of several metrics.

For accommodating rapidly increasing power demands, power systems are transitioning from analog systems to systems with increasing digital control and communications. Although this modernization brings many far-reaching benefits, the hardware and software newly incorporated into the power systems also incur many vulnerabilities. By taking advantage of these vulnerabilities, adversaries can launch various cyber/physical attacks to tamper with electricity meter readings, i.e., to steal electricity. It is reported that total worldwide annual economic losses caused by electricity theft reached up to almost one hundred billion dollars in recent years. With methods to tamper with meter readings becoming more versatile, secret, and flexible, electricity theft tends to get even more serious in modernized power systems. For preventing adversaries from stealing electricity, researchers have done a lot of works. Although some related surveys on these works exist, they are not updated or just discuss electricity theft in a specific region. This survey aims to gain a comprehensive and in-depth understanding of the electricity theft issue. After investigating how adversaries tamper with meter readings, we systematically survey all existing detection methods up to date, which is classified into machine learning- and measurement mismatch-based methods. Adverse effects and political and socioeconomic factors of electricity theft are also provided. This survey can help relevant researchers to shape future research directions, especially in the area of developing new effective electricity theft detection methods.

The ongoing coronavirus disease 2019 (COVID-19) is a pandemic causing millions of deaths, devastating social and economic disruptions. Testing individuals for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen of COVID-19, is critical for mitigating and containing COVID-19. Many countries are implementing group testing strategies against COVID-19 to improve testing capacity and efficiency while saving required workloads and consumables. A group of individuals’ nasopharyngeal/oropharyngeal (NP/OP) swab samples is mixed to conduct one test. However, existing group testing methods neglect the fact that mixing samples usually leads to substantial dilution of viral ribonucleic acid (RNA) of SARS-CoV-2, which seriously impacts the sensitivity of tests. In this paper, we aim to screen individuals infected with COVID-19 with as few tests as possible, under the premise that the sensitivity of tests is high enough. To achieve this goal, we propose an Adaptive Group Testing (AdaGT) method. By collecting information on the number of positive and negative samples that have been identified during the screening process, the AdaGT method can estimate the ratio of positive samples in real-time. Based on this ratio, the AdaGT algorithm adjusts its testing strategy adaptively between an individual testing strategy and a group testing strategy. The group size of the group testing strategy is carefully selected to guarantee that the sensitivity of each test is higher than a predetermined threshold and that this group contains at most one positive sample on average. Theoretical performance analysis on the AdaGT algorithm is provided and then validated in experiments. Experimental results also show that the AdaGT algorithm outperforms existing methods in terms of efficiency and sensitivity.Note to Practitioners—Real-time reverse transcription-polymerase chain reaction (rRT-PCR) tests provide scope for automation and are one of the most widely used laboratory methods for detecting the SARS-CoV-2 virus. This paper is motivated by the following challenges: (1) Many countries are experiencing an acute shortage of professionals and consumables for conducting rRT-PCR tests; (2) Group sizes of existing group testing methods against COVID-19 may not be optimal, which adversely impacts the efficiency of the screening of the SARS-CoV-2 virus; (3) Existing group testing methods do not consider the fact that the sensitivity of rRT-PCR tests usually decreases with the group size. The objective of this paper is to improve the efficiency and sensitivity of large-scale screening against COVID-19. For achieving this goal, we propose an Adaptive Group Testing (AdaGT) algorithm, which has the following advantages: (1) It can improve the efficiency for screening the SARS-CoV-2 virus, mainly by adaptively adjusting its testing strategy between an individual testing strategy and a group testing strategy based upon an estimated ratio of positive samples during the screening process; (2) It can guarantee a high sensitivity of the rRT-PCR tests by determining the group sizes of the group testing strategy based upon some constraints; (3) We derive an appropriate threshold for the estimated ratio of positive samples such that the AdaGT algorithm can achieve a minimum average number of rRT-PCR tests and can be directly employed in practical applications.

Multiagent systems (MASs) are distributed systems with two or more intelligent agents. Formation control is a significant control technique of MASs. To date, formation control on MASs is widely used in various fields, such as robots, spacecrafts, satellites, and unmanned aerial/surface/underwater vehicles. However, there is a relatively small body of literature that is concerned with security problems of formation control on MASs in past years. Our research represents the first step toward developing security attacks of formation control on MASs. Our study aims to investigate potential security problems of formation control on a multirobot system for the first time. We propose two kinds of control-level attacks and each kind of attack includes several specific attack forms. Then, we discuss specific features of formation control on a classical multirobot system and utilize theoretical analyses to illustrate how cyberattacks can influence the physical movements of robots. The experimental results of the proposed attacks show that attacks can easily interrupt formation movements of a multirobot system and several carefully designed attacks even can cause irreversible loss.

This article investigates optimal control problem for a class of discrete-time (DT) nonlinear systems with unknown dynamics. With the help of a broad learning system (BLS), a novel online adaptive dynamic programming (ADP) controller is presented. First, to approximate the unknown system dynamics, an approximator based on BLS is presented. The connection weights are calculated by the data of the system by using the ridge regression algorithm. Then, two BLSs are adopted to approximate the optimal cost function and optimal control law, respectively. The connection weights of these two BLSs are updated using the given weights tuning law at each sampling instant. The proposed optimal controller is proved to ensure that all the system states and estimation errors are uniform ultimate bounded. Finally, simulation examples are carried out to further demonstrate the effectiveness of the proposed BLS-based approximator and optimal controller.

Divergences or their counterpart (dis)similarity measures of two probability distributions play an important role in information theory. Especially, Csiszar divergences have many forms. Among so many forms of Csiszar divergences, we plan to find which divergence is the best suit of the analysis of binary sensor deployments. A binary sensor outputs a binary digit 1 or 0 when detecting an object or not, respectively. Recently, modulators made of opaque materials are utilized to modulate the sensing view of binary sensors to enhance their spatial awareness. In this paper, we construct two probability models of binary sensors modulated by modulators, i.e., an ideal model and an actual deployment model. Moreover, we utilize 13 forms of Csiszar divergences to analyze the distribution of those probability models. Based on the divergence calculation results, we classify the 13 divergences into five classifications. Furthermore, we propose a smoothing method to deal with the events which are absent in the experiments, i.e., occurring with zero probability. Our experiment results show that the smoothing method eliminates the zero probabilities and has little influence on the nonzero probabilities. Finally, we select the best divergence among the 13 divergences to analyze binary sensors modulated with modulators.

Accurate prediction of vessel traffic flow plays a significant role in the field of modern intelligent transportation system. In order to enhance the prediction accuracy of vessel traffic flow, this paper combines genetic algorithm (GA) and Back Propagation neural network (BPNN) to build a prediction model. Based on the vessel traffic flow data of The Wuhan Yangtze River Bridge, the simulation experiments were carried out from 2013 to 2018. The average relative error of BPNN optimized by GA is 4.03%, which is better than the average relative error of direct BPNN prediction is 5.57%. The results show that accuracy of the prediction model using BPNN with GA optimization is higher than the traditional BPNN. The BPNN optimized by GA has achieved more ideal results in the forecast of vessel traffic flow. This paper provides the theoretical basis for the relevant decision-making of the water safety authorities so as to guarantee the water traffic safety.

A domain name system (DNS) is one of the most important infrastructures of the Internet communication. It is also a crucial point which is subjected to attacks. The largest distributed denial-of-service (DDoS) attack on October 21, 2016 has targeted a major DNS infrastructure named dynDNS. It was actually the Internet of Things (IoT) DNS flood attack that made more than half of websites in the United States unreachable for a significant amount of time. As we are using the Internet for everything in our life, especially health care and transportation, an attack of this type may cause a major disruption. Therefore, in this article, we are going to analyze the DNS flood attacks and propose two mitigation methods. We propose a load distributed mitigation process which will work as a quick escape route of the legitimate traffic from the attack field. Our solution mainly involves service level changes which can be implemented with collaboration among service providers. Also, our proposed solution is very cost effective as compared to the cost of downtime of the domain names caused by a DNS flood attack. Furthermore, we propose a benign-bot mitigation method and a business model for the method. In the benign-bot mitigation method, a bot program is installed in customers' DNS local servers to allow IP addresses of a list of paid businesses' websites to maintain in the caches so that the websites can be accessed even when the DNS servers are down.

Integrated with cutting-edge equipment and technologies, smart grid takes prominent advantages over traditional power systems. However, hardware and software techniques also bring smart grid numerous security concerns, especially various cyberattacks. Malicious users can launch cyberattacks to tamper with smart meters anytime and anywhere, mainly for the purpose of stealing electricity. This makes electricity theft much easier to commit and more difficult to detect. Researchers have devised many approaches to identify malicious users. However, these approaches suffer from either poor accuracy or expensive cost of deploying monitoring devices. This paper aims to locate malicious users using a limited number of monitoring devices (called inspectors) within the shortest detection time. Before inspectors conduct any inspection, suspicions that users steal electricity are comprehensively assessed, mainly through analyzing prior records of electricity theft as well as deviations between the reported and predicted normal consumptions. On the basis of these suspicions, we further propose a suspicion assessment-based inspection (SAI) algorithm, in which the users with the highest suspicions will be first probed individually. Then, the other users will be probed by a binary tree-based inspection strategy. The binary tree is built according to users' suspicions. The inspection order of the nodes on the binary tree is also determined by the suspicions. The experiment results show that the SAI algorithm outperforms the existing methods.

Domain Name System (DNS) is an important infrastructure of the Internet. However, DNS can be attacked by flooding DNS servers with tongs of DNS queries within a short time period. In this short paper, we analyze DNS attacks and propose a mitigation process.

Recently, many researchers multiplex binary infrared sensors in object tracking, habitat monitoring, and atypical behavior detection. Due to the binary digit output of binary sensors, multiplex binary sensors may lead to count the wrong number of targets when three or more targets present in the field of interest (FOI). We call this as the invisible targets' problem. To enhance the sensing results of sensors, a reference structure tomography technique is used to segment and code the FOI by modulating the sensing view of sensors. In this paper, we propose a subregion coding method to count targets moving in the FOI. Hexagon modulators are designed to make their projections segment the FOI into hexagon cells. We also propose a signature construct scheme to code cells and a encoder to count the number of targets in the FOI. Experiment results show that the accuracy to correctly count targets of our method is around 90% which is much better than 45% of a conventional method.

Electricity theft is a widespread problem that causes tremendous economic losses for all utility companies around the globe. As many countries struggle to update their antique power systems to emerging smart grids, more and more smart meters are deployed throughout the world. Compared with analog meters which can be tampered with by only physical attacks, smart meters can be manipulated by malicious users with both physical and cyber-attacks for the purpose of stealing electricity. Thus, electricity theft will become even more serious in a smart grid than in a traditional power system if utility companies do not implement efficient solutions. The goal of this paper is to identify all malicious users in a neighborhood area in a smart grid within the shortest detection time. We propose an adaptive binary splitting inspection (ABSI) algorithm which adopts a group testing method to locate the malicious users. There are two considered inspection strategies in this paper: a scanning method in which users will be inspected individually, and a binary search method by which a specific number of users will be examined as a whole. During the inspection process of our proposed scheme, the inspection strategy as well as the number of users in the groups to be inspected are adaptively adjusted. Simulation results show that the proposed ABSI algorithm outperforms existing methods.

Summary Transactional memory (TM) is a programming paradigm that facilitates parallel programming for multi‐core processors. In the last few years, some chip manufacturers provided hardware support for TM to reduce runtime overhead of Software Transactional Memory (STM). In this work, we offer two optimization techniques for TMs. The first technique focuses on Restricted Transactional Memory (RTM) in Intel's Haswell processor and shows that while in some applications, RTM improves performance over STM, in some others, it falls behind STM. We exploit this variability and propose an adaptive technique that switches between RTM and STM, statically. The second technique focuses on the overhead of TM and enhances the speed of the adaptive system. In particular, we focus on the size of transactions and improve performance by changing the transaction size. Optimizing the transaction size manually is a time‐consuming process and requires significant software engineering effort. We use a combination of Linear Regression (LR) and decision tree to decide on the transaction size, automatically. We evaluate our optimization techniques using a set of benchmarks from NAS, DiscoPoP, and STAMP benchmark suites. Our experimental results reveal that our optimization techniques are able to improve the performance of TM programs by 9% and energy‐delay by 15%, on average.

As the smart meters are vulnerable to physical attacks as well as cyber attacks, electricity theft in smart grids is much easier to commit and more difficult to detect than that in traditional power grids. In this paper, to facilitate the inspection of the malicious meters, a full and complete binary inspection tree whose leaves stand for smart meters is employed as a logical structure. We can logically configure an inspector (a meter for detection) at any node on the tree. By calculating the difference between the inspector’s reading and the summation of the readings reported from the smart meters on the subtree of one node, as well as the difference between the total amount of stolen electricity on the subtrees of an internal node and its left child, we propose a difference-comparison-based inspection algorithm which allows the inspector to skip a large number of nodes on the tree and hence accelerates the detection speed of the malicious meters remarkably. Furthermore, for quickly identifying a complete set of malicious meters, we propose an adaptive reporting mechanism which adopts much shorter reporting periods during the inspection process. Analysis with proofs about the performance bounds of the proposed algorithm in terms of the number of inspection steps is provided. Simulations not only validate the theoretical analysis, but also show the superiority of the proposed algorithm over the existing works in terms of inspection steps, regardless of the ratio and the permutation of malicious meters.

Many security models and systems are based on the assumption that super users must be trusted. It is difficult to hold super users accountable because they can erase any logs of their activities and impersonate as other users. This work proposes an accountable system administration model for operating systems where the notion of super users is removed and all system administrators must be accounted for their activities even if they are untrustworthy. The model is built upon a premise that such a system has multiple peer system administrators, and the peer system administrators ensure the logs of their activities are preserved and audited. The accountability policy and operating system primitives are designed and constructed so that the proposed model is provable. An enforcement mechanism that instantiates the model and enforces the policy is designed and implemented in Linux, a real-world operating system.

Transactional memory (TM) has become progressively widespread especially with hardware transactional memory implementation becoming increasingly available. In this paper, we focus on Restricted Transactional Memory (RTM) in Intel's Haswell processor and show that performance of RTM varies across applications. While RTM enhances performance of some applications relative to software transactional memory (STM), in some others, it degrades performance. We exploit this variability and present an adaptive system which is a static approach that switches between HTM and STM in transaction granularity. By incorporating a decision tree prediction module, we are able to predict the optimum TM system for a given transaction based on its characteristics. Our adaptive system supports both HTM and STM with the aim of increasing an application's performance. We show that our adaptive system has an average overall speedup of 20.82% over both TM systems.

Abstract Non‐Technical Loss (NTL) fraud is a class of typical frauds in the power grids. The main form of NTL frauds is “stealing electricity” in the traditional power grid. Smart Grid has the capability of two‐way communication and two‐way electricity flow, and thus, adversaries can take advantage of it to commit NTL frauds via much more complicated ways. Many schemes have been proposed to detect NTL frauds. However, their detection speeds need to be improved. In this paper, a fast NTL fraud detector, named FNFD, is proposed. FNFD is based on Recursive Least Square to model adversary behavior. Experimental results show that FNFD outperforms existing schemes regarding detection speed and overhead. Moreover, experimental results and theoretical analysis of parameter selection are also provided. We further study the stability and convergence of FNFD theoretically. The study shows that FNFD is always convergent as a control method if and only if the input dataset is persistent exciting. Copyright © 2016 John Wiley & Sons, Ltd.

Among the principals for securing smart grid infrastructure, accountability is one with lesser addressed concepts in smart grid literature. Even further, studies in the home area network are lacking in enforcement of accountable mechanisms as assigning responsibilities for devices’ actions are generally made the responsibility of the utility. This paper addresses accountability of devices in the home area network by providing a witness-based method for more accurate monitoring and estimation of the energy usage for devices whose power consumption varies while these devices are powered on. Algorithm analysis and simulation results show that the method is effective, and the method is well within the acceptable rate of error based on today's standards of estimation without need of previous knowledge of device profiles. Copyright © 2015 John Wiley & Sons, Ltd.

Abstract Security in computer systems has been a major concern since the very beginning. Although security has been addressed in various aspects, accountability is one of the main facets of security that is lacking in today's computer systems. The ability not only to detect errors but also to find the responsible entity/entities for the failure is crucial. In this paper, we intend to provide a comprehensive investigation of the state‐of‐the‐art accountability research issues in current information systems. Also, we study the various accountability tactics that are available and how each one of them contributes to providing strong accountability of different aspects. Finally, we examine the various merits and tradeoffs. Copyright © 2012 John Wiley & Sons, Ltd.

Abstract Logging has become a fundamental feature within the modern computer operating systems because of the fact that logging may be used through a variety of applications and fashion, such as system tuning, auditing, and intrusion detection systems. Syslog daemon is the logging implementation in Unix/Linux platforms, while Windows Event Log is the logging implementation in Microsoft Windows platforms. These logging implementations provide application program interfaces that, in turn, simplify logging functions from data collection to data storage. In this paper, we survey Unix, Linux, and Windows logging mechanisms and introduce their security issues. Copyright © 2016 John Wiley & Sons, Ltd.

A Vehicle-to-Grid (V2G) network raises challenges on privacy preserving, such as location privacy and secure payment. In this paper, we propose an Integrated Privacy-Preserving Data Management (IP2DM) architecture for Smart Grid V2G networks to guarantee the benefits of both sides of the users and the utility companies, and to protect data aggregation and data publication. Several techniques are designed and adopted to support this architecture. We analyze the security of this architecture facing various attacks. Experimental results show that this architecture is effective and efficient.

To detect the malicious meters committing electricity theft in a neighborhood area smart grid, in this paper, a novel inspection algorithm, termed as the Binary-Coded Grouping-based Inspection (BCGI) algorithm, is proposed. In the proposed algorithm, each meter is identified with a unique binary-coded number. The BCGI algorithm can locate the unique malicious meter (if any) by one inspection step under the assumption that at most one meter becomes malicious in one reporting period. Furthermore, by controlling the reporting periods of meters, we could make the probability of the event that at most one meter becomes malicious in one reporting period arbitrarily close to 1 under some assumptions. We further extend the algorithm into a Generalized BCGI algorithm (G-BCGI) to deal with the case that there are two or more meters which happen to commit the theft of electricity in one reporting period. Simulation results demonstrate the inspection efficiency of the BCGI and G-BCGI algorithms.

In this paper, we explore the malicious meter inspection (MMI) problem in neighborhood area smart grids. By exploiting a binary inspection tree, we propose a Difference-Comparison-based Inspection (DCI) algorithm to quickly target the malicious meters. Different from existing algorithms, the DCI algorithm is designed based on three rules that are derived according to the difference comparison results in each local subtree. An attractive feature of the DCI algorithm is that it manages to skip a large number of nodes on the binary inspection tree and thus accelerates the detection of malicious nodes. Both analysis and simulation results show that DCI outperforms the existing inspection algorithms in terms of inspection speed, regardless of the ratio and permutation of malicious meters.

In this paper, study how to achieve accountable logging for operating system using the flow-net logging and its implementation in current operating system such as Linux. We demonstrate that the flow-net logging technique is capable of preserving event relationship. The performance for the flow-net logging implementation in Linux operation system is evaluated.

Logging is a critical component of Linux auditing. The experiments indicate that the logging overhead can be significant. The paper aims to leverage the performance overhead introduced by Linux audit framework under various usage patterns. The study on the problem leads an adaptive audit logging mechanism. The adaptive auditing mechanism reduces the overall system overhead and achieves a similar level of protection on the system and network security.

Abstract Logging is a critical component of Linux auditing. However, our experiments indicate that the logging overhead can be significant. The paper aims to leverage the performance overhead introduced by Linux audit framework under various usage patterns. The study on the problem leads to an adaptive audit‐logging mechanism. Many security incidents or other important events are often accompanied with precursory events. We identify important precursory events – the vital signs of system activity and the audit events that must be recorded. We then design an adaptive auditing mechanism that increases or reduces the type of events collected and the frequency of events collected based upon the online analysis of the vital‐sign events. The adaptive auditing mechanism reduces the overall system overhead and achieves a similar level of protection on the system and network security. We further adopt LMbench to evaluate the performance of key operations in Linux with compliance to four security standards. Copyright © 2015 John Wiley & Sons, Ltd.

Although previous bio-inspired models have concentrated on invertebrates (such as ants), mammals such as primates with higher cognitive function are valuable for modeling the increasingly complex problems in engineering. Understanding primates' social and communication systems, and applying what is learned from them to engineering domains is likely to inspire solutions to a number of problems. This paper presents a novel bio-inspired approach to determine group size by researching and simulating primate society. Group size does matter for both primate society and digital entities. It is difficult to determine how to group mobile sensors/robots that patrol in a large area when many factors are considered such as patrol efficiency, wireless interference, coverage, inter/intragroup communications, etc. This paper presents a simulation-based theoretical study on patrolling strategies for robot groups with the comparison of large and small groups through simulations and theoretical results.

Abstract Power transmission is the bulk transfer of electrical energy from power plants to sub‐stations. A wireless sensor network is a promising technology for transmission line monitoring due to its low cost, easy installation, large‐scale coverage, and fault tolerance characteristics. A wireless sensor network is application‐specific; therefore, we investigate the new features and requirements of the wireless sensor network used in transmission line monitoring. Then, we propose an efficient wireless sensor network framework, which includes a clustering algorithm to simplify network management and to balance the network's energy consumption and a hybrid media access control (MAC) (H‐MAC) protocol to handle traffic variability. The framework takes advantage of the features of network topology and traffic pattern to optimize the protocols' performance on real time and energy efficiency. The results indicate that the H‐MAC shows a significant improvement in the network's reliability, real‐time performance, and energy efficiency, and the cluster hierarchy can balance the network's energy consumption. Furthermore, the cluster hierarchy also prolongs the network's lifetime. Copyright © 2014 John Wiley & Sons, Ltd.

In wireless sensor networks, data aggregation protocols are used to prolong the network lifetime. However, the problem of how to perform data aggregation while preserving data privacy is challenging. This paper presents a polynomial regression-based data aggregation protocol that preserves the privacy of sensor data. In the proposed protocol, sensor nodes represent their data as polynomial functions to reduce the amount of data transmission. In order to protect data privacy, sensor nodes secretly send coefficients of the polynomial functions to data aggregators instead of their original data. Data aggregation is performed on the basis of the concealed polynomial coefficients, and the base station is able to extract a good approximation of the network data from the aggregation result. The security analysis and simulation results show that the proposed scheme is able to reduce the amount of data transmission in the network while preserving data privacy. Copyright © 2013 John Wiley & Sons, Ltd.

Today's computer and network systems were not originally designed for accountability which plays a crucial role in information assurance systems. To assure accountability, each entity in the system should be held responsible for its own behaviors so that the entity is part of larger chains of the system's accountability. In this paper, we propose designs of a multiresolution flow-net scheme to achieve multiple degrees of accountability. We apply the multi-resolution flow-net on TCP/IP networks that are designed and organized with multiple layers. Simulation results are presented to verify the performance.

Non-Technical Loss (NTL) fraud is a consistent problem harassing utility companies all over the world. Most of the previous researches on NTL depend fully on user behaviour monitoring, analysis, and feature extraction. In this paper, we propose a practical scheme, named NTL Fraud Detection (NFD), to detect NTL without knowing any extra information about customers. The proposed scheme differentiates tampered meters from normal meters using the approximated difference between the billing electricity and the actually consumed electricity.

Supervisory control and data acquisition (SCADA) systems are widely used to monitor and control industrial processes. They provide the key functionality of real-time monitoring, logging/archiving, report generation, and automation for smart grid, which is a promising power delivery system for the near future. On the basis of these functionalities, various SCADA architectures, including hardware and software architecture, have been proposed and standardized; however, the most open and expediently growing areas in the smart grid are the infrastructure and technologies for the SCADA communication and security. In this paper, we provide a review for many documented standards in SCADA, and we also review its state-of-the-art communication and security aspects. Copyright © 2013 John Wiley & Sons, Ltd. We provide a review for many documented standards in SCADA, and we also review its state-of-the-art communication and security aspects.

ABSTRACT Information/secret leaking cannot always be recorded in digital log files. In other words, in log files, not all information/events are recorded, and it is thus impossible to trace the paths of secret leaking on the basis of log files alone. In this paper, to resolve the difficulty of the lack of information, we utilize user–relationship graphs, or social networks, to compensate for the required information. We also utilize a probabilistic analysis to build virtual links to follow information flows. User–relationship graphs are constructed from several flow‐net data structures over a longer period so that we can avoid missing embedded threats such as hostile codes. We call this approach virtual flow‐net. Copyright © 2011 John Wiley & Sons, Ltd.

ABSTRACT In this work, we will illustrate our attempt to exploit log files that are recorded locally on each node in a distributed system or a wired/wireless network. In order to improve the efficiency of retrieving data, we propose the idea of building a global view of the system with a clustered log‐collecting scheme; this would help the monitoring node gain a whole view of the system by building up and maintaining high‐level log files. We also introduce an efficient, tamper‐evident scheme to detect whether a local flow‐net has been deliberately compromised. We provide both simulation results and implementation of the proposed scheme on Emulab, a network testbed. Copyright © 2011 John Wiley & Sons, Ltd.

ABSTRACT In social groups, complex group behavior often emerges from the local interaction among simple individuals. Throughout this study, we assume that individuals can access information by way of wireless communication. In this case, individuals are able to exchange accurate information with each other as long as wireless communication links between them are allowed. Subsequently, we propose a consensus decision‐making model for studying the consistency of group behavior considering both the wireless communication range and the probability of successful communication. Our simulation results show the following conclusions: (i) consistency of the group behavior is absolutely achieved, when the wireless communication range is large enough and the probability of successful communicationp = 1; (ii) when the wireless communication range is large enough, the consistency of the group behavior is still achieved as long aspis bigger than some small constant; and (iii) the law in (iii) remains applicable when the number of individuals in the group changes. Therefore, one may infer that consistency of group behavior in mobile sensors is much more related to the extent of distribution of obtainable information than the amount of information, where the extent of distribution of obtainable information means that each individual can obtain information from wider area or from those individuals who are not only in its local area. Copyright © 2012 John Wiley & Sons, Ltd.

ABSTRACT In this study, a deterministic deployment problem in wireless sensor networks is examined. On the basis of information coverage, we study equilateral triangle and square deployment strategies, and we provide the maximum distance between sensors in order to reach the required detection probability for any point in the monitoring field. First, we provide a model of the signal attenuation. On the basis of the detected signal from the K sensors, the best linear and unbiased estimation is used to estimate the signal parameter with the corresponding error. For the equilateral triangle deployment, the maximum distance between sensors is computed and provided when the received signal data from two or three sensors is used. Similarly, we have computed and supplied the maximum distance between sensors in the square deployment. Simulations are performed to show the relationship between the number of sensors and the detection probability. The simulation results show that it is not a good choice to improve the detection probability with a larger number of sensors.Copyright © 2012 John Wiley & Sons, Ltd.

ABSTRACT To produce ciphertexts, two modes of encryption are applied—block ciphers, which encrypt a fixed size block of plaintext at a time, and stream ciphers, which encrypt stream data, one or more bits at a time. As one of stream ciphers, the cipher feedback (CFB) mode is implemented by a block cipher via multiple stages, and in each stage, 1 bit or a number of bits of plaintext are encrypted at a time. Throughout this paper, the study will focus upon the error performance of the stream‐based CFB under two sliding‐window protocols, go‐back‐N and selective‐reject, in an error channel in terms of throughput. We model the performance of the CFB in terms of application‐level throughput and derive the number of stages needed to achieve the optimal throughput, under a given error rate in an error channel. Copyright © 2012 John Wiley & Sons, Ltd.

SUMMARY Intruders that log in through a series of machines when conducting an attack are hard to trace because of the complex architecture of the Internet. The thumbprinting method provides an efficient way of tracing such intruders by determining whether two connections are part of the same connection chain. Because many connections are transient and therefore short in length, choosing the best time interval to thumbprint over can be an issue. In this paper, we provide a way to shorten the time interval used for thumbprinting. We then study some special properties of the thumbprinting function. We also study another mechanism for tracing intruders in the Internet based on a timestamping approach, which passively monitors flows between source and destination pairs. Given a potentially suspicious source, we identify its true destination. We compute the error probability of our algorithm and show that its value decreases exponentially as the observation time increases. Our simulation results show that our approach performs well. Copyright © 2012 John Wiley & Sons, Ltd.

ABSTRACT Data aggregation protocols are essential for wireless sensor networks to prolong network lifetime by reducing energy consumption of sensor nodes. For mission‐critical wireless sensor networks, however, not only the energy consumption of sensor nodes but also the correctness of the data aggregation results is critical. As wireless sensor networks are usually deployed in harsh and hostile environments, malfunctioning and/or compromised sensor nodes negatively affect the correctness of the data aggregation results. This paper presents a fault‐tolerant data aggregation scheme that eliminates the false data sent by malfunctioning and/or compromised sensor nodes. To conserve energy while eliminating false data, an in‐network outlier detection technique that is based on locality sensitive hashing scheme is used. The simulation results show that the proposed scheme is able to reduce the number of false data transmissions, thereby increasing the data aggregation accuracy. Moreover, it is also observed that the proposed scheme reduces the overall data transmission in the network. Copyright © 2012 John Wiley & Sons, Ltd.

ABSTRACT Reliability is a crucial aspect of time synchronization for industrial wireless applications in wireless sensor networks. Existing time synchronization algorithms often provide good synchronization in laboratory environments; however, outdoor environments with associated radio interference influence the performance of time synchronization. In this paper, we propose a random time source protocol for industrial wireless applications in wireless sensor network synchronization. Each synchronized node randomly selects its time source for each period in order to prevent reliance on a fixed time source because this may lead to resynchronization once the source fails. We have implemented the algorithm on the SIA2420 platform usingTinyOS, and the results show the reliability of our protocol. Copyright © 2011 John Wiley & Sons, Ltd.

ABSTRACT Accountability is a very important topic for computer and networking systems. It helps to answer questions such as, “What happened?” and, “Who did it?” These two questions are also related to forensics; however, forensics normally tries to answer these questions by adding some human factors (such as a guess or an instinct due to missing evidence, as well as human involvements) under the available system. Accountability, on the other hand, can only be achieved by significantly improving the current system with the result that forensics becomes trivial in an accountable system. Furthermore, each entity in the system must be held responsible for its activities. In order to provide accountability, a better logging system is necessary so that not only their activities but also their relationships may be captured. To this end, our previous work proposed a novel logging mechanism, flow‐net methodology, for accountability. In this paper, we extend the flow‐net methodology and present its design and implementation in wireless networks. We also evaluate the performance of flow‐net and compare it with that of audit log files. Copyright © 2011 John Wiley & Sons, Ltd.

ABSTRACT Network security is an important area in computer science. Although great efforts have already been made regarding security problems, networks are still threatened by all kinds of potential attacks, which may lead to huge damage and loss. Log files are main sources for security analysis. However, log files are not user friendly. It is laborious work to obtain useful information from log files. Compared with log files, visualization systems designed for security purposes provide more perceptive and effective sources for security analysis. Most security visualization systems are based on log files. In this paper, we provide a survey on visualization designs for computer network security. In this survey, we looked into different security visual analytics, and we organized them into five categories. Copyright © 2011 John Wiley & Sons, Ltd.

ABSTRACT With the advancement of computer and information technology, cyber crime is now becoming one of the most significant challenges facing law enforcement organizations. Cyber crimes are generally referred as criminal activities that use computers or networks. An understanding of the characteristics and nature of cyber crimes is important in helping research communities find ways to effectively prevent them. Most existing research focuses more on attacks and attack models, including either actual attacks or imaginary/possible attacks over all layers of networks or computers, but there has been less work carried out on a comprehensive survey of cyber crimes. This paper provides a survey of cyber crimes that have actually occurred. First, cyber crimes in the digital world are compared with crimes in the physical world. Then, cyber crimes are categorized according to the roles of computers or networks. Furthermore, we also notice that some cyber crimes are actually traditionally non‐cyber crimes that are facilitated by computers or networks. It is surprising that there are so many recurrent cyber crimes. More efforts are needed to protect people from cyber crimes. Copyright © 2011 John Wiley & Sons, Ltd.

We study load balancing of paging schemes for multitier hierarchical cellular networks, in which different tiers of cells overlay each other to provide multiple coverage in cellular service areas. Each mobile terminal (MT) can be paged in any tier of a multitier hierarchical cellular network. Paging requests are balanced in different waiting queues of different tiers, and the load balancing among them is achieved probabilistically among N tiers. The studied paging schemes are the Hierarchical Pipeline Paging scheme, the Hierarchical Sequential Paging scheme, and the Hierarchical Blanket Paging scheme. We study two optimization problems using the N-tier load balancing: 1) given a paging delay constraint, to minimize the total paging cost under the constraint that the total delay is upper bounded by a predefined total delay, and 2) given a bound on the total delay, to minimize the total paging cost under a paging delay constraint.

This paper investigates the fundamental performance limits of medium access control (MAC) protocols for particular multihop, RF-based wireless sensor networks and underwater sensor networks. A key aspect of this study is the modeling of a fair-access criterion that requires sensors to have an equal rate of underwater frame delivery to the base station. Tight upper bounds on network utilization and tight lower bounds on the minimum time between samples are derived for fixed linear and grid topologies. The significance of these bounds is two-fold: First, they hold for any MAC protocol under both single-channel and half-duplex radios; second, they are provably tight. For underwater sensor networks, under certain conditions, we derive a tight upper bound on network utilization and demonstrate a significant fact that the utilization in networks with propagation delay is larger than that in networks with no propagation delay. The challenge of this work about underwater sensor networks lies in the fact that the propagation delay impact on underwater sensor networks is difficult to model. Finally, we explore bounds in networks with more complex topologies.

A feasible architectural framework for the smart grid in home areas is provided based on the latest NIST (National Institute of Standards and Technology, U.S.) smart grid interoperability standards (release 1.0). In this paper, we propose an accountable communication protocol using this architecture with certain reasonable assumptions. Analysis results indicate that our design makes all power loads in home areas accountable.

In wireless sensor networks, data aggregation protocols are employed to prolong the network lifetime. However, performing data aggregation while preserving security is a challenging problem. This paper presents a polynomial regression based secure data aggregation protocol in which sensor nodes represent their sensed data as polynomial functions. Instead of their original data, sensor nodes secretly send coefficients of these polynomial functions to data aggregators. Data aggregation is performed based on these coefficients and the base station is able to extract a good approximation of the network data from the aggregation result. The security analysis and simulation results show that the proposed scheme is able to reduce the amount of data transmission in the network without compromising data confidentiality.

Non-repudiation is one of the challenges in smart grids. A malicious smart meter is capable of compromising the power readings without being detected since it may be the only device to measure the electricity service amount in local. This kind of attack can cause financial loss due to incorrect readings and bring dispute between the power provider and the subscriber. In this paper, we address the non-repudiation problem with respect to accountability in the neighborhood area smart grids. We propose a mutual inspection strategy which can detect problematic smart meters and prevent further financial loss. Our evaluation results show that this scheme can be effectively applied to smart grids.

Many security models and systems are built upon the assumption that super users are trustworthy. However, it becomes challenging to hold super users accountable since they can erase any trace of their activities. This paper proposes an accountable administration model for operating systems where all system administrators can be accounted for even if they are untrustworthy. The model is implemented in Linux, a real world operating system.

Although previous bio-inspired models have concentrated on invertebrates, such as ants, mammals, such as primates with higher cognitive function, are valuable for modeling the increasingly complex problems in engineering. Understanding primates’ social and communication systems and applying what is learned from them to engineering domains will likely lead to solutions to a number of problems. Scent-marking is an important behavior among primates and many other mammals. In this article, inspired by primates’ scent-marking activity, we propose and study a collaboration strategy for mobile and static sensors with RFID tags, where mobile sensors can be treated as robots or mobile actuators and can leave information to direct others to find them. Mobile sensors are equipped with RFID tags (or sensors) that can be deployed whenever needed, and RFID tags (or sensors) carry related information for other robots to pick up. We propose several primate-inspired communication mechanisms, including delayed-and-relayed and scent-trail communication among robots. We analytically model and simulate scent-trail communication. We also study a tracking and pursuing scheme of mobile sensors using simulations in terms of robot speeds, searching function, deployment density, turning function, and so on. We assume that robots (mobile sensors or mobile actuators) are capable of deploying/throwing-out sensors/RFID tags.

Abstract There has been increasing interest in deploying a team of robots, or robot swarms, to fulfill certain complicate tasks such as surveillance. Since robot swarms may move to areas of far distance, it is important to have a pervasive networking environment for communications among robots, administrators, and mobile users. In this paper, we first propose a pervasive architecture to integrate wireless mesh networks and robot swarm networks to build a robot swarm communication network within the areas of special interest. Under the proposed architecture, one or more robots can get connected with a nearby mesh router and access the remote server, while a self‐organizing mobilead hocnetwork is formed within each swarm for communications among the robots. We then address and analyze many important issues and challenges. Finally, we describe our work to enable this architecture through a scalable algorithm for autonomous swarm deployment and ROBOTRAK, a socket‐based‐swarm monitoring and control toolkit. Extensive simulation results and demonstrations are presented to show the desirable features of the proposed algorithm and toolkit. Copyright © 2009 John Wiley & Sons, Ltd.

Abstract Wireless process control has been a popular topic recently in the field of industrial control. In the industrial field, wireless technologies are considered despite the lack of an ideal industrial wireless standard. However, application development of industrial wireless networks is slow due to the lack of an ideal standard. Open standards are the foundation of industrial wireless application extensions. This paper first summarizes a standardized process for industrial wireless network technologies and then introduces network composition, network topology, protocol stack architecture, and some key protocol technologies of WIA‐PA, which is an international specification of industrial wireless networks for process automation. Furthermore, a comparison between WIA‐PA and other main industrial wireless network specifications like WirelessHART and ISA100.11a is provided. Architecture and key technologies of a WIA‐PA are also introduced. Our first‐hand experiences in developing WIA‐PA testbed based on the modularization method are given. Finally, experiment results illustrate the performance and efficiency of WIA‐PA. Copyright © 2010 John Wiley & Sons, Ltd.

Abstract In this paper, we use a multiple recursive generator (MRG) to generate sequences of numbers with very long periods, i.e., pseudo‐random sequences. The MRG effectively constructs a block cipher which satisfies important quality requirements such as security, long period, randomness, and efficiency. We compare our approach with another lightweight block cipher based on a linear congruential generator (LCG) and analyze the efficiency in terms of the number of basic operations that are being performed. We also study the effects of using special classes of MRG which hold certain portability and efficiency properties, and analyze their advantages in this context. The proposed cipher is a lightweight cipher, which is very useful for resource limited resources such as sensor nodes in sensor networks, radio frequency identification (RFID) tags, etc. Copyright © 2010 John Wiley & Sons, Ltd.

The rapid development of wireless technology plays extremely important roles in monitoring and control related applications nowadays.This special issue aims at bringing together state-of-the-art contributions of wireless monitoring, control, actuator coordination as well as their co-designs.It is shown in this proposal that there are a number of potential contributors, as well as reviewers, with original research results to this special issue, and the guest editors are capable of managing the special issue.In recent years, the demand for wireless communications in many monitoring and control applications has grown tremendously, such as military, aerospace, industrial, commercial, environmental, and health monitoring, etc.Some new technologies like Zigbee, Wi-Fi, Mobile Robots, and Bluetooth have already made significant contribution to data acquisition.At the same time, there arise some new challenges to guarantee a highly reliable, accurate and fault-tolerant process.It is a critical issue to develop innovative approaches to deal with multi-variable, multi-space problem domains (detection, identification, tracking, data fusion, energy-efficiency, and fault-tolerant framework) as well as practical implementation in wireless monitoring and control application.The purpose of the special issue is to focus on the novel ways by which monitoring, detection, identification, coordination, and control schemes are applied in wireless monitoring and control applications.Specific areas of interest include (but are not limited to):

Abstract Sensor networks are adopted in many surveillance applications. A traditional method for such applications is to deploy sensor nodes all over the surveillance region in order to cover as much area as possible. However, this way not only waste huge amounts of money for sensor nodes and resources, but it is also unnecessary and unrealistic sometimes. It provides huge amounts of garbage in the form of dead sensor nodes and batteries. It invokes many data collisions and places a serious burden on network protocols. In many applications, we have no need to have detail on every point inside the area, but only in some critical places. For example, in a forest fire surveillance application, covering the whole forest is unnecessary and unrealistic. In this paper, we propose a divide‐ and conquer‐based surveillance framework, in which a large surveillance area is divided into small areas by critical points and critical lines. Sensor nodes, sinks, robots, and RFID tags are all used. We only deploy sensor nodes along critical lines instead of all over the region. Our aim is to do surveillance with efficient deployment of sensor nodes and sinks, and to detect, track, and even capture targets, e.g., an intrusion tank or forest fire, with the collaboration of robots and sensor nodes. We study boundary coverage along critical lines. Robots perform tasks of patrolling, handling incidents, communicating with sensor nodes/sinks, and even being capable of deploying/throwing‐out sensor nodes/RFID tags. Finally, we evaluate perimeter coverage, robot patrol routing, and so on. Copyright © 2009 John Wiley & Sons, Ltd.

In this paper, we propose an implementation scheme of flow-net which is designed to record events and their relations. Different implementation schemes of the flow-net are introduced and compared. Under the collaboration of the nodes in a network, all of the events in the network are recorded and the relations of the events can be clearly described by flow-net. Because of the clear description of the events' relations, flow-net can be used to detect attacks in networks by using the fingerprint of the attacks.

This paper explores the segmentation of a monitoring space generated by binary pyroelectric sensors and reference structure. Each segment in the monitoring space can be identified by a state of a family of binary sensors, called a signature. In this paper, we show that the maximum number of signatures in a sensor network with n binary sensors is 2nand that it can be achieved by n modulators under a defined procedure and one assumption. Furthermore, we prove that the maximum number of signatures can be achieved in a sensor network with n binary sensors without the constraint of the number of modulators. Finally, we explore the signature combination for several simple cases.

In this paper, we explore a quantitative approach to accountable wireless multi-hop networks. We propose using hierarchical P-Accountability to adapt the requirements of modeling a complex network environment and assess the degree of accountability in a fine-grained manner. We have defined P-Accountability and demonstrated its use in the hierarchical network environment. In addition, we apply P-Accountability to a wireless multi-hop network system. Both numerical and simulation results show that our approach is applicable to most accountable systems and that it provides a flexible and comprehensive view of the degree of accountability.

In the following paper, we study the tradeoff between network utility and network lifetime for energy-constrained wireless sensor networks (WSNs). By introducing a weighted factor, we combine these two objectives into a single weighted objective, and we consider rate control and routing in this tradeoff framework simultaneously. First, by using a dual decomposition method, we decompose the tradeoff model into two subproblems: the congestion control/routing problem and the network lifetime problem, both of which interact through the dual variables for energy dissipation constraints. Based on the decomposition results, we propose a fully distributed algorithm to solve these two sub-problems and the dual problem by using gradient and sub-gradient projection methods. Second, we propose a fully distributed algorithm by approximating the network lifetime maximization problem by using the network utility maximization (NUM) framework. Third, we extend our distributed algorithm to deal with reliable communication and the real-time requirement. Rigorous analysis and simulations are presented to validate our algorithms.

In wireless sensor networks, some sensor nodes are put in sleep mode while other sensor nodes are in active mode for sensing and communication tasks in order to reduce energy consumption and extend network lifetime. This approach is a special case (k=2) of a randomized scheduling algorithm, in which k subsets of sensors work alternatively. In this paper, we first study the randomized scheduling algorithm via both analysis and simulations in terms of network coverage intensity, detection delay, and detection probability. We further study asymptotic coverage and other properties. Finally, we analyze a problem of maximizing network lifetime under quality of service constraints such as bounded detection delay, detection probability, and network coverage intensity. We prove that the optimal solution exists, and provide conditions of the existence of the optimal solutions.

In this paper, inspired by the society of animals, we study the coalition formation of robots for detecting intrusions using game theory. We consider coalition formation in a group of three robots that detect and capture intrusions in a closed curve loop. In our analytical model, individuals seek alliances if they think that their detect regions are too short to gain an intrusion capturing probability larger than their own. We assume that coalition seeking has an investment cost and that the formation of a coalition determines the outcomes of parities, with the detect length of a coalition simply being the sum of those of separate coalition members. We derive that, for any cost, always detecting alone is an evolutionarily stable strategy (ESS), and that, if the cost is below a threshold, always trying to form a coalition is an ESS (thus a three-way coalition arises).

In this paper, we study the overhead introduced by the advanced encryption standard cipher in the context of wireless LANs, specifically at the medium access control layer, as described in the 802.11 standard developed by the 802.11n task group. The advanced encryption standard is incorporated into existing aggregation schemes for 802.11 wireless LANs in order to achieve secure transmission of frames. We compute the maximum throughput, optimal frame, and fragment sizes which can be achieved in this context and compare them to the optimal values when encryption is not used. We evaluate the delay performance of such a scheme in the context of encryption and study asymptotic properties of the medium access control layer efficiency, expected frame size, and throughput.

Wireless sensor networks consist of a large number of sensors and have been broadly used for intrusion detection in surveillance systems. To guarantee detection quality, such networks are usually over-engineered, i.e., more than required sensors are deployed and remain active in order to cover each point in the monitored field with a high probability at any time instance. Existing sensor scheduling schemes based on the point coverage model tightly weave a sensor "net" that is unnecessarily dense. Intuitively, when the size and the shape of intrusion objects are considered, any net with holes no smaller than the size of the intrusion object would work fine. With this design philosophy in mind, we build a new mathematical model to investigate the impact of size and shape of intrusion objects on network configuration. We derive analytical results that provide practitioners with insights on how to weave an effective sensor "net" for intrusion object detection with minimum number of active sensors.

In this paper, we study a true coalition formation of three robots (i.e., 2 robots vs. 1 robot) in order to detect and capture intrusions in a curved loop. A coalition benefits robots by increasing detection and capture strength, but it has a tradeoff of paying an investment cost for each individual

A new analytical model based on Parallel Space-Time Markov Chain concept is presented for performance evaluation of IEEE 802.11 DCF MAC in multi-hop ad hoc networks. The proposed framework is able to model hidden-terminal problem and the aforementioned unreachability phenomena in such networks precisely. To the best of our knowledge, the proposed framework is one of the leading approaches in finite load analysis of multi-hop ad hoc networks taking into account backoff and post-backoff processes, in addition to the MAC sub-layer transmission queue status in an integrated fashion. Based on the proposed model, we provide an extensive throughput performance evaluation of practical multi-hop networks based on IEEE 802.11 DCF MAC.

To achieve better performance, we adopt a heterogeneous sensor network (HSN) model. In many applications, the locations of some sensor nodes are controllable. In this paper, first we propose a novel density-varying deployment scheme for high-end sensors (H-sensors) in an HSN. The scheme solves the bottleneck problem in typical many-to-one sensor networks. We then study the optimal placement of H-sensors whose locations are controllable. The goal is to use the minimum number of H-sensors for ensuring successful data delivery, coverage and connectivity in a network for a given lifetime. We present an effective H-sensor placement scheme that can simultaneously achieve coverage, connectivity and data relay requirements while uses a small number of H-sensors. Both theoretical proofs and simulation results demonstrate that the proposed H-sensor placement scheme achieves very good performance.

Large propagation delay and node movement are considered to be two significant attributes that differentiate an underwater wireless sensor network (UWSN) from a ground wireless sensor network (WSN). Considering the effects of both propagation delay and movement, we propose a time synchronization algorithm suitable for a UWSN. An underwater node can move out of and into another node's range frequently. With the proposed algorithm, no time synchronization is necessary if the time stamps of the received data packets are within the tolerance. In this fashion, the network underwater does not need to perform global time synchronizations periodically, which reduces the time used to synchronize clocks among sensor nodes. The simulation results show the time cost for synchronization is linear to the data packets exchanged.

In this paper, we study the overhead introduced by the advanced encryption standard cipher in the context of wireless LANs, specifically at the medium access control layer, as described in the 802.11 standard developed by the 802.11n task group. We compute the maximum throughput, optimal frame, and fragment sizes which can be achieved in this context and compare them to the optimal values when encryption is not used.

Wireless sensor networks have been widely used in environment and habitat monitoring, as well as in military applications such as battlefield surveillance. In this paper, we focus on detecting intruders in such surveillance systems. Our goal is to optimize the network coverage when the network is deployed to detect an intrusion object with the shape of a disc or a rectangle. We study how the size and shape of the intrusion object influence the configuration of the sensor network. We prove many mathematical results related to detection probability and intrusion coverage intensity and study the asymptotic properties of these detection metrics. We also study the problem of maximizing network lifetime under some QoS constraints. We prove the existence of the solution and derive the explicit form of the solution under certain conditions.

In this paper, we propose a divide and conquer based surveillance framework, in which a large surveillance area is divided into small areas by critical points and critical lines. Sensor nodes, sinks, robots, and RFID tags are all used. We deploy sensor nodes along critical lines only instead of all over the region. Our aim is to do surveillance with efficient deployment of sensor nodes and sinks, and to detect then track and even capture targets, e.g., an intrusion tank or forest fire, with the collaboration of robots and sensor nodes.

Scent-marking is an important activity among primates as well as other primates and accomplished through deploying chemicals with irritating odor such as urine at prominent locations. In this paper, we propose a primate-inspired scent-marking collaboration strategy for mobile and static sensors with RFID tags. We study the proposed scheme using simulations in terms of robot speeds, searching function, turning function, etc.

This paper investigates fundamental performance limits of medium access control (MAC) protocols for particular underwater multi-hop sensor networks under a fair-access criterion requiring that sensors have an equal rate of underwater frame delivery to a base station. Tight upper bounds on network utilization and tight lower bounds on minimum time between samples are derived for fixed linear topology. The paper also examines the implication of the end-to-end performance bounds regarding the traffic rate and sensing time interval of individual sensors.

A medium access control (MAC) protocol to address the so-called unreachability problem in mobile ad hoc networks is proposed. Stations maintain double hop neighborhood graphs and exchange designated eMAC tables to share their knowledge about their neighborhood topology. An adaptive table broadcasting technique to facilitate topology information dissemination in mobile ad hoc networks is also proposed. Performance of the proposed schemes is evaluated and compared with earlier schemes through simulations. Our results show performance enhancement due to better handling of unreachability, possible heterogeneous power distributions among contending stations, and mobility issues.

Many elder patients have multiple health conditions such as heart attacks (of various kinds), brain problems (such as seizure, mental disorder, etc.), high blood pressure, etc. Monitoring those conditions needs different types of sensors for analog signal data acquisition, such as electrocardiogram (ECG) for heart beats, electroencephalogram (EEG) for brain signals, and electromyogram (EMG) for muscles motions. To reduce mobile-health (m-health) cost, the above sensors should be made in tiny size, low memory, and long-term battery operations. We have designed a series of medical sensors with wireless networking capabilities. In this paper, we report our work in three aspects: (1) networked embedded system design, (2) network congestion reduction, and (3) network loss compensation. First, for networked embedded system design, we have designed an integrated wireless sensor network hardware / software platform for multi-condition patient monitoring. Such a system integrates ECG/EEG/other sensors with Radio Frequency Identification (RFID) into a Radio Frequency (RF) board through a programmable interface chip, called PSoc. Second, for network congestion reduction, the interface chip can use compressive signal processing to extract bio-signal feature parameters and only transmit those parameters. This provides an alternative approach to sensor network congestion reduction that aims to alleviate ?hot spot? issues. Third, for network loss compensation, we have designed wireless loss recovery schemes for different situations as follows. (1) If original sensor data streams are transmitted, network congestion will be a big concern due to the heavy traffic. A receiver-only loss prediction will be a good solution. (2) If the signal parameters are transmitted, the transmission loss mandates a 100% recovery rate. We have comprehensively compared the performance of those schemes. The proposed mechanisms for m-health system have potentially significant impacts on today's elder nursing home management and other mobile patient monitoring applications.

Abstract Anonymity is an important security aspect of wireless communications and has continuously attracted significant attention. Implementing anonymity of mobile users not only protects their privacy but also reduces the chances of attacks based on impersonation; therefore security can be improved. Untraceability is a related issue to anonymity. If a user is traceable, its hidden identity can be revealed through profiling the activities associated to a user. In this paper, we conduct a survey on anonymity issues of wireless communication systems. We first discuss general issues of anonymity in wireless communication systems. Then we survey some protocols in the literature, which are designed for wireless mobile systems as well as wirelessad hocnetworks. Copyright © 2008 John Wiley & Sons, Ltd.

Abstract Wireless sensor network security requires the cryptography software extremely low complex and energy efficient due to the limited memory and CPU capacity in a sensor. The NTRU (Nth degree truncated polynomial ring) encrypt algorithm has been shown to provide certain advantages when designing low power and resource constrained systems, while still providing comparable security levels to higher complexity algorithms. Unlike the current works that build NTRU software in a chip, this research focuses on the hardware implementation of NTRU algorithms because hardware implementation has much higher execution speed than software implementation. In contrast to previous research, the focus is shifted away from specific optimizations but rather provides a study of many of the recommended practices and suggested optimizations with particular emphasis on polynomial arithmetic and parameter selection. Recommendations for algorithm and parameter selection are made regarding implementation in hardware with respect to the resources available. Copyright © 2008 John Wiley & Sons, Ltd.

Abstract WiFi is becoming increasingly prevalent nowadays, whether as a simple range extender for a home wired Ethernet interface or a wireless deployment throughout an enterprise. Wireless local area networks (WLANs) provide us with mobility, convenience, and low cost. At the same time, WiFi is unsafe and is more vulnerable than traditional Ethernet, so that anyone familiar with wireless networks can initiate an attack. One strategy to identify potentially malicious unauthorized users is through packet capturing. Although there are several software products available for packet capture, there is currently no paper in the literature that describes how to build a software tool to capture WiFi frames and its associated functions. In this paper, we present how we build our frame capture tool along with a set of implementation techniques for automatically capturing all the frames and analyzing an attack on a WiFi. In our research, we focus on the WiFi medium access control (MAC) layer for wireless network analysis. We also discuss what we learned and the limitations which we discovered when implementing the tool. Copyright © 2009 John Wiley & Sons, Ltd.

Previous research on sensor network security mainly considers homogeneous sensor networks, where all sensor nodes have the same capabilities. Research has shown that homogeneous ad hoc networks have poor performance and scalability. The many-to-one traffic pattern dominates in sensor networks, and hence a sensor may only communicate with a small portion of its neighbors. Key management is a fundamental security operation. Most existing key management schemes try to establish shared keys for all pairs of neighbor sensors, no matter whether these nodes communicate with each other or not, and this causes large overhead. In this paper, we adopt a Heterogeneous Sensor Network (HSN) model for better performance and security. We propose a novel routing-driven key management scheme, which only establishes shared keys for neighbor sensors that communicate with each other. We utilize Elliptic Curve Cryptography in the design of an efficient key management scheme for sensor nodes. The performance evaluation and security analysis show that our key management scheme can provide better security with significant reductions on communication overhead, storage space and energy consumption than other key management schemes.

Ultra-wideband (UWB) is a new technology that enables wireless connectivity with consistent high data rates across multiple devices, such as high-definition television (HDTV) receivers, PCs, printers and digital cameras, within the digital home, and the office. In this paper, we focus on UWB transmissions where multiple accesses to the channel are coordinated by the IEEE 802.15.3 medium access control mechanism proposed in the IEEE 802.15.3a task group. Advanced encryption standard (AES), the most popular encryption cipher used nowadays, is used to ensure the security of the transmission. We study the overhead introduced by applying the AES cipher to the transmitted frames. Specifically, we analyze the tradeoff between throughput, payload size, and channel error when AES is used to encrypt the frames.

Block ciphers encrypt a fixed size block of plaintext at a time to produce a block of ciphertext. Stream ciphers encrypt stream data, such as voice or Telnet traffic, one bit or more bits at a time. The cipher feedback mode is a stream cipher implemented by a block cipher via multiple stages, and in each stage one bit or a number of bits of plaintext are encrypted at a time. In this paper, we study error performance of the stream-based cipher feedback mode in an unreliable wireless channel in terms of throughput. We model performance of the cipher feedback mode in terms of the probability that part of or the whole ciphertext can not be successfully decrypted, and the throughput by adopting the cipher feedback mode. We explicitly derive the optimal number of stages in the cipher feedback mode to achieve the optimal throughput, given an error rate in a wireless network. We also prove that for the cipher feedback mode, the whole ciphertext is successfully decrypted if and only if the whole ciphertext is successfully transmitted.

We propose a hierarchical pipeline paging (HPP) for multi-tier hierarchical cellular networks, in which different tiers overlay with one another to provide overlapped coverage of cellular service, and each mobile terminal can be paged in any tier of a network. Paging requests (PRs) are queued in different waiting queues, and multiple PRs in each waiting queue are served in a pipeline manner. We study HPP, hierarchical sequential paging (HSP), and hierarchical blanket paging (HBP) schemes analytically in terms of discovery rate, total delay, paging delay, and cost. It is shown that HPP scheme outperforms both HBP and HSP schemes in terms of discovery rate while maintaining the same cost as HSP scheme. The HPP scheme outperforms HSP scheme in terms of total delay and has a lower total delay than HBP scheme when traffic load is high.

Abstract Wireless transmission of a patient's electrocardiogram (ECG) signals can be used to reduce cardiac healthcare cost. However, wireless transmissions have high error rates due to radio interference. The ECG signal, where every second of data could mean abnormal patterns, cannot tolerate such losses. Due to this healthcare crisis, the ability for a device to remotely monitor a patient's medication intake and transmit accurate ECG readings, while being cost efficient, is a major innovation. In this research, we integrate a multi‐hop wireless sensor network (WSN) with radio frequency identification (RFID) readers. Our system has two distinct features: (1) remotely supervise patient medication intakeviaRFID technology, and (2) accurately and remotely transmitting a patient's ECG by adopting extended Kalman filter (EKF) for wireless error recovery. Copyright © 2008 John Wiley & Sons, Ltd.

Abstract An event‐to‐sink reliable transport (ESRT) control scheme was recently proposed to address the event‐to‐sink reliability issues in wireless sensor network (WSN). In this paper, we study the performance of ESRT in the presence of ‘over‐demanding’ event reliability, using both the analytical and simulation approaches. We show that the ESRT protocol does not achieve optimum reliability and begins to fluctuate between two inefficient network states. With insights from update mechanism in ESRT, we propose a new algorithm, called enhanced ESRT (E2SRT), to solve the ‘over‐demanding’ event reliability problem and to stabilize the network. Simulation results show that E2SRT outperforms ESRT in terms of both reliability and energy consumption in the presence of ‘over‐demanding’ event reliability. Besides, it ensures robust convergence in the presence of dynamic network environments. Copyright © 2008 John Wiley & Sons, Ltd.

In this paper, we propose to use a Multiple Recursive Generator (MRG) to generate sequences of numbers with very long periods, i.e., pseudo-random sequences. The MRG effectively constructs a block cipher which satisfies important quality requirements such as security, long period, randomness, and efficiency. The proposed cipher is a light weight cipher, which is very useful for resource limited resources such as sensor nodes in sensor networks, RFID tags, etc.

Wireless sensor networks are usually over-engineered, i.e., more than required sensors are deployed and remain active in order to cover each point in the monitored field with a high probability at any time instance. Intuitively, when the size and the shape of objects are considered, any net with holes no smaller than the size of the object would work fine. In this paper, we build a mathematical model to investigate the impact of size and shape of objects on network configuration. We derive analytical results that provide practitioners with insights on how to weave an effective sensor "net" for object detection with minimum number of active sensors.

In this paper, based on our proposed mal-packet self-propagation models in wireless sensor networks, we use TOSSIM to study their propagation dynamics. We also present a preliminary study of the feasibility of mal-packet defense in sensor networks. Specifically, based on random graph theory and percolation theory, we propose the immunization of the highly-connected nodes in order to partition the network into as many separate pieces as possible, thus preventing or slowing down the mal-packet propagation. We study the percolation threshold of different network densities and the effectiveness of immunization in terms of connection ratio, remaining link ratio, and distribution of component sizes. We also present an analysis of the distribution of component sizes.

Channel capacity and node energy represent resources and constraints in designing efficient routing schemes for Wireless Sensor Networks(WSNs). To delivery more data, a higher rate is desirable, which however consumes more energy and may demand more bandwidth. Hence, data transmission in WSNs should take into account both limited capacity and constrained energy. In this paper, we propose an utility-based nonlinear convex optimization formulation to maximize utility subject to the capacity and energy constraints. To achieve this, we introduce link interference set to represent all flows contention over a link, and it offers the capacity constraint over the specific link. For each node, we express the energy constraint with network lifetime requirement. A distributed solution with dual decomposition approach is proposed to address the optimization formulation. In addition, an Optimal Rate Routing (ORR) is developed by incorporating the optimization result to select the optimal rate route. Comparing with the previous schemes, ORR is able to achieve the highest utility, optimal rate selection during routing, and well-balanced performance.

This paper presents a theoretical model of control and communication over wireless sensor and actuator networks (WSANs). We propose two control schemes, a centralized control scheme (CC) in which decisions are made based on global information, and a distributed control scheme (DC) that enables distributed actuators to make decisions locally. Because of global information, CC can obtain optimal control at each step. However, when that information is delivered over lossy wireless channels, it could become unstable. It is demonstrated by simulations that DC could also stabilize the control system analogously with the CC, though with more steps.

Security is critical for wireless sensor networks deployed in military, homeland security and other hostile environments. In this paper, we study a security issue related with broadcast in sensor networks. Due to the broadcast nature of wireless communications, often it is more efficient to broadcast packets to sensor nodes. Typically, broadcast authentication is achieved by digital signatures. Since digital signature operations are expensive for small sensor nodes, an attacker can launch a serious denial of service (DoS) attack. That is, an attacker may forge a large number of broadcast messages with digital signatures, and then force sensor nodes to verify these signatures, which can cause them run out of power. In this paper, we present an effective and efficient scheme that can defend such DoS attack on broadcast authentication. Our performance evaluation shows that the scheme is much more secure and efficient than an existing scheme.

Many performance evaluations for IEEE 802.11 distributed coordination function (DCF) have been formerly reported in the literature; most studies are based on saturation analysis, and a few models under a finite load condition adopt an M/G/l queuing system. However, using M/G/l queuing only considers the first moment of frame service time to derive the probability of transmission queue being vacant. In this paper, we model the DCF using Parallel Space-Time Markov Chain (PSTMC), in which frame arrivals are tracked by monitoring the transmission queue during transitions between successive states of the space-time Markov chain. The proposed framework provides the possibility of modeling the contention phase, backoff and post-backoff procedures, and the transmission queue status. The proposed framework is validated by the simulation results.

In this paper, we discuss how to prevent users' passwords from being stolen by adversaries. We propose a virtual password concept involving a small amount of human computing to secure users' passwords in on-line environments. We adopt user-determined randomized linear generation functions to secure users' passwords based on the fact that a server has more information than any adversary does. We analyze how the proposed scheme defends against phishing, key logger, and shoulder-surfing attacks.

With the availability of multiple rates in IEEE 802.11 a/b/g wireless LANs, it is desirable to improve the network capacity and temporal fairness by sending multiple consecutive frames over high rate links, as proposed in opportunistic auto rate (OAR [1]). However, the basic OAR does not provide quality of service (QoS) guarantee and thus is not sufficient in supporting real time voice/video traffic. In this paper, we further enhance the OAR protocol with a set of QoS mechanisms. The proposed QOAR protocol consists of two protocols: (i) a traffic- differentiating flow weight adaptation protocol (FWA) that dynamically tunes both contention window and concatenation number per channel access; (ii) an admission control protocol (AC) that guarantees the bandwidth/delay requirements of multimedia services. Extensive simulation studies show that QOAR enables QoS for real-time traffic yet maximizes performance of best effort traffic.

Worms have become an emergent threat towards information confidentiality, integrity, and service availability. While playing an important role for people to interact with surrounding environments, wireless sensor networks suffer from growing security concerns posed by worms because of sensor networks' low physical security, lack of resilience and robustness of underlying operating systems, and the ever increased complexity of deployed applications. In this paper, we study worm propagation in 802.15.4 based wireless sensor networks. First we present a baseline worm model in the context of wireless sensor networks. Then we describe a preliminary study of the impact of various protocol parameters and network scenarios on worm propagation dynamics. Our simulation study can provide insight into deriving a suitable model to characterize worm propagation in sensor networks.

Behaviors of users in a computer or a computer network can be observed by system authorities via logs of all the actions. In a computer or network system, if at some point the fact that the content of a secret file is leaking has been already known, to figure out the reasons of the leaking, we can search partial or entire log files to find out direct or indirect accesses to the file; since a user who accessed the secret before may send messages containing the secret to other users (the secret is leaking due to indirect accesses) via packets in a computer network, or via pipe/FIFO/message-queue/etc. in a computer system, finding the reasons of the leaking is not a trivial task. In this paper, we analyze and simulate the complexity of retrieving knowledge from the computer and network auditing log database for forensics and accountability.

Icebergs denote data items whose total frequency of occurrence is greater than a given threshold. When data items are scattered across a large number of network nodes, searching for global icebergs becomes a challenging task especially in bandwidth limited wireless networks. Existing solutions require a central server for ease of algorithm design and/or use random sampling to reduce bandwidth cost. In this paper, we present a new distributed algorithm to search for global icebergs without any centralized control or random sampling. A new type of Bloom filter, called linked counting Bloom filter, is designed to check the membership of a set and to store the accumulative frequency of data items. We evaluate the performance of our distributed algorithm with real data sets.

In this paper, we discuss how to prevent users' passwords from being stolen by adversaries. We propose differentiated security mechanisms in which a user has the freedom to choose a virtual password scheme ranging from weak security to strong security. Among the schemes, we have a default method (i.e., traditional password scheme), system recommended function, user-specified function, user-specified program, etc. We further propose a codebook approach to serve as system recommended functions and provide a security analysis. For user-specified functions, we adopt secret little functions, in which security is enhanced by hiding secret functions/algorithms.

In this paper, we propose and study two different bandwidth partition schemes for integrated voice/video/data traffic in the IEEE 802.11e wireless LANs: a Static/fixed bandwidth Partition scheme, and a Dynamic budget Partition scheme. The proposed schemes are compared and evaluated via extensive simulations.

Providing quality of service (QoS) to users in a wireless ad-hoc network is a key concern for service providers. With the availability of multiple rates in IEEE 802.11a/b/g wireless LANs, it is desirable to improve the network capacity and temporal fairness by sending multiple consecutive frames (also referred as frame concatenation mechanism) over high rate links, as proposed in opportunistic auto rate (OAR). However, OAR does not consider the effect of frame sizes and may yield unsatisfactory performance for high priority multimedia flows transmitting over low rate links. Therefore, a more appropriate frame concatenation strategy and a corresponding service differentiation scheme should be devised to provide better performance for high priority voice/video flows than low priority data flows, under various channel rate scenarios. We first analyze the effect of frame size on the performance of OAR. Then, we propose a general concatenation mechanism (GCM), a more accurate frame concatenation mechanism for multi-rate MAC with better fairness. Finally, we propose two mechanisms: adaptive weighted fair frame concatenation mechanism (AWFCM) and adaptive QoS aware frame concatenation mechanism (AQCM), for supporting service differentiation and QoS in multi-rate wireless ad hoc networks. The primary idea is to adjust the number of concatenated frames based on flow weights/priorities, frame sizes, link rates, and network traffic. Simulation results show that the proposed mechanisms achieve desirable performance on supporting multimedia applications in multi-rate wireless ad-hoc networks.

Adversaries can easily launch an attack, by taking advantage of the free wireless networking available to the public at many conferences, airports or cafes. Meanwhile in these environments, it is very difficult to identify the adversaries. In this paper, we present a scheme that is designed to defend against potential attacks at a very early stage, in order to minimize the damage to the victims and the entire network. Instead of taking actions only after the attacks arrive at the host, our scheme makes the access point the one who monitors, identifies and prevents potential attacks. In this active protection way, the system can respond more quickly and can also prevent much of the malicious network traffic.

Because of easy accessible medium in wireless networks, use of these wireless networks in military applications poses several security issues. Likewise, in the business field, despite the emerging static wireless Internet access, the same security issues remains. On example is the passive attack in which attackers attempt to overhear network communications from the outside. Confidentiality can be further divided into two categories, namely, data confidentiality and traffic confidentiality. In this paper, for improving traffic confidentiality, we propose two anonymous routing algorithms, called randomized routing algorithm and probabilistic penalty-based routing algorithm. Both algorithms aim to differentiate routing paths to the same destination enhancing anonymity of the network traffic. We provide simulation results and demonstrate how much these two algorithm disperse routing paths in a network.

Wireless sensor networks are widely used for monitoring applications. The monitored area and the intrusion object are mostly three dimensional. In this paper, we are particularly interested in a sensor network used for monitoring a field to detect intrusion objects such as submarine in some sea area, or goods on shelves in warehouse. In these applications, sensors float in different depth of water or on different height of shelves in three dimensional situations. Since sensor nodes have limited energy supply, sensor networks may be configured to put some sensor nodes in sleep mode to save energy. This is a special case of a randomized scheduling algorithm. In this paper, we study the performance of several randomized scheduling algorithms in terms of intrusion coverage intensity when an intrusion object is considered to occupy a three dimensional space. We study the impact of the size of intrusion object on the sensor networkpsilas configuration.

In this paper, using the so-called parallel space-time Markov chain (PSTMC) framework we analyze the IEEE 802.11 Distributed Coordination Function (DCF) frame service time, jitter, and queuing delay in a single-hop non-saturated wireless network. PSTMC framework provides the possibility of simultaneous modeling of backoff and post-backoff procedures, in addition to the transmission queue status of a non-saturated 802.11 station. To the best of our knowledge, the presented contribution is the first analysis of service time, i.e., access delay and retransmission delay, plus queuing delay at the same time, when the precise modeling of binary exponential backoff (BEB) scheme in medium access control (MAC) layer is the main issue of concern. The model is validated by extensive simulations, showing its remarkable level of accuracy.

To preserve network connectivity is an important issue especially in wireless sensor network, where wireless links are easy to be disturbed and tiny sensors are even easy to fail accidently. Therefore, it is necessary to design a fault-tolerant network. A feasible method is to construct a k-vertex connected topology. In this paper, we consider k-connectivity of wireless network and propose a simple global algorithm (GAFTk) which preserves the network k-connectivity and reduces the maximal transmission power (TP). The average degree expectation of the topology generated by GAFTkis O(k2). Based on GAFTk, we propose a simple local algorithm (LAFTk) which preserves k-vertex connectivity while maintaining bi-directionality of the network. Simulation results show that GAFT/LAFT have better performance than other current fault-tolerant protocols.

Many performance evaluations for IEEE 802.11 distributed coordination function (DCF) have been formerly reported in the literature; most studies are based on saturation analysis, and a few models under a finite load condition adopt an M/G/l queuing system. However, using M/G/l queuing only considers the first moment of frame service time to derive the probability of transmission queue being vacant. In this paper, we model the DCF using parallel space-time Markov chain (PSTMC), in which frame arrivals are tracked by monitoring the transmission queue during transitions between successive states of the space-time Markov chain. The proposed framework provides the possibility of modeling the contention phase, backoff and post-backoff procedures, and the transmission queue status. The proposed framework is validated by the simulation results.

It is very important to monitor the water quality of lakes since any abnormal chemical components/pollutants can possibly cause health problems. Chemical Water Sensors can be used for such long-term monitoring purpose. In this paper, we propose a scalable, low-energy, delay-tolerant Water-quAlity moniToring sEnsor netwoRk (WATER) model, which has essential differences from terrestrial radio sensor networks due to its highly variable, long propagation delay and mobility nature. In the vertical direction, we propose a light-weight time synchronization mechanism that can achieve satisfactory timestamp accuracy. On the other hand, malicious people can use many network attacks (such as Sybil attacks, wormhole attacks, replay attacks, Byzantine attacks, etc.) to mislead water quality monitoring in WATER platforms. To make our time synchronization protocol dependable, we propose a correlation-based security model to detect outlier timestamp data and identify nodes generating insider attacks, which is different from external attacks due to the complete keying material disclosure. Our correlation-based security scheme can also countermeasure many insider attacks (i.e. assuming the enemies already captured the water sensors and got to know the keying materials). Detail experiments have validated the efficiency of our security approaches. The proposed secure time synchronization mechanism (we call it WATERSync) is especially important to navy/military underwater sensor systems.

In this paper, we study MPEG-4 transmissions over the IEEE 802.11e wireless local area networks (WLANs). In (Y. Xiao et al., 2007), we provided a simulation of MPEG-4 using OPNET over WLANs, and simulation results show that a higher throughput does not always mean a better quality of MPEG-4 video. Therefore, in this paper, we propose two schemes to enhance MPEG4 transmissions over WLAN: 1) we propose a prioritized frame cross-layer transmission scheme between the medium access control (MAC) layer and the application layer, and 2) we adopt a measurement admission control scheme for IEEE 802.11e. Simulation results show advantages of the proposed schemes.

In mobile cellular networks, bandwidth is deterministic in terms of number of channels by frequency division, time division, or code division. On the other hand, bandwidth partition schemes in the contention-based medium access control (MAC) in distributed wireless LANs are extremely challenging due to the contention-based nature. In this paper, we propose and study a dynamic bandwidth partition with finer-tune (DP-FT) scheme for integrated voice/video/data traffic in the IEEE 802.11e wireless LANs.

Abstract This paper analyzes and simulates the complexity of searching a particular database called a computer or network auditing log database. In order to observe behaviors of users in a computer or a computer network, system authorities in a particular domain first keep logs of all the actions conducted by the users. In general, we can grasp the users' actions by analyzing their actions in a computer system, or messages in a computer network, especially analyzing headers of packets in a particular network protocol. From this bunch of data (database), we can retrieve particular knowledge according to some requirements for computer and network forensics and accountability. For example, in a computer or network system, if at some point the fact that the content of a secret file is leaking has been already known, to figure out the reasons of the leaking, we can search partial or entire log‐files to find out direct or indirect accesses to the file; since a user who accessed the secret before may send messages containing the secret to other users (the secret is leaking due to indirect accesses) via packets in a computer network, or via pipe/FIFO/Message‐Queue in a computer system, finding the reasons of the leaking is not a trivial task. In this paper, we analyze and simulate the complexity of retrieving knowledge from the computer and network auditing log database for forensics and accountability. Copyright © 2008 John Wiley & Sons, Ltd.

One of the most important challenges in Mobile IPv6 is to provide the service for a mobile node to maintain its connectivity to the Internet when it moves from one domain to another, which is referred to as handover. Here we deal with the fast handover problem, which is to provide rapid handover service for the delay-sensitive and real-time applications. In this paper, we propose an enhanced fast handover scheme for Mobile IPv6. In our scheme, each AR (Access Router) maintains a CoA (Care of Address) table and generates the new CoA for the MN that will move to its domain. At the same time, the binding updates to home agent and correspondent node are to be performed from the time point when the new CoA for MN is known by PAR (Previous AR). Also the localized authentication procedure cooperated with the proposed scheme is provided. For the comparison with the existing fast handover scheme, detailed performance evaluation is performed. From the evaluation results, we can see that the proposed enhanced fast handover scheme can achieve low handover latency and low packet delay.

In this paper, we perform a tele-traffic queueing analysis for OFDM subcarrier allocation in wireless multiservice networks. For this purpose two call admission control algorithms, the batch blocking scheme and the partial blocking scheme, are proposed. Call connection requests are classified into two different types, narrow-band and wide-band. For either class of calls, the traffic process is characterized as batch arrival, as each call may request multiple subcarriers to satisfy its quality-of-service (QoS) requirements. The batch size is a random variable which obeys a probability mass function (pmf) with a realistic maximum value. In addition, the service times for various call classes are different. Consequently, an OFDM-based broadband wireless multiservice network can be formulated as a multiclass multiserver batch arrival queueing system. The methodology and results are further generalized into a multiple-class scenario with service priority provision. Formulae are developed for evaluation of the following performance metrics: the probability that a call will be blocked, the average number of subcarriers used, and bandwidth utilization. Numerical results are presented to demonstrate the interactions between key parameters and performance metrics. The analytical model was validated by the simulation results, showing the fact that it can be used as an efficient tool for design of future-generation broadband wireless access networks.

Abstract Sensor nodes are powered by battery and have severe energy constraints. The typical many‐to‐one traffic pattern causes uneven energy consumption among sensor nodes, that is, sensor nodes near the base station or a cluster head have much heavier traffic burden and run out of power much faster than other nodes. The uneven node energy dissipation dramatically reduces sensor network lifetime. In a previous work, we presented the chessboard clustering scheme to increase network lifetime by balancing node energy consumption. To achieve good performance and scalability, we propose to form a heterogeneous sensor network by deploying a few powerful high‐end sensors in addition to a large number of low‐end sensors. In this paper, we design an efficient routing protocol based on the chessboard clustering scheme, and we compute the minimum node density for satisfying a given lifetime constraint. Simulation experiments show that the chessboard clustering‐based routing protocol balances node energy consumption very well and dramatically increases network lifetime, and it performs much better than two other clustering‐based schemes. Copyright © 2006 John Wiley & Sons, Ltd.

Abstract One of today's most pressing matters in medical care is response time to patients in need. Scope of this research is to suggest a solution that would help reduce response time in emergency situations utilizing technologies of wireless sensor networks. The enhanced power efficiency, minimized production cost, condensed physical layout, and reduced wired connections present a much more proficient and simplified approach to the continuous monitoring of patients' physiological status. The proposed sensor network system is composed of wearable vital sign sensors and a workstation monitor. The wearable platforms are to be distributed to patients of concern. The wearable platforms can provide continuous electrocardiogram (ECG) monitoring by measuring electrical potentials between various points of the body using a galvanometer. They will then relay the ECG signals wirelessly to the workstation monitor. In addition to displaying the data, the workstation will also perform signal wavelet transformation for ECG characteristic extractions. Copyright © 2007 John Wiley & Sons, Ltd.

Abstract Underwater Acoustic Networks (UANs) have important applications in ocean exploration and lake pollution monitoring. UANs are however different from terrestrial sensor networks due to their highly variable, long propagation delay, and mobility. Clock synchronization is an important protocol to achieve timing‐based sensor communications. In this paper, we propose a three dimensional, scalable UAN time synchronization scheme that can achieve both horizontal (i.e., in the same water depth) and vertical (i.e., from bottom up to the surface) clock synchronization to overcome the effects of long acoustic delay. To secure UAN clock synchronization services, we also propose a two‐step security UAN synchronization model: (1) correlation test and (2) statistical reputation and trust model. The proposed model can detect outlier timestamp data and identify nodes generating insider attacks. Copyright © 2007 John Wiley & Sons, Ltd.

Abstract In this paper, based on a distributed particle filter, two tracking algorithms are proposed for tracking mobile targets in cluster‐based underwater sensor networks (USNs). Both tracking algorithms run local particle filter sequentially at each cluster along target trajectories, but they adopt different methods of selecting measurements from sensor nodes to balance the information contribution against the cost. Performance metrics are proposed and discussed in terms of tracking performance, communication cost, energy cost, and tracking response time. Simulations are conducted to quantitatively compare the proposed algorithms as well as another tracking algorithm based on extended Kalman filter (EKF). Our results indicate that one tracking algorithm achieves higher tracking accuracy while the other achieves dramatic reduction of communication cost, energy cost, and tracking response time. Furthermore, performance of two tracking algorithms has been studied in terms of detection threshold and sensor density. Copyright © 2008 John Wiley & Sons, Ltd.

Abstract Radio frequency identification (RFID) systems are very effective for identifying objects. Existing published works focus on designing efficient collision resolution protocols for the tag identification problem in RFID systems with passive RFID tags. However, advances in low‐cost and low‐power sensing technologies will make active RFID tags more popular and affordable in the near future. In multiple object identification systems with active tags, the tags are designed for extremely low‐cost large‐scale applications such that battery replacement is not feasible. This imposes a critical energy‐constraint on the communication protocols used in these systems. In this paper, we analyze energy consumption and identification times for several protocols. The objective is to decrease energy consumption of tags by reducing both the total identification time and the total active time. Copyright © 2007 John Wiley & Sons, Ltd.

Cardiovascular diseases are the single largest cause of morbidity and mortality in the U.S. and Western world. Tele- cardiology through RFID-based wireless sensor networks can provide anytime cardiac patient monitoring in large nursing homes. Wireless medical sensors and PDA devices can provide continuous transmission of patients' cardiac data (such as ECG, blood pressure, SpO2, etc.). However, the radio broadcasting nature has the risk of losing confidentiality (i.e. privacy) of patients' data. This paper discusses our research on a secure RFID/sensor based tele-cardiology system. It is based on the light-weight encryption and key management algorithms. The RFID helps trace the mobility of patients and manage medical facilities in nursing homes.

In this paper, we carry out a comprehensive study to compare invalidation report (IR) to three other cache access algorithms, including poll-each-read (PER), call-back (CB), and lease schemes in future multiple cell wireless Internet. The purpose of this study is to study scalability of IR schemes. To the best of our knowledge, this is the first such study. We focus on the scalability issue of these four fundamental strong-consistent schemes in terms of network transmission costs regarding network size, database size, subscription ratio, and network traffic through extensive computer simulations. Our results show that: 1) the IR schemes do not perform well in multiple-cell wireless Internet with a large update rate, database size, and IR window size, and with a small subscription density; 2) the IR schemes do scale up well with the IR period and the access rate; however, good performance can be obtained when the IR period is large, which implies a large access latency; 3) the PER CB and the lease schemes perform well with a large update rate, small subscription ratio, and large database size.

Security is critical for sensor networks used in military, homeland security and other hostile environments. Previous research on sensor network security mainly considers homogeneous sensor networks, i.e., all sensor nodes are the same. Research has shown that homogeneous ad hoc networks have poor performance and scalability. Furthermore, many security schemes designed for homogeneous sensor networks have high communication overhead, computation overhead, and/or large storage requirement. To achieve better security and performance, we adopt a heterogeneous sensor network (HSN) model. In this paper, we present an efficient key management scheme that takes advantage of the powerful high-end sensors in HSN. The performance evaluation and security analysis show that the key management scheme provides better security with low complexity and significant reduction on storage requirement, compared to existing sensor key management schemes.

Time synchronization is critical for many sensor network operations, such as mobile object tracking and sensor node scheduling. Many existing time synchronization schemes for sensor networks do not considering security issue, and they are vulnerable to several attacks. Furthermore, most existing synchronization schemes are designed for homogeneous sensor networks, where all sensors have the same capability. Research has shown that homogeneous ad hoc networks have poor fundamental limits and performance. To improve performance and security of sensor networks, we adopt a Heterogeneous Sensor Network (HSN) model. In this paper, we present a secure and efficient time synchronization scheme for HSN by utilizing powerful high-end sensors. We implement the synchronization scheme in real sensors and our experiments show that the scheme achieves high accuracy. The security analysis demonstrates that our scheme is resilient to various attacks.

This paper investigates fundamental performance limits of medium access control (MAC) protocols for multi-hop sensor networks. A unique aspect of this study is the modeling of a fair-access criterion requiring that sensors have an equal rate of frame delivery to the base station. Tight upper bounds on network utilization and tight lower bounds on minimum time between samples are derived for fixed linear and grid topologies. The significance of these bounds is two-fold: First, they are universal, i.e., they hold for any MAC protocol. Second, they are provably tight, i.e., they can be achieved by a version of time division multiple access (TDMA) protocol that is self-clocking, and therefore does not require system-wide clock synchronization. The paper also examines the implication of the end-to-end performance bounds regarding the traffic rate and sensing time interval of individual sensors.

Scheduling strategies for on-demand data in broadcast systems typically consider how to minimize the wait time of the requests. When users' requests for data in a broadcast system have real-time constraints, scheduling strategies for such requests typically only consider how to minimize the number of deadlines missed. There are many applications with both real-time and non-real-time requests that would benefit from a broadcast scheduling strategy that considers both the timing constraints and the wait times of requests. We refer to such a broadcast environment as a mixed-type request broadcast environment. In this paper, we present an on-demand broadcast cost model for mixed-type broadcast environments that considers both the response time and number of deadlines missed. We propose a scheduling strategy for mixed-type broadcast systems, called the maximum paid cost first (MPCF) that is based on this cost model. The simulation results show that our MPCF strategy always achieves the best result for varying request arrival rates, ratio of non-real-time requests and real-time requests, and a weighted missed deadline value, when compared to existing broadcast strategies.

In wireless sensor networks, time synchronization is highly desired because data collected from agglomerated sensors become truly meaningful when they are stamped with the accurate time. Most of current studies on time synchronization don't consider the effects of channel errors on time synchronization. In this paper, we evaluate effects of channel error on time synchronization via simulations in different configurations. We study the impact degree of channel error on synchronization time and clock drift. Our results show that channel error is an important factor in time synchronization in wireless sensor networks. Our results also show time offset delta exponentially increases as the channel error rate increases.

Secure in-network aggregation in wireless sensor networks is a necessary and challenging task. In this paper, based on an extended Kalman filter which can facilitate us to set up a normal range of the neighbor's future transmitted aggregated values, we further apply an algorithm of combining cumulative summation and generalized likelihood ratio, which can utilize the cumulative sum of the deviations between measured values and estimated values, and derive a normal range which is more sensitive to attacks. We conduct experiments and simulations to evaluate our proposed local detection mechanisms under different aggregation functions.

In this paper, we propose Least Total-Route- Temperature (LTRT), a thermal aware routing algorithm, to reduce temperature caused by biomedical sensors implanted in human bodies. In the proposed scheme, nodes' temperatures are converted into graph weights and minimum temperature routes are obtained. Simulations are conducted to show the advantages of the proposed scheme when comparing with three other related schemes.

In this paper, we provide a performance evaluation for blanket paging scheme, sequential probability paging scheme, and pipeline probability paging scheme in wireless networks. Both analytical models and extensive simulations are adopted to study these schemes.

The many-to-one traffic pattern dominates in sensor networks, where a large number of sensor nodes send data to one sink. A sensor node may only communicate with a small portion of its neighbors. Most existing key management schemes for sensor networks are designed to establish shared keys for all pairs of neighbor sensors, no matter whether they communicate with each other or not, and this causes large overhead. To achieve better security and performance, we adopt a heterogeneous sensor network (HSN) model. In this paper, we propose a novel routing-driven key management scheme, which only establishes shared keys for neighbor sensors that may communicate with each other. Work has demonstrated the feasibility of implementing elliptic curve cryptography on small sensor nodes. We utilize elliptic curve cryptography to design an efficient key management scheme for HSN. The performance evaluation and security analysis show that our key management scheme can provide better security with significant saving on sensor storage space and energy consumption than some existing key management schemes.

Secure in-network aggregation in wireless sensor networks (WSNs) is a necessary and challenging task. In this paper, we address this research problem from an intrusion detection perspective. We propose that system monitoring modules, which provide one of the most important functionalities for WSNs, should be integrated with intrusion detection modules. Under this architecture, we first propose an extended Kalman filter (EKF) based mechanism to detect false injected data. Specifically, by monitoring behaviors of nodes' neighbors and using EKF to predict their future state (the real in-network aggregated value), we aim at setting up the normal range of neighbors' future transmitted aggregated values. We illustrate how we use EKF to create effective local detection mechanisms. Using different aggregation functions (average, sum, max, and min), we analyze how to obtain the threshold in theory. We then illustrate how our proposed local detection approach can work together with the system monitoring module to differentiate between malicious events and emergency events. We conduct simulations to evaluate performance of local detection mechanisms, including false positive rate and detection rate, under different aggregation functions.

In our previous work [11], we derived detection delay and detection probability for a randomized scheduling algorithm in wireless sensor networks. In this paper, we study asymptotic coverage, prove many mathematical lemmas, and study properties including asymptotic properties of network coverage intensity, detection probability, and detection delay in wireless sensor networks.

Radio frequency identification (RFID) systems are very effective for identifying objects. In multiple object identification systems with active tags, the tags are designed for extremely low-cost large-scale applications such that battery replacement is not feasible. This imposes a critical energy-constraint on the communication protocols used in these systems. In this paper, we analyze energy consumption and identification times for several protocols. The objective is to decrease energy consumption of tags by reducing both total identification time and total active time.

A lot of realistic applications in sensor networks adopt hierarchical architecture in which sensor nodes are grouped into clusters, with each cluster relying on a gateway node for local data aggregation and long-distance radio transmission. Compared to normal sensor nodes, the gateway nodes, also called application nodes (ANs), are equipped with relatively powerful transceivers and have more energy. Nevertheless, since an AN is the main gateway for sensor nodes within its cluster, its energy may be depleted more quickly than normal sensor nodes. As such, it is important to find methods to save energy for ANs. This paper presents and evaluates an energy efficient coarse-grained scheduling scheme for ANs.

A dynamic periodic location area update (DPLAU) scheme was proposed for 3GPP technical specifications for the circuit-switched domain of universal mobile telecommunications system. In this paper, we propose an analytical model for the optimal DPLAU (ODPLAU) scheme to minimize the cost of location management under the presence of abnormal detachments. Simulations are conducted and validate the analytics results.

In wireless sensor networks, in order to minimize energy consumption and extend network lifetime, some sensors are put in the sleep mode while the other sensor nodes are in the active mode for the sensing and communication tasks. In a randomized scheduling algorithm, a set of sensors work alternatively. In this paper, we provide an analytical model for the randomized scheduling algorithm, and derive detection delay and detection probability. Simulations are conducted to validate analytical results.

In this paper, we provide an evaluation for our proposed real-time virtual videophone using talking heads over low-bandwidth wireless networks, in which a person's face is substituted with a talking head to save bandwidth. Results show large enough gains in communication bandwidth to make the architecture feasible.

In this paper, we provide a simulation of MPEG-4 using OPNET over the IEEE 802.11 wireless local area networks (WLANs) in terms of throughput and impacts of multiple MPEG-4 streams and compression rates on the throughput. Simulation results are explained in detail, especially for MPEG-4 simulations. Our results show that a higher throughput does not always mean a better quality of MPEG-4 video.

Telemedicine has been in use for many years and it is the use of telecommunications technologies to consult with remote physician. In this paper, we shed light on telemedicine in terms of the common usage and the future potentials of the technology with some examples.

From the viewpoint of control theory, TCP congestion control system can be regarded as a feedback regulating system. In this paper, a novel active queue management (AQM) scheme, called WTCP, is proposed for TCP congestion control in high speed wired/wireless Internet. The design principles of WTCP are presented in details. Simulation results demonstrate that the WTCP AQM outperforms FAST TCP in items of window size, queue length, and self-clocking against traffic load fluctuation such as HDP and HTTP disturbance.

Cache can be used for mobile devices to reduce the usage of limited bandwidth in wireless networks. Ideally, frequently accessed and infrequently updated data items should be cached and infrequently accessed and frequently updated data items should be evicted or not cached at all. Most of the existing cache replacement policies adopt only access information so that frequently updated data items are also cached. As a remedy, we propose a cache replacement policy, called On-Bound Selection (OBS), that uses both data access and update information. The proposed OBS is inspired by an analytical analysis for a server-based Poll-Each-Read (SB-PER) and a revised Call-Back (R-CB). The OBS provides an upper bound for effective hit ratio and a lower bound for communication cost. The proposed scheme is evaluated and compared with a least frequently used (LFU) replacement policy through extensive simulations. Simulation results show that the OBS outperforms LFU in terms of both effective hit ratio and communication cost.

Bandwidth allocation schemes have been well studied for mobile cellular networks. However, there is no study about this aspect reported for IEEE 802.11 contention-based distributed wireless LANs. In cellular networks, bandwidth is deterministic in terms of the number of channels by frequency division, time division, or code division. On the contrary, bandwidth allocation in contention-based distributed wireless LANs is extremely challenging due to its contention-based nature, packet-based network, and the most important aspect: only one channel is available, competed for by an unknown number of stations. As a consequence, guaranteeing bandwidth and allocating bandwidth are both challenging issues. In this paper, we address these difficult issues. We propose and study nine bandwidth allocation schemes, called sharing schemes, with guaranteed Quality of Service (QoS) for integrated voice/video/data traffic in IEEE 802.11e contention-based distributed wireless LANs. A guard period is proposed to prevent bandwidth allocation from overprovisioning and is for best-effort data traffic. Our study and analysis show that the guard period is a key concept for QoS guarantees in a contention-based channel. The proposed schemes are compared and evaluated via extensive simulations.

This paper proposes an approach to analyze pulse waveform dependent bit error rate (BER) performance of a DS-CDMA ultra wideband (UWB) radio, which operates in a frequency selective fading channel. The analysis takes into account almost all real operational conditions, such as asynchronous transmissions, RAKE receiver, multiple access interference (MAI), multipath interference (MI), log-normal shadowing, and noise. The main objective of the paper is to reveal the relationship between time domain characteristics of pulse waveforms and BER of a UWB radio. It is shown through analysis (also validated by simulation) that the normalized mean squared auto-correlation function (ACF) of the pulse waveforms can be used as an effective merit figure to judge the suitability for their applications in a DS-CDMA UWB radio. In fact, the normalized mean squared auto-correlation function (ACF) governs the average inter-chip interference caused by imperfect auto-correlation function of the pulse waveforms. The paper concludes that, as long as the power spectral density (PSD) functions of the pulse waveforms fit the FCC spectral mask, the pulse waveforms' normalized mean squared ACF should be minimized to ensure an acceptable BER.

Research on sensor network routing focused on efficiency and effectiveness of data dissemination. Few of them considered security issues during the design time of a routing protocol. Furthermore, previous research on sensor networks mainly considered homogeneous sensor networks where all sensor nodes have the same capabilities. It has been shown that homogeneous ad hoc networks have poor fundamental performance limits and scalability. To achieve better performance, we adopt a heterogeneous sensor network (HSN) model. In this paper, we present a secure and efficient routing protocol for HSNs - two tier secure routing (TTSR). TTSR takes advantage of powerful high-end sensors in an HSN. Our security analysis demonstrates that TTSR can defend typical attacks on sensor routing. Our performance evaluation shows that TTSR has higher delivery ratio, lower end-to-end delay and energy consumption than a popular sensor network routing protocol.

Mobility databases such as home location register and visitor location register are adopted to support mobility management in personal communications services networks. If a visitor location register fails or crashes, the subscribers' services will be seriously degraded due to the loss or corruption of location information. In this paper, we optimize utilization of demand re-registration messages for an adaptivep-persistent backoff database failure restoration scheme. An analytical model is developed and validated with simulations to obtain the optimal utilization using appropriate parameters so that the failed visitor location register is restored with the fastest speed. Some interesting aspects on the performance are studied and their deep insights are observed, such as effects of message sizes on choices of system parameters, effects of the inaccurate estimated number of stations, etc. One observation is that optimizations of utilization and successful transmission probability are two different goals, and a value to achieve the optimal successful transmission probability does not necessarily ensure optimal utilization. Furthermore, we also propose a scheme how to handle the problem with inaccurate (estimated) number of stations.

Paging schemes for wireless systems have been well studied in the literature. However, most schemes are considered on per user basis. In these schemes, when an incoming call arrives at a mobile terminal (MT), a paging request (PR) is put in a queue. PRs are served in an FIFO manner. When a PR is served, a search process is carried out to find the corresponding MT in a location area (LA). Most schemes study how to achieve a better performance in terms of cost with/without delay constraints per PR, and totally ignore other PRs in the queue until the MT is found or all the cells in the LA have been paged. In this paper, we propose a non-blocking pipeline probability paging scheme, which assumes known knowledge on location probabilities of individual MTs, under a paging delay constraint, where the location probability of an MT in a cell is the probability that the MT is in the cell. The proposed scheme is independent of the number of PRs in the queue and the arrival rate of PRs. Our study shows that the proposed scheme outperforms both the sequential probability paging scheme with known knowledge on location probabilities of individual MTs and the blanket paging scheme in terms of discovery rate and the total delay. Finally, we study several optimization problems with quality of service constraint for the pipeline probability paging scheme.

Abstract A radio frequency identification (RFID) system is a special kind of sensor network to identify an object or a person using radio frequency transmission. A typical RFID system includes transponders (tags) and interrogators (readers): tags are attached to objects/persons, and readers communicate with the tags in their transmission ranges via radio signals. RFID systems have been gaining more and more popularity in areas such as supply chain management, automated identification systems, and any place requiring identifications of products or people. RFID technology is better than barcode in many ways, and may totally replace barcode in the future if certain technologies can be achieved such as low cost and protection of personal privacy. This paper provides a technology survey of RFID systems and various RFID applications. We also discuss five critical research issues: cost control, energy efficiency, privacy issue, multiple readers' interference, and security issue. Copyright © 2006 John Wiley & Sons, Ltd.

We propose two contention-based medium access control (MAC) mechanisms to provide quality of service (QoS) for variable bit rate (VBR) voice over IP (VoIP) in IEEE 802.11e contention-based channel access (EDCA) wireless LANs (WLANs): Access time-based admission control (ATAC) and access point dynamic access (AP-DA). Simulation results indicate that the proposed mechanisms offer a satisfactory solution for QoS of VBR VoIP; the ATAC algorithm outperforms the EDCA and significantly improves QOS of VBR VoIP sessions in terms of average delay and delay distribution; and the AP-DA algorithm effectively balances downlink and uplink VoIP sessions.

We propose an enhance model for performance analysis of an energy saving mechanism in the IEEE 802.16e broadband wireless access (BWA) network. A mobile subscriber station goes to sleep-mode after negations with the base station and temporarily wake-up periodically for a short interval to check whether there is downlink traffic to it to decide whether it goes to wake-mode or continues to be in the sleep-mode. The sleep interval is increased exponentially upon no arrival traffic. We analytically model the sleep-mode scheme and validate the model with simulations. Our enhanced model considers both incoming frames and outgoing frames.

Ultra-wideband (UWB) transmission is an emerging wireless technology. The IEEE 802.15.3 medium access control (MAC) is proposed for short-range UWB system. In this paper, we first formulate a throughput optimization problem for a given contention-free channel time allocation under error channel condition and with the three ACK mechanisms: No-ACK, Immediate-ACK, and Delayed-ACK. Furthermore, we apply the three ACK mechanisms in the contention access period (CAP), to optimize the channel throughput. Simulation results demonstrate the effectiveness of our investigation.

Most of existing cache replacement policies are access-based replacement policies where update process is ignored. However, update information is extremely important. In this paper, we provide a deep analysis on cache access algorithms, and propose a step-wise optimal update-based replacement policy, called update-based step-wise optimal (USO) scheme, to optimize transmission cost and effective hit ratio at each replacement. Unlike traditional studies of replacement policies which are mostly based on only intuitions, our proposed scheme is based on quantitative analysis, and optimality is proved by an analytical model. The extensive simulations have shown that the advantage of the proposed replacement policy.

Sensor networks are envisioned to have important applications in military and homeland security. For sensor networks deployed in such hostile environments, security is critical to ensure privacy, integrity, authenticity, and availability of communications. Routing is a fundamental operation in sensor networks. Past researches on sensor network routing focused on efficiency and effectiveness of data dissemination. Few of them considered security during the design phase of the routing protocols. Furthermore, previous researches on sensor networks mainly considered homogeneous sensor networks, i.e., all sensor nodes are the same. Research has shown that homogeneous ad hoc networks have poor performance. We adopt a heterogeneous sensor network (HSN) model for better performance and security. In this paper, we present an efficient secure routing protocol for HSN which takes advantage of the powerful high-end sensors. The security analysis demonstrates that the secure routing protocol can defend typical routing attacks. The simulation shows that the secure routing protocol has better performance than a popular routing protocol - directed diffusion.

Security is critical for sensor networks deployed in hostile environments. Previous research on sensor network security mainly considers homogeneous sensor networks, i.e., all sensor nodes have the same capabilities. Many security schemes designed for homogeneous sensor networks suffer from high communication/computation overhead, and/or large storage requirement. We adopt a heterogeneous sensor network (HSN) model to overcome these problems. In this paper, we present an efficient asymmetric pre-distribution (AP) key management scheme that takes advantage of the powerful high-end sensors (H-sensors) in an HSN. The AP scheme utilizes the large storage of H-sensors and pre-load each H-sensor with a relatively large number of keys. The AP scheme dramatically reduces the total storage space for key pre-distribution. The performance evaluation and security analysis show that the AP scheme provides better security than existing key management schemes, while achieving significant reduction on sensor storage.

In this paper, we study various security aspects in the IEEE 802.15.3 wireless personal area networks (WPANs) with security analysis. We present these security features in a more natural and concise manner than the overly complicated standard.

Significant security concerns have come to the attention of both service providers and end users in cellular mobile systems. In these systems, misuse-based intrusion detection approaches are not effective since a potential wide variety of mobile users' behaviors are not taken into consideration. In this paper, by exploiting the location history traversed by mobile users, we propose an anomaly detection scheme to identify a group of especially harmful insider attackers - masqueraders. A realistic network model integrating geographic road-level granularities is proposed to effectively utilize users' location information. Based on this model, an Instance-Based Learning (IBL) technique is presented to construct mobile users' movement patterns. Simulation results demonstrate the effectiveness of the proposed scheme in terms of false positive rate and detection rate.

Radio frequency identification (RFID) systems have provided promising solutions to effective identification of a large number of tagged objects. However, RFID systems suffer from unauthorized tag reading and potential eavesdropping, which becomes a challenging issue because of the shared radio medium and limited size and cost considerations in RFID. In this paper, based on a linear congruential generator (LCG), we propose a lightweight block cipher that can meet the security and performance requirement of RFID systems. The trade-off between the security and overhead is discussed. Based on the proposed block cipher, we further propose a secure protocol for RFID that can provide data confidentiality and mutual authentication between the reader and the tag. We also provide performance analysis of our proposed block cipher.

In this paper, we present a detection technique based on Bayes decision rule to identify a group of especially harmful insider attackers - masqueraders. In this technique, we exploit the calling patterns demonstrated by mobile users in mobile cellular networks. Specifically, we formulate the intrusion detection problem as a multi-feature two-class pattern classification problem. Call duration time, call inactivity period and call destination are extracted to form a feature vector to reflect users' calling activities. A nonparametric technique, Parzen window approach with a Gaussian kernel, is used to estimate the smooth class-conditional probability density function. A Bayes decision rule is applied in order to achieve the minimum error rate. Using users' calling activities to demonstrate different behaviors, we carried out simulations to evaluate the proposed scheme in terms of false positive rate and detection rate.

The default acknowledgment (ACK) strategy of TCP easily overruns the constrained ACK channel capacity of the asymmetric network links. There is no effective ACK mechanism to address the asymmetric channel problem for space-Internet. A configurable ACK delay (CAD) mechanism has been developed to delay the ACKs for a configurable period of time to improve the TCP throughput performance over asymmetric space-Internet links. This paper introduces the CAD mechanism and presents a performance evaluation of it in an experimental manner. The experimental results show that the CAD mechanism has significant performance advantages in asymmetric space links with a channel ratio higher than 50/1. The higher the asymmetric channel ratio is, the more advantageous the CAD is over the default ACK strategy.

In this paper, we compare a pipeline probability paging scheme, a blanket paging scheme, and a sequential probability paging scheme in wireless networks. An optimization problem under quality of service constraint is studied for the pipeline probability paging scheme.

In this paper, we study a randomized scheduling algorithm, and analyze the problem of maximizing network lifetime under quality of service constraints such as bounded values of detection delay, detection probability, and network coverage intensity in wireless sensor networks. We show that the optimal solutions exist and provide the conditions of the existence of the optimal solutions.

In this paper, we propose and study a hierarchical pipeline paging (HPP) for multi-tier hierarchical cellular networks, in which each mobile terminal (MT) can be paged in any tier of a network. Furthermore, paging requests are queued in N different waiting queues, where N stands for the number of tiers, and multiple paging requests in each waiting queue are served in a pipeline manner. We study the HPP scheme analytically in terms of discovery rate, total delay, paging delay, cost, and load balance, validated with simulations.

Advanced encryption standard has been proposed and implemented for several years as a new cipher to replace data encryption standard. There are many researches and applications using this new cipher. However, there is a need to provide its performance analysis in scenarios of network applications. In this paper, we provide an overhead analysis of advanced encryption standard and its performance in wireless networks.

A three-tier wireless local loop (WLL) extends the single-tier or two-tier WLL, and it is capable of accommodating more subscribers. This paper presents and analyzes channel allocation algorithms for a three-tier WLL. These algorithms include no repacking (NR), always repacking (AR), Repacking on Demand - Random (RoDR), Repacking on Demand - Least Load (RoDL), and Repacking on Demand - Subscriber Terminal (RoDST), depending on how repacking candidates are handled. Blocking probability and handoff probability are compared among all these channel assignment algorithms by simulations. It is shown that given the same set of simulation parameters, NR has the highest blocking probability, AR has the lowest blocking probability, and RoD has a blocking probability that falls in between. Compared with NR, both AR and RoD reduce the block probability at cost of a high handoff probability. Among RoDR, RoDL, and RoDST, RoDST has the lowest blocking probability but the highest handoff probability.

Cache can be used for mobile devices to reduce the usage of scarce wireless channels in wireless networks. Ideally, only frequently accessed and infrequently updated data items should be cached and infrequently accessed and frequently updated data items should be evicted or not cached at all. Existing cache replacement policies which use only access information may cause frequently updated data items to be cached. As a remedy, we propose a cache replacement policy, called asymptotical keep-best (AKB), that uses both data access and update information. The proposed AKB is evaluated and compared with the least recently used replacement policy (LFU) through extensive simulations. Simulation results show that the proposed replacement policy outperforms LFU in terms of both effective hit ratio and communication cost.

In this paper, based on a Linear Congruential Generator (LCG), we propose a new block cipher that is suitable for constructing a lightweight secure protocol for resource-constrained wireless sensor networks. Based on the Plumstead's inference algorithm, we are motivated to embed the generated pseudo-random numbers with sensor data messages in order to provide security. Specifically, the security of our proposed cipher is achieved by adding random noise and random permutations to the original data messages. The analysis of our cipher indicates that it can satisfy the security requirements of wireless sensor networks. We demonstrate that secure protocols based on our proposed cipher satisfy the baseline security requirements: data confidentiality, authenticity, and integrity with low overhead. Performance analysis demonstrates that our proposed block cipher is more lightweight than RC5 in terms of the number of basic operations.

In this paper, we compare the normal location area update (NLAU) scheme, the periodic location area update (PLAU) scheme, and the PNLAU (NLAU+PLAU) scheme in 3GPP specifications for Universal Mobile Telecommunications System (UMTS) in terms of signaling and initial trunk setup cost. We analytically model cost functions of these schemes per checkpoint event. Optimality issue of the PNLAU has been studied to minimize the total cost of signaling and failure call setup, and optimal values are derived.

In this paper, we propose a pipeline probability paging to reduce delay and improve performance for wireless systems assuming prior knowledge on location probabilities of individual mobile terminals, under a paging delay constraint. Our study shows that the proposed scheme outperforms both the sequential probability paging scheme with prior knowledge on location probabilities of individual mobile terminals and the blanket paging scheme in terms of discovery rate and the total delay.

In-network data aggregation in an essential operation to reduce energy consumption in large-scale wireless sensor networks. With data aggregation, however, raw data items are invisible to the base station and thus the authenticity of the aggregated data is hard to guarantee. A compromised sensor node may forge an aggregation value and mislead the base station into trusting a false reading. Due to the stringent constraints of energy supply and computing capability on sensor nodes, it is challenging to detect a compromised sensor node and keep it from cheating. This paper proposes a secure aggregation tree (SAT) to detect and prevent cheating. Our method is essentially different from other existing solutions in that it does not require any cryptographic operations when all sensor nodes work honestly. The detection of cheating is based on the topological constraints in the aggregation tree.

We consider the medium access control (MAC) layer for very high-speed wireless LANs, which is designed to support rich multimedia applications such as high-definition television. In such networks, the physical (PHY) layer data rate is proposed to exceed 216 Mbps. The legacy MAC layer, however, greatly restricts the performance improvement due to its overhead. It has been shown that MAC utilizes less than 20% of the transportation ability provided by the PHY layer. To mitigate this inefficiency, we propose an aggregation with fragment retransmission (AFR) scheme, which supports transmissions of very large frames and partial retransmissions in the case of errors. Aggregation allows for increased performance despite per-transmission overhead while partial retransmission alleviates the risk of losing the entire frame. Extensive simulations show that AFR fundamentally outperforms the legacy MAC protocol. It is particularly effective for applications with high data rates and large packet sizes such as HDTV and high-rate UDP traffic. For applications with very low data rates and small packet sizes such as voice over IP, AFR performs slightly better.

This paper introduces an approach to generate generalized pairwise complementary (GPC) codes, which offer a uniform interference free windows (IFWs) across the entire code set. The GPC codes work in pairs and can fit extremely power efficient quadrature carrier modems. The characteristic features of the GPC codes include: the set size is 2K, the processing gain is 4NK, and the IFW's width is 8N identically for all codes in a set, where K is the times to perform Walsh-Hadamard expansions and N is element code length of seed complementary codes. Therefore, by using different N, the IFW width of a GPC code set can be adjusted with its set size unchanged. Each GPC code set consists of two code groups, with each having K codes, and they have sparsely and uniformly distributed autocorrelation side lobes and cross-correlation levels outside the IFWs.

Ultra-wideband (UWB) transmission is an emerging wireless technology for future short-range indoor and outdoor multimedia applications. To coordinate the access to the wireless medium among the competing devices, the IEEE 802.15.3 medium access control (MAC) is proposed for short-range high-speed wireless personal area networks (WPANs) in the IEEE 802.15.3a task group. In the MAC, three acknowledgment (ACK) mechanisms are adopted during channel time allocation for error control over the error-prone wireless channel: No-ACK, Immediate-ACK (Imm-ACK), and Delayed-ACK (Dly-ACK). Frames received with errors can be retransmitted in the Imm-ACK and Dly-ACK mechanisms. However, how to optimally use these ACK mechanisms during channel time allocation is still an open issue. In this paper, we investigate how to configure the ACK mechanism parameters in order to achieve optimal throughput performance. We first formulate the throughput optimization problem for a contention-free channel time allocation under error channel condition. We then apply the three ACK mechanisms in the contention access period, to optimize the channel throughput. Simulation results demonstrate the effectiveness of our investigation.

Cache has been applied for wireless data access with different replacement policies in wireless networks. Most of the current cache replacement schemes are access-based replacement policies since they are based on object access frequency/recency information. Access-based replacement policies either ignore or do not focus on update information. However, update information is extremely important since it can make access information almost useless. In this paper, we consider two fundamental and strongly consistent access algorithms: Poll-Per-Read (PER) and Call-Back (CB). We propose a server-based PER (SB-PER) cache access mechanism in which the server makes replacement decisions and a client-based CB cache access mechanism in which clients make replacement decisions. Both mechanisms have been designed to be suitable for using both update frequency and access frequency. We further propose two update-based replacement policies, least access-to-update ratio (LA2U) and least access-to-update difference (LAUD). We provide a thorough performance analysis via extensive simulations for evaluating these algorithms in terms of access rate, update rate, cache size, database size, object size, etc. Our study shows that although effective hit ratio is a better metric than cache hit ratio, it is a worse metric than transmission cost, and a higher effective hit ratio does not always mean a lower cost. In addition, the proposed SB-PER mechanism is better than the original PER algorithm in terms of effective hit ratio and cost, and the update-based policies outperform access-based policies in most cases.

Strongly consistent callback cache mechanisms have been studied for data access in wireless networks. In cache access mechanisms, update information is extremely important since an updated data object in a remote server makes the corresponding data objects invalidated in mobile terminals (MTs), and the data object cache hit information in those MTs becomes almost useless. In this paper, we propose an adaptive access mechanism, called optimal callback with two-level adaptation. In the first-level adaptation, cache size in an MT is adaptively adjusted based on update-to-access-ratio (UAR), defined as the average number of updates per data object access. The range of the cache size is [O, M], where M is the maximum physical cache size of the MT. Two extreme cases are given as follows: 1) when the UAR is very large so that objects in the cache are always obsolete, the cache should not be used and, therefore, the cache size should be set to zero; 2) when the UAR is zero so that every object in the cache is valid, the cache size should be set to M. Under other situations, the cache size is dynamically changed between O and M. Define U-threshold of the UAR for any object, a particular important threshold, as a UAR value, beyond which the object should be not cached at all. The idea of the second-level adaptation is that if an object size is small, sending back the object may be a better choice than sending back an invalidation message when the object is updated. Therefore, when an object is updated at the server, it is sent directly to MTs if the object size is smaller than a threshold, called push threshold (T); otherwise, an invalidation message is sent to the MTs. We analytically model cost function for the proposed adaptive scheme as the total traffic involved between the server and an MT per data object access, and the optimal cache size and the optimal T value are obtained simultaneously to minimize the cost function. Furthermore, U-threshold is derived analytically. Both simulations and analytical results are used to study and compare the performance of the proposed scheme with several others under many different scenarios.

In this paper, we present a simple pipeline paging (PP) scheme, in which multiple paging requests (PRs) can be served in a pipeline manner in different paging areas. We analytically model the blanket paging (BP) scheme, the sequential paging (SP) scheme, and the PIP scheme so that discovery rate, total delay, paging delay, and cost are derived analytically as functions of traffic load. Extensive simulations are carried out to verity our analytical results. Our study shows that the PIP scheme outperforms both the BIP and SIP schemes in terms of discover rate while maintaining the same cost as the SIP scheme. The PIP scheme outperforms the SP scheme in terms of total delay and has a lower total delay than the BIP scheme when traffic load is high. We also show that, when the paging delay constraint D is large enough, the PIP scheme achieves almost 200 percent of discovery rate and 50 percent of cost of the BP scheme, whereas discovery rate of the SIP scheme is far less than that of the BP scheme. Furthermore, we solve the following two-optimization problems for the PIP scheme: 1) the minimization of discovery rate with a bound on total delay and 2) the minimization of cost with a bound on total delay. In case the cost factor is not considered but total delay is important, we propose an adaptive scheme: When the traffic is lower than a threshold, the BIP scheme is adopted; otherwise, the PIP scheme is used. In this case, the threshold value is explicitly derived.

Sensor scheduling plays a critical role for energy efficiency of wireless sensor networks. Traditional methods for sensor scheduling use either sensing coverage or network connectivity, but rarely both. In this paper, we deal with a challenging task: without accurate location information, how do we schedule sensor nodes to save energy and meet both constraints of sensing coverage and network connectivity? Our approach utilizes an integrated method that provides statistical sensing coverage and guaranteed network connectivity. We use random scheduling for sensing coverage and then turn on extra sensor nodes, if necessary, for network connectivity. Our method is totally distributed, is able to dynamically adjust sensing coverage with guaranteed network connectivity, and is resilient to time asynchrony. We present analytical results to disclose the relationship among node density, scheduling parameters, coverage quality, detection probability, and detection delay. Analytical and simulation results demonstrate the effectiveness of our joint scheduling method

In this paper, we propose a novel contention-based protocol called backoff counter reservation and classifying stations for the IEEE 802.11 distributed coordination function (DCF). In the proposed scheme, each station has three states: idle, reserved, and contentious. A station is in the idle state if it has no frame ready to transmit. A station is in the reserved state if it has a frame ready to transmit and this frame's backoff counter has been successfully announced through the previous successfully transmitted frame so that other stations know this information. A station is in the contentious state if it has a frame ready to transmit, but this frame's backoff counter has not been successfully announced to other stations. All the stations in the idle state, the reserved state, and the contentious state form an idle group, a reserved group, and a contentious group, respectively. Two backoff schemes are proposed in the BCR-CS protocol based on the number of stations in the contentious group including the optimal pseudo-p-persistent scheme. The proposed schemes are compared with the DCF and the enhanced collision avoidance (ECA) scheme in the literature. Extensive simulations and some analytical analysts are carried out. Our results show that all proposed schemes outperform both the DCF and the ECA, and the BCR-CS with optimal pseudo-p-persistent scheme is the best scheme among the four schemes

A normal location area update (NLAU) and a periodic location area update (PLAU) schemes are adopted in 3GPP specifications for Universal Mobile Telecommunications System to detect presence of mobile stations. In this paper, we compare the NLAU scheme, the PNLAU (NLAU+PLAU) scheme, and a dynamic PNLAU scheme in terms of signaling and initial trunk setup cost. We analytically model cost functions of these schemes per checkpoint event. Optimality issues of the PNLAU have been studied, and optimal values are derived. The first optimality issue is to minimize the total cost of signaling and failure call setup. The second optimality issue is to minimize the signaling cost with an upper bound on failure call setup probability. Simulations are carried out to validate against analytical results.

Paging is a search process conducted in a paging area to locate a mobile terminal (MT) in terms of a cell. In this paper, we propose two paging schemes, called separated macro-micro paging (SMMP) and combined macro-micro paging (CMMP) for macrocell-microcell hierarchical cellular networks. In this kind of networks, MTs can receive signals from both macrocells and overlaid microcells. In the SMMP scheme, an MT can be paged from either the macrocell-tier or its overlaid microcell-tier. In the CMMP scheme, an MT is paged in a mix of the macrocell-tier and its overlaid microcell-tier. Optimal paging load balance between the macrocell-tier and the microcell-tier has been studied. The SMMP scheme when location probabilities are available is also studied. Analytical models are developed to evaluate the proposed schemes.

Abstract Past researches on sensor network routing have been focused on efficiency and effectiveness of data dissemination. Few of them consider security issues during the design time of routing protocols. Security is very important for many sensor network applications. Studies and experiences have shown that considering security during design time is the best way to provide security for sensor network routing. In this paper, we propose an efficient key management scheme and a novel secure routing protocol—Secure cell relay (SCR) for sensor networks. We also present an effective key setup scheme for sensor nodes deployed in the later stage. We analyze the security of SCR under various attacks and show that SCR is very effective in defending against several sophisticated attacks, including selective forwarding, sinkhole, wormhole, Sybil, hello flooding, and clone attacks. SCR is an energy‐efficient routing protocol with acceptable security overhead. Our simulations demonstrate that with all the security primitives, SCR still has lower energy consumption and higher delivery ratio than a popular routing protocol—directed diffusion. Copyright © 2006 John Wiley & Sons, Ltd.

Abstract A Block Transmission and Acknowledgement (BTA) scheme, also called Block ACK, has been proposed in the IEEE 802.11e wireless local area networks (WLAN) specification to improve efficiency of the medium access control layer. The idea of the BTA scheme is to transmit multiple data frames followed by only one acknowledgement frame in a transmission block. In this paper, we present a theoretical model to evaluate the saturation throughput for the BTA scheme under error channel conditions in the ad hoc mode, validated with simulations. We show some advantages of BTA over the legacy MAC, and analyze how to select a proper number of frames for each transmission block. Results show that BTA is particularly effective in very high‐speed wireless networks, and it is important that the number of frames in each block is negotiated before transmissions to provide better efficiency. Copyright © 2006 John Wiley & Sons, Ltd.

Abstract Current IEEE 802.11 wireless local area network (WLAN) standard products can provide up to 54 Mbps raw transmission rate, while non‐standard WLAN products with 108 Mbps have already appeared in the market, and the next generation WLAN will provide much higher transmission rates. However, the medium access control (MAC) was designed for lower data rates, such as 1–2 Mbps, and it is not an efficient MAC. Furthermore, a theoretical throughput limit exists due to overhead and limitations of physical implementations, and therefore increasing transmission rate cannot help a lot. Designing efficient MAC strategies becomes critical and important. In this paper, we introduce and propose a series of efficient MAC strategies to overcome the fundamental overhead, and to improve performance. The protocols and mechanisms include Direct Link Protocol, Without Acknowledgement, Without Retransmissions, Block Acknowledgement Protocol, Concatenation, Packing, Multiple Frame Transmission (versions 1 and 2) and Piggyback. The aim of this paper is to introduce and propose these efficient new MACs not only for current IEEE 802.11 standards (.11a/.11b/.11g), but also for the next generation WLAN with higher speed and higher throughput, especially for IEEE 802.11n. Copyright © 2006 John Wiley & Sons, Ltd.

Most of cache replacement schemes are access-based replacement policies since they are based on object access frequency/time information. However, update information is extremely important since an updated object makes itself invalid, and the object hit information becomes useless. In this paper, we propose two update-based replacement policies, the least access-to-update ratio (LA2U) and least access-to-update difference (LAUD) in wireless data access, based on both update frequency and access frequency. Extensive simulations have been carried out to evaluate the proposed policies. Simulation results show that the proposed update-based policies outperform access-based policies at most cases. It is concluded that considering update information in designing replacement policies can increase cache performance, especially, when updates are heavy.

A block ACK (BTA) scheme has been proposed in IEEE 802.11e to improve medium access control (MAC) layer performance. It is also a promising technique for next-generation high-speed wireless LANs (WLANs) such as IEEE 802.11n. We present a theoretical model to evaluate MAC saturation throughput of this scheme. This model takes into account the effects of both collisions and transmission errors in a noisy channel. The accuracy of this model is validated by NS-2 simulations.

In this paper, we provide a survey on energy-efficient scheduling mechanisms in sensor networks that have different design requirements than those in traditional wireless networks. We classify these mechanisms based on their design assumptions and design objectives. Different mechanisms may make different assumptions about their sensors including detection model, sensing area, transmission range, failure model, time synchronization, and the ability to obtain location and distance information. They may also have different assumptions about network structure and sensor deployment strategy. Furthermore, while all the mechanisms have a common design objective to maximize network lifetime, they may also have different objectives determined by their target applications.

Cache mechanisms have been proposed for wireless data access. Poll-each-read (PER) is a fundamental cache access algorithm and has been studied in wireless data access. However, PER overlooks the importance of update information. In this paper, we propose a server-based PER (SB-PER) cache access mechanism in which the server makes replacement decisions. Through extensive simulations, we provide a profound performance analysis for the SB-PER in terms of access rate, update rate, cache size, and database size, which is useful for understanding of the related algorithms. Simulation results show that the proposed SB-PER outperforms the original PER in terms of effective hit ratio and cost.

This paper first surveys security vulnerabilities of IEEE 802.11 WLANs. Then, two approaches to enhance security are proposed to overcome some known vulnerabilities and thus to provide better data confidentiality and authentication. Finally, simulation methodology is presented, and simulate results are provided. Our studies show that the proposed enhancements provide better data confidentiality with some degree of computing cost as the tradeoff.

We propose a two-level adaptive callback access mechanism for wireless data access. In the first level, cache size in a mobile termination is adaptively adjusted based on update-to-access-ratio. In the second level adaptation, when an object is updated at the server, whether to send the object directly or an invalidation message, adaptively depends on the object size. We analytically model cost function, and the optimal cache size and the optimal adaptation threshold value are obtained simultaneously. Both simulations and analytical results are used to study the performance.

In this paper, we present analytical models for the pipeline paging (PP) scheme, the blanket paging (BP) scheme, and the sequential paging (SP) scheme. In the PP scheme, multiple paging requests can be served in a pipeline manner in different paging areas. Discovery rate, total delay, paging delay, and cost are derived analytically as functions of traffic load. Extensive simulations are carried out to verify our analytical results. Our study shows that the PP scheme outperforms both the BP and SP schemes.

Block ciphers encrypt a fixed size block of plaintext at a time to produce a block of ciphertext. Stream ciphers encrypt stream data, such as voice or Telnet traffic, one bit or more bits at a time. The cipher feedback mode is one stream cipher implemented by a block cipher via multiple stages, and in each stage, one bit or a number of bits of plaintext are encrypted at a time. In this paper, we study error performance of the stream-based cipher feedback mode in an error channel in terms of throughput. We model performance of the cipher feedback mode in terms of the probability that part/whole of the ciphertext cannot be successfully decrypted, as well as the throughput by adopting the cipher feedback mode. We explicitly derive the optimal number of stages in the cipher feedback mode to achieve the optimal throughput, given an error rate.

Two paging schemes, called separated macro-micro paging (SMMP) and combined macro-micro paging (CMMP) for macrocell-microcell hierarchal cellular networks, are proposed in this paper. In this kind of networks, mobile terminals (MTs) can receive signals from both macrocells and overlaid microcells. In the SMMP scheme, an MT can be paged from either the macrocell-tier or its overlaid microcell-tier. In the CMMP scheme, an MT is paged in a mix of the macrocell-tier and its overlaid microcell-tier. Optimal paging load balance between the macrocell-tier and the microcell-tier has been studied.

The IEEE 802.15.4 specification defines medium access control (MAC) layer and physical layer for wireless sensor networks. Furthermore, security mechanisms are also defined in the specification. This paper first surveys security services provided in the IEEE 802.15.4 wireless sensor networks. Then, some security enhancements are proposed to prevent same-nonce attack, denial-of-service attack, reply-protection attack, ACK attack, etc.

We evaluate the performance of voice transmission over a single-AP WLAN analytically and via simulation. Given the parameters of the medium access control protocol and different voice codecs, the voice capacity of the WLAN, in terms of the maximum number of voice connections that can be supported by the WLAN with satisfactory user-perceived quality, is obtained. Our analysis is applicable for unsaturated-station scenarios, and considers the practical issue induced by the unbalanced traffic. Extensive simulations have been performed to validate the analytical results.

In sequential paging (SP) schemes, the paging process is considered on a per user basis. When an incoming call reaches a mobile terminal (MT), the associated location area is divided into several paging areas (PAs) and PAs are paged one by one until the MT is found. Even though SP algorithms can reduce the paging cost compared to blanket paging (BP), they introduce extra and unnecessary delay, and are not efficient. We present a pipeline paging (PP) scheme in which multiple paging requests (PRs) can be served in a pipeline manner for different paging areas. We study the proposed scheme via extensive simulations in terms of discovery rate, total delay, and cost under different traffic loads. Our study shows that the PP scheme outperforms both the BP and SP schemes in terms of discover rate and total delay, while maintaining a cost similar to that of the SP scheme. The study also shows that when the paging delay constraint D is as large as 6, the PP scheme achieves almost 171% of the BP's discovery rate and 58% of the BP's cost, whereas the SP's discovery rate is far less than that of the BP scheme.

Nodes having a self-centrically broadcasting nature of communication form a wireless ad hoc network. Many issues are involved to provide quality of service (QoS) for ad hoc networks, including routing, medium access, resource reservation, mobility management, etc. Previous work mostly focuses on QoS routing with an assumption that the medium access control (MAC) layer can support QoS very well. However, contention-based MAC protocols are adopted in most ad hoc networks since there is no centralized control. QoS support in contention-based MAC layer is a very challenging issue. Carefully designed distributed medium access techniques must be used as foundations for most ad hoc networks. In this paper, we study and enhance distributed medium access techniques for real-time transmissions in the IEEE 802.11 single-hop ad hoc wireless networks. In the IEEE 802.11 MAC, error control adopts positive acknowledgement and retransmission to improve transmission reliability in the wireless medium (WM). However, for real-time multimedia traffic with sensitive delay requirements, retransmitted frames may be too late to be useful due to the fact that the delay of competing the WM is unpredictable. In this paper, we address several MAC issues and QoS issues for delay-sensitive real-time traffic. First, a priority scheme is proposed to differentiate the delay sensitive real-time traffic from the best-effort traffic. In the proposed priority scheme, retransmission is not used for the real-time traffic, and a smaller backoff window size is adopted. Second, we propose several schemes to guarantee QoS requirements. The first scheme is to guarantee frame-dropping probability for the real-time traffic. The second scheme is to guarantee throughput and delay. The last scheme is to guarantee throughput, delay, and frame-dropping probability simultaneously. Finally, we propose adaptive window backoff schemes to optimize throughput with and without QoS constraints.

The IEEE 802.11 distributed coordination function (DCF) enables fast installation with minimal management and maintenance costs, and is a very robust protocol for the best effort service in wireless medium. However, the current DCF is unsuitable for real-time applications. This paper studies backoff-based priority schemes for IEEE 802.11 and the emerging IEEE 802.11e standard by differentiating the minimum backoff window size, the backoff window-increasing factor, and the retransmission limit. An analytical model is proposed to derive saturation throughputs, saturation delays, and frame-dropping probabilities of different priority classes for all proposed priority schemes. Simulations are conducted to validate analytical results. The proposed priority schemes can be easily implemented, and the results from this paper are beneficial in designing good priority parameters.

The IEEE 802.11 medium access control (MAC) is a very robust protocol for the best effort service in the wireless medium. However, many studies have reported that it is not very efficient. One of the fundamental problems of MAC inefficiency is overhead. In this paper, we propose two novel mechanisms to reduce overhead of the IEEE 802.11 protocols: 1) concatenation mechanism (CM); and 2) piggyback mechanism (PM). Performance analysis is conducted under both the best-case scenario and the saturation scenario. Studies show that both proposed schemes have greatly improved the system performance.

Abstract It is well known that the medium access control (MAC) layer is the main bottleneck for the IEEE 802.11 wireless LANs. Much work has been done on performance analysis of the 802.11 MAC. However, most of them assume that the wireless channel is error free. In this paper, we investigate the saturation throughput performance achieved at the MAC layer, in both congested and error‐prone channels. We provide a simple and accurate analytical model to calculate the MAC throughput. The model is validated through extensive simulation results. Our results show that channel errors have a significant impact on the system performance. Copyright © 2005 John Wiley & Sons, Ltd.

Adaptive multimedia services are very attractive since resources in wireless/mobile networks are relatively scarce and widely variable, and more importantly the resource fluctuation caused by mobility and channel fading can be mitigated using adaptive services. Therefore, there are extensive research activities on Quality of Service (QoS), call admission control, as well as bandwidth degradation and adaptation for adaptive multimedia services in wireless/mobile networks in recent years. However, fairness of bandwidth degradation has largely been ignored in previous work and remains an important issue in adaptive multimedia service provisioning. In this paper, we propose and study proportional degradation service provisioning in wireless/mobile networks that offer multiple classes of adaptive multimedia services. The proposed proportional degradation fairness model guarantees the proportional bandwidth degradation among different classes of services. Two proportional degradation scenarios are studied in this paper. In the first scenario, we study the proportional degradation provisioning with two QoS parameters for adaptive multimedia: the degradation ratio (DR) and the degradation degree (DD). In the second scenario, we study the proportional degradation provisioning with a new QoS parameter for adaptive multimedia: the degradation area (DA). For each scenario, based on the QoS parameters, proportional degradation adaptation algorithms are proposed to approximate the proportional degradation model, to fairly adapt calls' degradations, to utilize the system resource efficiently, as well as to optimize QoS parameters. Performance studies show that in the first scenario, proportional DR has been achieved very well, whereas proportional DD has not been well achieved. In other words, DR outperforms DD in terms of proportional degradation. In the second scenario, proportional DA has been well achieved. Furthermore, bandwidth resources have been efficiently utilized and DA has been minimized. Copyright © 2004 John Wiley & Sons, Ltd.

Integration of 3G and wireless LAN (WLAN) becomes a trend in current and future wireless networks, and brings many benefits to both end users and service providers. In this paper, we provide a comprehensive survey on integration of 3G and WLAN. We discuss issues such as underline network architectures, integrated architectures, mobility management, and quality of service (QoS). We particularly study handoff QoS mapping and guarantee between 3G and WLAN, as well as how seamless voice/multimedia/data handoff becomes possible. Copyright © 2005 John Wiley & Sons, Ltd.

We study backoff-based priority schemes for IEEE 802.11 and the emerging IEEE 802.11e standard by differentiating the minimum backoff window size, the backoff window-increasing factor, and the retransmission limit. An analytical model is proposed to derive saturation throughputs, saturation delays, and frame dropping probabilities of different priority classes for all proposed priority schemes. Simulations are conducted to validate analytical results. The proposed priority schemes can be easily implemented, and results are beneficial in designing good priority parameters.

In this paper, a dynamic HLR (home location register) scheme for location management in PCS (personal communications service) networks is presented. The proposed scheme provides a dynamic copy of mobile terminal location information in the nearest (current) HLR database. A modified table lookup procedure is also proposed for determining the current HLR easily. It allows the location registration and call delivery to be performed efficiently. An analytical model is developed for studying the performance of the proposed scheme. The performance study shows that the proposed scheme significantly reduces the system overhead for location management in PCS networks.

In order to support multimedia applications such as voice and video over the wireless medium, a contention-based channel access function, called enhanced distributed coordination function (EDCF), is being developed in the emerging standard IEEE 802.11e. In EDCF, differentiated services are provided for different traffic classes. In this paper, we propose a two-level protection and guarantee mechanism for voice and video traffic in IEEE 802.11e wireless LANs. In the first-level protection, the existing voice and video flows are protected from the new and other existing voice and video flows. In the second-level protection, the voice and video flows are protected from the best-effort data traffic. For each protection level, a couple of protection mechanisms are proposed. Extensive simulation results show that the proposed two-level protection and guarantee mechanism is very effective in terms of protecting and guaranteeing existing voice and video flows as well as fully utilizing the channel capacity.

Best-effort data control and admission control are vital to guarantee quality of service for real-time (voice and video) transmissions in the IEEE 802.11e wireless LANs. In this paper, we propose and study a global data parameter control scheme integrated with a measurement-based admission control scheme for the IEEE 802.11e enhanced distributed channel access. In the proposed global data control scheme, the access point dynamically controls best-effort data parameters of stations globally based on traffic condition. Such a global/centralized data parameter control mechanism provides the best fairness for data transmissions among stations. In the proposed centrally-assisted distributed admission control scheme for voice and video transmissions, stations listen to available budgets from the access point to make decisions on acceptance or rejection of a voice or video stream. Such a scheme provides good differentiation among different access categories and provides good fairness among real-time streams within the same access category. The proposed mechanisms are evaluated via extensive simulations. Studies show that, with the proposed global data control scheme and the admission control scheme, quality of service can be greatly improved while maintaining a good utilization.

Location management is a key issue in personal communication service networks to guarantee the mobile terminals to continuously receive services when moving from one place to another. We study two location management schemes, a dynamic movement-based scheme (DYNAMIC-3G) and a static scheme (STATIC-3G), for 3G cellular networks where home location registers, gateway location registers (GLRs), and visitor location registers form a three-level hierarchical mobility database structure. For both schemes, the cost functions are formulated analytically. We prove that there is an optimal movement threshold that minimizes the total cost function of DYNAMIC-3G and propose a binary search algorithm to find the optimal threshold. Furthermore, we present performance evaluation and comparison of the proposed schemes with the previous schemes in 2G cellular networks where the GLR is not present. Our studies validate the optimality of the DYNAMIC-3G scheme and show that the proposed schemes outperform the previous schemes, especially when the remote-local-cost ratio is high. The comparison results between DYNAMIC-3G and STATIC-3G indicate that DYNAMIC-3G should be adopted when the mobility rate is low, and STATIC-3G should be adopted otherwise. Furthermore, DYNAMIC-3G tends to perform better than STATIC-3G when the paging cost is high or the number of cells in a location area is large.

We propose a dynamic fractional movement-based location management scheme for 3G networks where home location registers (HLRs), gateway location registers (GLRs), and visitor location registers (VLRs) are formed into a three-level hierarchical mobility database structure. The cost functions of location updates and paging are formulated analytically. We prove analytically that there is an optimal fractional movement threshold that minimizes the total cost function. Our study shows that the proposed scheme outperforms the previous two-tier mobility database scheme, especially when the remote-local-cost ratio is high.

In a 3G cellular network, the visitor location registers (VLRs), the gateway location registers (GLRs), and the home location registers (HLRs) from a three-level mobility database structure. When users leave a GLR/VLR service area, deregistration with GLR/VLR is required. Deregistration may create significant traffic in the network, especially the traffic between GLR and a HLR, which is the remote/international traffic. In this paper, we propose a hierarchical implicit deregistration scheme with a first/subsequent registration in 3G cellular networks to effectively eliminate deregistration traffic. An analytic model is proposed to carry out the performance of the proposed scheme. Our study shows that the proposed scheme not only reduces the local deregistration traffic between the GLR and the VLR, but also reduces the remote/international deregistration traffic between the HLR and the GLR. This is especially true when the ratio of the cost of the remote/international traffic between the GLR and the HLR to the cost of local traffic between the VLR and the GLR is high.

We introduce the emerging IEEE 802.11e standard to support quality of service at medium access control level. One of the most important functions in 802.11e is the contention-based channel access mechanism called enhanced distributed coordination function (EDCF), which provides a priority scheme by differentiating the inter-frame space and the initial window size. We propose an analytical model to evaluate the EDCF priority scheme. Saturation throughput and saturation delay are derived analytically. Simulations are also conducted to validate analytical results. Our study shows that differentiating the initial window size is better than differentiating the inter-frame space in terms of total throughput and delay.

Abstract In a 3G cellular network, the gateway location registers (GLRs), the visitor location registers (VLRs) and the home location registers (HLRs) form a three‐level mobility database structure. An HLR database is used to record mobile users' permanent subscription information. A VLR database is used to temporarily hold the subscription information of the roaming users who visit the service area of the VLR. A GLR is deployed at the edge of a visited network handling the location management of a roaming subscriber in a visited network without involving the HLR, and holding users' temporary subscription information when the mobile user is within the service area of the GLR. When users leave the GLR/VLR service area, the corresponding records in the GLR/VLR are deleted. Owing to mobility, a GLR/VLR database may overflow at some time periods when the number of visitors significantly increases in the GLR/VLR area. If the GLR/VLR is full, the registration procedure fails and the system cannot deliver services to incoming users under the existing cellular technology. This issue is called GLR/VLR overflow. In this paper, we propose a hierarchical database overflow control mechanism in 3G cellular networks to effectively eliminate the GLR/VLR overflow problem, and incoming users can continuously use the service with insignificant extra overhead. An analytic model is proposed to investigate the performance of the hierarchical database overflow control scheme. Our study not only shows that the probability of VLR overflow is very small but also shows that among the VLR overflow cases, there is a very small probability of GLR overflow. In other words, the overhead in terms of causing both local and remote/international signaling traffic by exercising our approach is very small. Copyright © 2003 John Wiley & Sons, Ltd.

In this paper, we propose proportional degradation services for multiple classes of adaptive multimedia services in wireless/mobile networks. First, we introduce two novel quality of service (QoS) parameters for the bandwidth degradation: the degradation ratio (DR) and the degradation degree (DD). Then, we propose two measurement-based call admission control (CAC) schemes to satisfy QoS requirements, and to utilize the resource efficiently. They are the window averaging (WA) scheme and the leaky-bucket integration (LBI) scheme. Finally, a K-level proportional bandwidth adaptation algorithm is also proposed to fairly adapt calls' bandwidth, to minimize DR and DD, to minimize DD with higher priority than to minimize DR, and to guarantee the ratios of service degradation among classes.

Power saving is an important issue for mobile handsets since they must rely on their batteries. To reduce the battery consumption of mobile handsets, we propose a fractional threshold-based wake-up mechanism, which switches the system into the sleep mode when the packet-receiving queue is empty, and switches the system on when the number of packets in the queue "reaches" a fractional threshold value. A fractional threshold value can be any real number, instead of just a natural number. In fact, the fractional threshold value indicates the mean threshold value. Our study indicates that the fractional threshold scheme with probability 1 provides an optimal power saving solution. The optimization objective is to minimize switch-on rate while satisfying the quality of service requirement, which is an upper bound of the packet dropping probability.

We propose a quality of service (QoS) provisioning framework for multimedia traffic in wireless/mobile networks. We classify the services into three categories: bandwidth guaranteed (BG) service, bandwidth not-guaranteed (BNG) service, and best effort (BE) service. BG service is for non-adaptive multimedia traffic or non-multimedia traffic; BNG service is for adaptive multimedia traffic, whereas BE service is for computer data or multimedia traffic that can be suspended and reactivated. For each of the above three categories, traffic descriptors and QoS parameters are defined and specified. In addition, there are multiple classes for each of the above three categories. For all service categories we present, analytically, an optimal call admission control that guarantees the QoS parameters and traffic descriptors, and maximizes the revenue. Simulation results reveal that the proposed optimal call admission control scheme is very promising.

There is a great demand on multimedia applications with quality of service (QoS) in wireless/mobile networks. In this paper, we propose an optimal call admission control (CAC) framework with a bandwidth re-allocation (BRA) algorithm for adaptive multimedia services in wireless/mobile networks, where the bandwidth of an ongoing call is time-varying during its lifetime. The optimization is in the sense of optimizing the revenue and satisfying QoS requirements. We adopt a semi-Markov decision process (SMDP) approach to model both the CAC and the BRA at the same time. The proposed approach allows us to make decisions on CAC as well as on BRA. The simplex method in linear programming is used to solve the optimal decision problem. Numerical results reveal that the proposed CAC-BRA scheme adapts itself well to time-varying multimedia traffic, achieves optimal revenue and satisfies QoS up to the upper-bound handoff blocking probability.