The evolution of next-generation wireless networks demands intelligent, adaptive, and explainable decision-making for robust communication in dynamic environments. This paper presentsEnwar 2.0, the first agentic large language model (LLM) framework integrating adaptive retrieval-augmented generation (RAG) and chain-of-thought (CoT) reasoning into situation-aware and explainable wireless network management.Enwar 2.0introduces two specialized agents: a transformer-fusion (TransFusion)-based beam prediction agent and an environment perception agent, both of which fuse multi-modal sensory inputs—including camera, LiDAR, radar, and GPS—from the DeepSense6G dataset. The beam prediction agent enables infrastructure-to-vehicle (I2V) target-in-the-loop beam tracking and real-time adaptation based on dynamic environmental conditions. In contrast, the environment perception agent provides situation-aware reasoning and justifications for beam decisions. Unlike its predecessor,Enwar 1.0, which relied on static knowledge bases (KBs) and text-only LLMs,Enwar 2.0is designed for CoT reasoning, leverages LLaMa3.2-3B/LLaMa3.1-8B/LLaMa3.3-70B for text-generation, the multi-modal capabilities of LLaMa 3.2, and employs LlamaIndex for fine-grained, dynamic context retrieval, eliminating retrieval ambiguities and enhancing response relevance. Numerical results show that the beam prediction agent achieves up to 90.0% Top-3 accuracy at$t+3$, effectively predicting optimal beam selections three time steps ahead. Overall,Enwar 2.0achieves state-of-the-art performance, with up to 89.7%/83.5% interpretation/perception correctness, 81.6%/80.9% faithfulness, and 89.9%/88.2% relevancy. In comparison, the baseline pretrained LLaMa3 models without adaptive RAG achieves up to 80.3%/77.3% correctness, and the baseline without RAG performs significantly worse at 67.1%/64.8%. Additionally,Enwar 2.0reduces processing time by over 100% relative to the baseline, while its adaptive RAG improves performance by up to 13.7% compared to static RAG.

Date of Conference: 04-07 August 2025. Conference Location: Tokyo, Japan

The rapid evolution of wireless technologies has intensified interest in open and fully programmable radio access networks for whole-stack research, innovation, and evaluation of emerging solutions. Large-scale wireless living labs, such as ARA, equipped with real-world infrastructure play a vital role in this evolution by enabling researchers to prototype and evaluate advanced algorithms for next-generation wireless systems in outdoor and over-the-air environments benefiting from real-world fidelity and end-to-end programmability. However, at the core of this innovation is the performance in terms of coverage and reliability of these wireless living labs. For instance, interfacing power amplifiers and low noise amplifiers with software-defined radios (SDRs) for experimenting outdoors introduces issues in random access procedure—a process crucial in establishing connectivity between user equipment (UE) and the core network in 5G and 6G systems. Therefore, to ensure seamless connectivity and reliable communications in open-source 5G software stacks such as OpenAirInterface (OAI), we propose a slot-based approach to the 5G random access procedure leveraging full downlink (DL) and uplink (UL) slots instead of using special or mixed slots. We highlight how this approach achieves reliable 5G connectivity over 1 mile—the longest communication range that has been achieved so far in real-world settings using open-source 5G software stacks and the Universal Software Radio Peripheral (USRP) SDRs. We also demonstrate that, in a highly obstructed environment such as an industrial setting, we can increase the probability of a successful random access procedure to 90%–100% when we use at least 9 OFDM symbols to transmit msg2 and msg3.

Batteryless sensor nodes, powered solely by energy harvesting, are a promising alternative to battery-powered sensor nodes. However, energy harvesting rates being very low, unreliable, and time-varying, nodes cannot sustain a continuous operation, making them intermittently powered. As a result, these nodes incur unpredictable wakeup times due to continuously varying off-times. To perform tasks like distributed sensing, time synchronization, and communication for intermittently powered nodes, timely execution and robust coordination is vital. To achieve robust coordination, nodes must guarantee to be ON at a coordinated target time regardless of harvesting variations. To ensure robust coordination of on-times, we propose PAIL, a novel hardware-software approach where the hardware component enforces a constant off-time, with small variations. The software component dynamically corrects for those variations. We fabricated a PAIL sensor node and validated its ability to discover neighboring nodes. Using extensive simulations calibrated from experimental measurements, we observe that PAIL maintains nearly 99.3% coordination at steady state. In the context of pairwise communication, we show that leveraging PAIL coordination, nodes improve packet tail latency by 99%.

Wireless innovation can significantly benefit from having access to real-world, over-the-air (OTA) living labs for open-source prototyping and field evaluation of emerging, state-of-the-art solutions. However, the existing open-source 5G testbeds are either confined to controlled indoor environments, or they use commercial-off-the-shelf (COTS) user equipment (UEs) only without supporting software-defined-radio (SDR) UEs, thus lacking real-world fidelity or end-to-end programmability from UEs to gNBs and core networks. To fill the gap, we develop and deploy AraSDR that, as an integral element of the ARA Platform for Advanced Wireless Research (PAWR) on rural broadband, serves as a first-of-its-kind outdoor living lab supporting end-to-end, fully-programmable 5G experiments with SDR UEs and base stations (BSes) in real-world rural settings. AraSDR deploys in agriculture farms and rural cities NI N320 and B210 as the BS and UE SDRs respectively, and it employs low-cost, performant custom RF front-ends with power amplifiers (PAs) and low-noise amplifiers (LNAs) to boost the transmit and receive signals for extended cellular coverage. To enable real-world SDR-based experiments with open-source 5G stand-alone (SA) TDD cellular operations, we address the challenges of reliable control signaling, precision timing of the transmission/reception mode of RF front-ends, as well as transmission and reception gain control. We develop the software control framework to support remote experiments with streamlined workflows and to enable container-based experiment portability and reproducibility. Using OpenAirInterface (OAI) as an example open-source 5G software platform, we demonstrate the capability of AraSDR in supporting real-world, OTA 5G experiments.

ARA is an at-scale Platform for Advanced Wireless Research (PAWR), specifically tailored to the unique community, application, and economic context of rural regions. It features the first-of-its-kind real-world implementation of long-distance, high-capacity wireless backhaul and access systems spanning over 30 km in diameter. Leveraging both software-defined radios and programmable Commercial Off-The-Shelf (COTS) systems, ARA orchestrates the wireless resources alongside the networking and compute resources for enabling end-to-end experiments involving user equipment, base stations, edge computing, and cloud infrastructure. Such an integration facilitates the coevolution of rural-focused wireless innovation and applications, while helping to advance the frontiers of advanced Next-G wireless systems such as Open RAN. As of summer 2024, ARA is publicly accessible with 7 base stations (BSes) and over 30 user equipment (UEs). In this demo, we share advanced wireless research experiments enabled by ARA, involving MU-MIMO in TV White Space (TVWS) bands, long-range mmWave and microwave backhaul communications, and open-source 5G NR protocol stacks such as srsRAN and OpenAirInterface (OAI).

Time synchronization is a critical component in network operation and management, and it is also required by Ultra-Reliable, Low-Latency Communications (URLLC) in next-generation wireless systems such as those of 5G, 6G, and Open RAN. In this context, we design and implement AraSync as an end-to-end time synchronization system in the ARA wireless living lab to enable advanced wireless experiments and applications involving stringent time constraints. We make use of Precision Time Protocol (PTP) at different levels to achieve synchronization accuracy in the order of nanoseconds. Along with fiber networks, AraSync enables time synchronization across the AraHaul wireless x-haul network consisting of long-range, high-capacity mmWave and microwave links. In this paper, we present the detailed design and implementation of AraSync, including its hardware and software components and the PTP network topology. Further, we experimentally characterize the performance of AraSync from spatial and temporal dimensions. Our measurement and analysis of the clock offset and mean path delay show the impact of the wireless channel and weather conditions on the PTP synchronization accuracy.

As the Platform for Advanced Wireless Research (PAWR) in rural broadband, the ARA wireless living lab features the deployment of first-of-its-kind wireless access and backhaul platforms in real-world agriculture and rural settings, and preliminary experiments have demonstrated very promising results, e.g., up to 3.2 Gbps wireless access throughput and more than 10 Gbps throughput across a wireless backhaul link of over 10 km. ARA is expected to be publicly released for broad community use starting in September 2023. Through this demo, we plan to share, for the first time, with the wireless research community the transformative research experiments enabled by ARA. To stimulate discussion and community participation, we will demonstrate a few example experiments ranging from MU-MIMO in TV White Space (TVWS) bands to long-range mmWave and microwave backhaul communications, as well as open-source 5G NR protocol stacks such as srsRAN and OpenAirInterface.

Current mainstream biometric user authentication approaches are based on passive measurements of the subject's characteristics, and usually come with less-than-satisfactory accuracy. This paper takes a unique approach to biometric authentication. Specifically, instead of training a machine learning algorithm to recognize a legitimate user, the paper proposes a hybrid type of training, in which the legitimate user is also trained to use a customized instance of the machine. The user thus achieves a level of artificially-induced expertise to interact with the machine, which makes the user easier to recognize. We implement this concept in a mouse-based user authentication system, in which we produce customized machine instances by introducing an angle offset to the standard mouse. Human subjects then rely on their kinesthetic intelligence to achieve motor learning and visual-motor adaptation to the modified mouse. We design a 7-week IRB-approved experiment, collect data from 18 human subjects over this period, and evaluate the proposed approach with two existing state-of-the-art mouse-based authentication schemes. We find that, in both schemes, our approach significantly outperforms the baseline in which a regular unaltered mouse is used. Somewhat surprisingly, results also show that our approach improves the authentication performance even when both legitimate and non-legitimate users are trained to exactly the same instance of customized machine (i.e., the same mouse angle offset). In addition, we also observe that users can generally maintain their learned expertise even after one week of washout, which further demonstrates the practicality of the approach. Finally, we present a practical strategy to manage the enrollment of users in such a proposed system.

Wireless sensor nodes powered solely by energy-harvesting show promise in enabling truly pervasive, long-duration sensing by avoiding the fragility, cost, and maintenance limitations of batteries. Unfortunately, since the amount of energy harvested is often significantly less than the active consumption of the device, these devices operate intermittently with limited control of when they are on and how long they are off. Such uncontrollable intermittency first poses a challenge for traditional time synchronization error metrics, since nodes cannot reliably communicate time values at known intervals, resulting in the illusion that nodes are out-of-sync. Second, long duration off-times can exceed the inherent timing limit of persistent clocks that intermittent nodes rely on to measure off-times. Bursty groups of long off-times can cause traditional time synchronization mechanisms to re-converge slowly, incurring significant periods of high error in which nodes are effectively out-of-sync. In this paper, we define the meaning of a shared sense of time for intermittently-powered nodes, and propose two intermittency-aware synchronization error metrics. We then propose an intermittency-resilient time synchronization mechanism, called Levee, that exhibits more rapid re-convergence after losing time and a 2.12× reduction in maximum time synchronization error for a 48-hour period.

Batteryless energy-harvesting sensor nodes can operate indefinitely, but if the harvesting rate is too low, they must operate intermittently. Intermittent operation imposes various challenges upon the system. One of the least-studied is communication–if nodes are unpowered for long, unpredictable periods of time, how can they reliably communicate with each other? In prior work, we proposed the concept of lifecycle management protocols (LMPs) to mitigate this issue and enable wireless communication directly between intermittent sensor nodes using active radios. In this paper, we propose a design framework for a class of LMPs. We then provide analytical models for the delay and throughput of two-node communication using this framework. Finally, we implement this framework on hardware and validate our models in an experimental setting. To the best of our knowledge, this is the first design framework for, and implementation of, protocols for enabling and improving general-purpose communication between intermittent sensor nodes using active radios.

Nodes in batteryless sensor networks operate intermittently, making tasks such as node-to-node communication and coordinated computation extremely challenging. Adding to this challenge, a node typically has little control over its intermittency. Therefore, in this paper, we introduce a new class of protocols, which we call lifecycle management protocols (LMPs), to better control and manage the intermittency of batteryless nodes. These protocols may be designed and optimized for a particular task; here, we propose and evaluate a set of LMPs designed to enable direct communication between intermittent batteryless sensor nodes with active radios.

Batteryless sensing devices powered solely by ambient energy sources are expected to operate in an intermittent manner, since they do not have a predictable, or even continuous, energy supply. When such an intermittent system is powered off, it cannot keep track of time using conventional means. However, a continuous sense of time is critical for any system running real-time or time-sensitive applications. In this paper, we present HARC (Heterogeneous Array of Redundant Persistent Clocks), a novel solution to the problem of timekeeping for batteryless, intermittently-powered systems. HARC uses a heterogeneous, redundant array of capacitor-based persistent clocks that each decay in parallel, but at different rates, to provide variation-resilient high accuracy over a wide range of power off-times. We demonstrate the feasibility and effectiveness of HARC using experimental evaluations on a HARC prototype, and trace-based simulations of HARC-supported communication directly between two devices intermittently-powered by RF harvesting.

Biometric user authentication is at the core of multifactor authentication, and mouse-based biometric authentication comes at no additional cost for most computer systems. This paper describes a mouse-based user authentication scheme, called MAUSPAD, which uses a novel progress-adjusted dynamic time warping (PADTW) algorithm, along with a segmentation algorithm, to accurately and meaningfully measure the differences between observed data and reference data. By introducing a new concept, which we call progress, into standard DTW, the new PADTW can have better control of the warping and mapping process and hence is more suitable for comparing time-stamped spatial sequences such as mouse cursor movements. Furthermore, in order to preserve the important but transient details in the cursor movement (which may be critical in identifying a specific user), we apply a segmentation algorithm to divide each reference cursor movement into multiple smaller segments, and measure the differences between cursor movements at the segment level. Evaluation results on two mouse-behavior datasets show that MAUSPAD yields the best overall performance among tested schemes, and demonstrate the effectiveness of PADTW over DTW, and segmentation over non-segmentation. The processing techniques developed herein can be extended to applications that rely on sequence comparison, and where relevant sequence information spans multiple semantic domains.

The restriction of access to software systems is more important than ever. For example, critical data is increasingly being stored on web services that are accessible from anywhere in the world. Yet most primary authentication methods are still largely based on passwords, which are vulnerable to various attacks such as phishing scams and keyloggers. Advanced methods of behavior-based authentication exist, but most are designed for a specific area or system and are not generally applicable. In this paper, we propose a generic continuous authentication scheme for software systems, which supplements existing authentication schemes and works as an auxiliary layer to provide additional protection against impostors. The kernel of our scheme is a novel monitoring engine that detects impostors in real-time based on behavior and context information. We evaluate our scheme on a dataset consisting of real users' historical records provided by our industrial partner, and the results demonstrate that our approach achieves a high classification accuracy with only a short delay in detection, allowing for real-time, continuous authentication.

This paper presents RIVER-MAC, a very efficient receiver-initiated asynchronously-duty-cycled medium access control (MAC) protocol for IoT devices. The key innovations of RIVER-MAC include (1) a CCA-based rendezvous to reduce idle listening for the sender node by an order of magnitude, and (2) a beacon train-based collision resolution scheme to reduce contention between receiver nodes, a previously-overlooked issue in receiver-initiated MAC protocol design. We have implemented RIVER-MAC in Contiki OS, and used extensive Cooja simulations to demonstrate its high performance compared to RI-MAC (a classic receiver-initiated protocol), as well as ContikiMAC (a state-of-the-art sender-initiated asynchronously duty-cycled MAC protocol) in our tested scenarios. We also have used analytic studies to show that RIVER-MAC yields a comparable performance with a wakeup radio-based scheme, an emerging alternative to duty-cycled MAC protocols for IoT devices.

In this paper, we investigate the problem of optimal planning and deployment of multiple relays to support energy-efficient uplink transmissions of Internet of Things (IoT) devices. A novel approach is proposed to optimize the relay locations with the objective of minimizing the total energy consumption of the network. In addition, the uplink transmit power of IoT devices and the device-relay-channel association are jointly optimized to meet the QoS requirement of IoT devices. A mixed-integer linear programming (MILP) problem is formulated to obtain the optimal solution. We also design a low-complexity genetic algorithm to provide a sub-optimal solution to the problem.

The Internet of Things (IoT) paradigm has been proposed to assist and automate various activities such as environment monitoring by connecting physical devices in the area of our interest. Low- cost, battery-operated, and resource-limited IoT devices usually are densely deployed for robustness against node failures as well as for providing desired quality of monitoring. One of the effective ways to prolong the lifetime of an IoT network is to schedule selected IoT devices to enter the sleep mode and activate them later in a future time. However, this must be done carefully in order not to violate application-specific requirements. In this paper, we study the scheduling problem of IoT devices to prolong the network lifetime while satisfying both report- accuracy and timely-update requirements. We model and analyze the network as a Markov process, and derive system parameters. We formulate an optimal node activation scheduling problem and propose a low-complex greedy algorithm to expedite the scheduling process. Evaluation results demonstrate the effectiveness of both optimal and greedy algorithms.

The technology of low-power wireless sensor networks (WSNs) needs to become more flexible to cater to emerging data-driven applications and the Internet of Things. For example, WSNs need to look beyond the traditional many-to-one data collection traffic model and begin to support multicast communications. However, efficient multicasting in WSNs is challenging. In this paper, we propose to apply the concept of opportunistic forwarding to create an opportunistic multicast framework for duty-cycled WSNs. Our framework allows for any node to directly and efficiently multicast to any subset of known potential destinations. We propose several variations of schemes to operate within this framework. We evaluate our framework and the proposed schemes using simulations.

Thunder localization provides an important solution to lightning location systems. This paper designs a smartphone- based thunder localization system, ThunderLoc. The key idea is to turn the localization problem into search problem in Hamming space by collecting the dual-microphone data of smartphones via crowdsensing mechanism. We utilized the TDOA of dual- microphone integrated in smartphone. After the quantization with a bit for the TDOA measurement from the smartphone nodes, thunder localization is performed by minimizing the Hamming distance between the measured binary sequence and the binary vectors in a database. Evaluation results demonstrate that ThunderLoc can effectively localize the virtual thunder with good robustness.

Energy-efficient and robust-time synchronization is crucial for industrial Internet of things (IIoT). Some energy-efficient time synchronization schemes that achieve high accuracy have been proposed recently. However, some unsynchronized nodes namely isolated nodes exist in the schemes. To deal with the problem, this paper presents R-Sync, a robust time synchronization scheme for IIoT. We use a pulling timer to pull isolated nodes into synchronized networks whose initial value is set according to level of spanning tree. Then, another timer is set up to select backbone node and its initial value is related to the distance to parent node. Moreover, we do experiments based on simulation tool NS-2 and testbed based on wireless hardware nodes. The experimental results show that our approach makes all the nodes get synchronized and gets the better performance in terms of accuracy and energy consumption, compared with three existing time synchronization algorithms TPSN, GPA, STETS.

As wind energy continues to expand to new frontiers in terms of the location, number, and size of wind turbines, the industry has begun to seek smarter operations and management solutions. Wireless sensing nodes could provide a low-cost platform to support a variety of applications designed to reduce the levelized cost of energy and increase the safety of wind turbines. However, a wireless sensor node deployed on a wind turbine blade would have an extremely limited energy supply. To combat this limitation, we present BladeMAC, a new MAC-layer protocol designed for sensor nodes deployed on rotating wind turbine blades. BladeMAC overcomes a unique cyclical channel problem to allow a sensor node attached to a rotating blade to opportunistically and efficiently offload its data to a sink node attached to the turbine tower. We have implemented and evaluated BladeMAC using Contiki OS and the Cooja simulation tool. We present results showing that BladeMAC effectively deals with the cyclical channel problem at a wide range of data arrival intervals, and that BladeMAC is insensitive to rotation speed and rotation speed fluctuations.

Barrier coverage is a natural application of sensor networks in which sensors are deployed to detect intruders or protect crucial resources. In this paper, we consider a hybrid sensor network with a two-phase deployment, in which less-expensive static sensors are first randomly deployed in an area, and then more-expensive mobile sensors are deployed to fill coverage gaps. We use a probabilistic model to take into account the practical constraints of detection probability and false positives. We propose an iterative scheme that finds a sensor deployment strategy that minimizes the total sensor cost. Our scheme makes use of a graph transformation and includes speed-up strategies. We present simulation results that verify the correctness of the proposed scheme and demonstrate the effectiveness of the speed-up strategies.

Barrier coverage is an important application of sensor networks to prevent intruders from crossing the protected region. In this paper, we study the problem of building a strong horizontal barrier with mobile sensors while minimizing the maximum sensor moving distance. An efficient binary-search based scheme is proposed to optimize the barrier location and sensors' final positions along the barrier. Performance and efficiency of our scheme are evaluated using simulation results.

Oblivious RAM (ORAM) is a security-provable approach for protecting clients' access patterns to remote cloud storage. Recently, numerous ORAM constructions have been proposed to improve the communication efficiency of the ORAM model, but little attention has been paid to the storage efficiency. The state-of-the-art ORAM constructions have the storage overhead of O(N) or O(N log N) blocks at the server, when N data blocks are hosted. To fill the blank, this paper proposes a storage-efficient ORAM (SE-ORAM) construction with configurable security parameter λ and zero storage overhead at the server. Extensive analysis has also been conducted and the results show that, SE-ORAM achieves the configured level of security, introduces zero storage overhead to the storage server (i.e., the storage server only storages N data blocks), and incurs O(log N) blocks storage overhead at the client, as long as λ ≥ 2 and each node on the storage tree stores 4 log N or more data blocks.

We propose a unique Dynamic Sensing Scheduling (DSS) scheme to prolong the lifetime of a sensor network. Different from most existing works, we study the sensor network lifetime under two practical requirements: sensing coverage and network connectivity. A sensor node is considered critical if its depletion of energy would cause either a violation of the sensing coverage requirement (specified by the application) or a disconnection of the routing tree. The key idea of DSS is to adjust the sensing duties of sensor nodes according to their nodal lifetime as well as their criticality. Under this design principle, DSS schedules more sensing duties to non-critical nodes (even at the cost of losing them more quickly) so that critical nodes may stay alive for a longer period of time, thus extending the network lifetime. DSS adjusts the sensing duties between neighboring nodes only, and is a distributed and lightweight solution. Simulation results show that DSS performs well under various network setups, close to a theoretical upper bound.

Barrier coverage is a fundamental application for wireless sensor networks. In this paper, we consider a practical probabilistic sensing model and propose an iterative scheme, called BaCo, to provide strong barrier coverage under this model, with the objective of minimizing the number of active sensors. Moreover, we build the barrier under practical constraints of minimum detection probability and maximum false alarm probability. We use simulations to show that BaCo converges quickly and achieves better results than previous work while also bounding the system false alarm probability.

This paper presents DiVA, a novel hybrid range-free and range-based acoustic source localization scheme that uses an ad-hoc network of microphone sensor nodes to produce an accurate estimate of the source's location in the presence of various real-world challenges. DiVA uses range-free pairwise comparisons of sound detection timestamps between local Voronoi neighbors to identify the node closest to the acoustic source, which then estimates the source's location using a constrained range-based method. Through simulation and experimental evaluations, DiVA is shown to be accurate and highly robust, making it practical for real-world applications.

Many small businesses and public areas offer free Wi-Fi access, but may wish to restrict network access only to their customers or patrons inside the physical property. Unfortunately, due to the nature of wireless networks, this is difficult to accomplish. We develop and implement CLAC, a Crowdsourced Location aware Access Control scheme using physical layer information to address this challenge. It crowdsources both channel state information (CSI) and received signal strength (RSS) of already validated users to classify future users. We propose and use two CSI metrics in CLAC: CSI Cross-Antenna Stability Metric and CSI Cross-Frame Stability Metric, which summarize well the spatial and temporal CSI characteristics respectively. CLAC is evaluated in an office and a classroom. Evaluation results show that CLAC performs well in both environments, allowing most valid users inside the area to access the network, while the chance that invalid users outside the boundary may access the network is small.

This paper proposes a pairwise SIR-based random sequential scheduling algorithm for wireless D2D communications. We derive an upper and a lower bound on the number of scheduled links by identifying the equivalence between the proposed algorithm and the Random Sequential Adsorption (RSA) process in physics. We then study the optimal SIR threshold, which is a key parameter in the proposed algorithm, for achieving the maximum sum rate. We finally extend the algorithm when a minimum SIR is required at each scheduled link. From the simulations, we observe that the proposed algorithm can achieve 24% higher sum rate compared with the aggregate SIR-based scheduling algorithm.

In recent years, Wi-Fi has seen extraordinary growth; however, due to the cost, performance and security issues, many Wi-Fi hotspot owners would like to restrict the network access only to individuals inside the physical property. Unfortunately, due to the nature of wireless, this is difficult to accomplish, especially with the off-the-shelf omni-antenna devices. In this work, we develop and implement CLaWa, a Crowdsourced Location Aware Wi-Fi Access Control scheme to address this challenge. Our system is based on observations of differing characteristics of physical layer information across physical boundaries such as walls and corners. CLaWa crowdsources both channel state information (CSI) and received signal strength (RSS) of already validated users to classify future users. We have also selected an appropriate machine learning algorithm for CLaWa. Evaluation results show that CLaWa can identify the boundary around a given area precisely, thus granting network access only to users inside the area while not validating users outside the boundary. Compared to indoor localization schemes, CLaWa is a lightweight solution which does not require expensive localization operations.

This paper presents DiVA, a new acoustic source localization scheme that uses an ad-hoc network of microphone sensor nodes to produce an accurate estimate of the source's location. DiVA uses pairwise comparisons of sound detection timestamps between local Voronoi neighbors to identify the node closest to the acoustic source and then estimates the source's location. The scheme improves on the state of the art by effectively dealing with anchor nodes' position error, time stamp measurement error and time synchronization error in real world conditions. Through simulation and experimental evaluations, DiVA is shown to be more robust than existing solutions under different error conditions.

Recent efforts in applying anycast techniques to duty-cycled wireless sensor networks have shown promising results in terms of reduced delay and energy consumption. This paper further increases the energy savings by introducing EDAD, an energy-centric cross-layer data collection protocol designed for anycast communications in asynchronously duty-cycled wireless sensor networks. EDAD uses a new anycast routing metric, EEP, that minimizes the expected energy consumed along the path of a packet and automatically adapts to network settings. Simulation results show that EDAD consumes less energy than similar existing protocols, while maintaining a comparable delay and high delivery rate.

Barrier coverage is an important application of sensor networks. This paper studies how to build a strong barrier with mobile sensors in which the maximum moving distance of sensors is minimized. Our work differs from others in the way the y-coordinate of the barrier is determined. We optimize the y-coordinate of the barrier instead of fixing it a priori. An efficient algorithm is proposed, in which the search space of the y-coordinate of the barrier is first discretized and then searched over iteratively. In the theoretical worst case, O(N4) iterations may be needed to find the optimal barrier location, where N is the number of sensors, but in practice, our algorithm requires less than O(N2) iterations, as confirmed in simulation.

As outsourcing data to remote storage servers gets popular, protecting user's pattern in accessing these data has become a big concern. ORAM constructions are promising solutions to this issue, but their application in practice has been impeded by the high communication and storage overheads incurred. Towards addressing this challenge, this paper proposes a segmentation-based ORAM (S-ORAM). It adopts two segment-based techniques, namely, piece-wise shuffling and segment-based query, to improve the performance of shuffling and query by factoring block size into design. Extensive security analysis proves that S-ORAM is a highly secure solution with a negligible failure probability of O(N-log N). In terms of communication and storage overheads, S-ORAM outperforms the Balanced ORAM (B-ORAM) and the Path ORAM (P-ORAM), which are the state-of-the-art hash and index based ORAMs respectively, in both practical and theoretical evaluations. Particularly under practical settings, the communication overhead of S-ORAM is 12 to 23 times less than B-ORAM when they have the same constant-size user-side storage, and S-ORAM consumes 80% less server-side storage and around 60% to 72% less bandwidth than P-ORAM when they have the similar logarithmic-size user-side storage.

A sensor network deployed for long-term monitoring shall sustain meanwhile provide as much useful sensory information (i.e., as high network utility) as possible. We propose a JCRA (Joint Charging and Rate Allocation) scheme to maximize the network utility while satisfying the network sustainability requirement. JCRA is designed based on the observation that the energy repository of a sensor node is co-affected by three factors: uncontrollable ambient energy harvesting, controllable wireless charging, and controllable sensory data generation. It jointly controls the charging, communication, and sensing activities while guaranteeing non-empty energy repositories at all sensor nodes. JCRA is a low-cost solution, as neighbor sensor nodes collaborate with each other to adjust their data generation rates in a distributed manner, based on the status of ambient energy supply and the wireless charging schedule planned by the base station. Extensive simulations have verified the effectiveness of JCRA in achieving the stated goals: JCRA can always guarantee network sustainability, while the achieved network utility is close to that by a centralized (1 - ϵ) approximate solution to the same optimization problem, in most simulation settings.

This paper proposes JAM, a Joint Aggregation and MAC design, to improve the sensor network lifetime under the end-to-end delay constraint. The key idea is to adjust both network traffic (via data aggregation) and communication overhead (via duty-cycled MAC) in a holistic manner at each individual node as well as between neighbors. As a result, JAM extends the sensor network lifetime more efficiently and effectively than the state-of-the-art solutions while guaranteeing the desired delay bound and achieving a lower level of average nodal power consumption. JAM is a lightweight and distributed solution with limited control information exchanged between neighbors only, which makes it deployable in practical sensor networks. Extensive ns-2 simulation and TinyOS experiment results are used to demonstrate the effectiveness of JAM in prolonging the network lifetime.

We present a novel holistic approach (called I2C - Intra-route and Inter-route Coordination) to prolong the sensor network lifetime under the end-to-end delivery delay constraint. I2C is composed of two lifetime balancing modules: (i) the IntraRoute Coordination module that allows the nodes on the same route to balance their nodal lifetimes through adjusting the MAC behaviors collaboratively; (ii) the Inter-Route Coordination module that balances the nodal lifetimes across different routes via adjusting the communication routes. Different from existing works which conduct either intra-route or inter-route lifetime balancing, or a simple combination of the two, I2C leverages the advantages of both techniques with a sophisticated design that emphasizes the awareness and collaboration between two modules. Thus, I2C is able to prolong the network lifetime much more effectively than the state-of-the-art solutions, while guaranteeing the desired delay bound and maintaining a similar level of network power consumption. This has been demonstrated with extensive ns-2 simulation and TinyOS experiment results.

Providing adequate Wi-Fi services to meet user demand in densely populated environments has been a fundamental challenge for Wi-Fi networks. In this paper, we explore the emerging OAMI (One-AP-Multiple-Interface) architecture and propose a unique solution called SAP (Smart Access Point). SAP takes full advantage of the OAMI architecture to provide seamless handoff experience to users, while smartly balancing the network load across multiple interfaces based on users' time-varying traffic load conditions. Moreover, we define a Traffic Fulfillment (TF) performance metric to quantify the user experience and aid in association scheduling. SAP is an AP-only solution that requires trivial network modifications and is backwards compatible with legacy 802.11 stations. We have implemented SAP in the MadWifi device driver and demonstrated its effectiveness via experiments.

This paper proposes LBA, a lifetime balanced data aggregation scheme for asynchronous and duty cycle sensor networks under an application-specific requirement of end-to-end data delivery delay bound. In contrast to existing aggregation schemes that focus on reducing the energy consumption and extending the operational lifetime of each individual node, LBA has a unique design goal to balance the nodal lifetime and thus prolong the network lifetime more effectively. To achieve this goal in a distributed manner, LBA adaptively adjusts the aggregation holding time between neighboring nodes to balance their nodal lifetime; as such balancing take place in all neighborhoods, nodes in the entire network can gradually adjust their nodal lifetime towards the globally balanced status. Experimental studies on a sensor network testbed shows that LBA can achieve the design goal, yield longer network lifetime than other non-adaptive and nodal lifetime-unaware data aggregation schemes, and approach the theoretical upperbound performance, especially when nodes have highly different nodal lifetime.

Channel asymmetry and high fluctuation of channel conditions are two salient characteristics of wireless channels in mobile environments. Therefore, when using IEEE 802.11 devices in mobile environments, it is critical to have an effective rate adaptation scheme that can deal with these issues. In this paper, we propose a practical rate adaptation scheme called Rate Adaptation in Mobile environments (RAM) and implement it in the MadWifi device driver. RAM uses a receiver-based approach to handle channel asymmetry and a conservative SNR prediction algorithm to deal with high channel fluctuation. More importantly, RAM allows the receiver to convey the feedback information to the transmitter in a creative manner via ACK transmission rate variation, which does not require changes to the device firmware and hence is implementable at the device driver level. In addition, RAM adopts an effective scheme to guarantee that RAM-based and legacy IEEE 802.11 devices can interoperate with each other. The effectiveness of RAM is demonstrated via in-depth experimental evaluation in indoor static and mobile environments as well as outdoor vehicular environments.

With the proliferation of Wi-Fi equipped mobile devices such as smart phones, it becomes even more important to design and implement effective power management schemes for Wi-Fi interfaces so that the battery lifetime can be prolonged. In this paper, we propose an enhancement to the default 802.11 Power Save Mode (PSM), called M-PSM, which exploits additional power-saving opportunities by considering user mobility and detailed traffic condition when making the sleep/wakeup schedules for Wi-Fi interfaces. We have implemented M-PSM in the Madwifi device driver and demonstrated its effectiveness via experiments and trace-based simulations.

The emerging wireless charging technology creates a controllable and perpetual energy source to provide wireless power over distance. Schemes have been proposed to make use of wireless charging to prolong the sensor network lifetime. Unfortunately, existing schemes only passively replenish sensors that are deficient in energy supply, and cannot fully leverage the strengths of this technology. To address the limitation, we propose J-RoC - a practical and efficient Joint Routing and Charging scheme. Through proactively guiding the routing activities in the network and delivering energy to where it is needed, J-RoC not only replenishes energy into the network but also effectively improves the network energy utilization, thus prolonging the network lifetime. To evaluate the performance of the J-RoC scheme, we conduct experiments in a small-scale testbed and simulations in large-scale networks. Evaluation results demonstrate that J-RoC significantly elongates the network lifetime compared to existing wireless charging based schemes.

This paper presents a new receiver-initiated sensor network MAC protocol, called CyMAC, which has the following unique features. It reduces the idle listening time of sensor nodes via establishing rendezvous times between neighbors, provides the desired relative delay bound guarantee for data delivery services via planning the rendezvous schedules carefully, and adjusts the sensor nodes' duty cycles dynamically to the varying traffic condition. More importantly, CyMAC achieves the above goals without requiring time synchrony between sensor nodes. We have implemented and evaluated CyMAC in both TinyOS and the ns-2 simulator. Experimental and simulation results show that, comparing with RI-MAC - a state-of-the-art sensor network MAC protocol, CyMAC can always guarantee the desired delay bound for data delivery services and yields a lower duty cycle under reasonable delay requirements.

How to reduce the handoff delay and how to make appropriate handoff decisions are two fundamental challenges in designing an effective handoff scheme for 802.11 networks to provide seamless and satisfactory data roaming services to mobile users. In this paper, we propose a unique fast handoff scheme called HaND (Handoff with Null Dwell time). HaND adopts a novel zero-channel-dwell-time architecture which leverages on the communication backbone between APs to relay the information about wireless channels, and allows the AP (rather than the station) to make appropriate handoff decisions aiming at providing fair service satisfaction to all stations. HaND is a software-only solution and compatible with the 802.11 standard without modifying the 802.11 protocol or introducing new wireless frames. We have implemented it in the Madwifi device driver and demonstrated its effectiveness via experiments.

Deploying wireless sensor networks to provide guaranteed barrier coverage is critical for many sensor networks applications such as intrusion detection and border surveillance. To reduce the number of sensors needed to provide guaranteed barrier coverage, we propose multi-round sensor deployment which splits sensor deployment into multiple rounds and can better deal with placement errors that often accompany sensor deployment. We conduct a comprehensive analytical study on multi-round sensor deployment and identify the tradeoff between the number of sensors deployed in each round of multi-round sensor deployment and the barrier coverage performance. Both numerical and simulation studies show that, by simply splitting sensor deployment into two rounds, guaranteed barrier coverage can be achieved with significantly less sensors comparing to single-round sensor deployment. Moreover, we propose two practical solutions for multi-round sensor deployment when the distribution of a sensor's residence point is not fully known. The effectiveness of the proposed multi-round sensor deployment strategies is demonstrated by numerical and simulation results.

The emerging wireless charging technology is a promising alternative to address the power constraint problem in sensor networks. Comparing to existing approaches, this technology can replenish energy in a more controllable manner and does not require accurate location of or physical alignment to sensor nodes. However, little work has been reported on designing and implementing a wireless charging system for sensor networks. In this paper, we design such a system, build a proof-of-concept prototype, conduct experiments on the prototype to evaluate its feasibility and performance in small-scale networks, and conduct extensive simulations to study its performance in large-scale networks. Experimental and simulation results demonstrate that the proposed system can utilize the wireless charging technology effectively to prolong the network lifetime through delivering energy by a robot to where it is needed. The effects of various configuration and design parameters have also been studied, which may serve as useful guidelines in actual deployment of the proposed system in practice.

Recently, there has been an increasing interest in developing 60 GHz wireless personal area networks (WPANs) for short-range high-speed wireless communications. Both industrial and standardization organizations such as IEEE 802.15.3c and IEEE 802.11ad are making considerable efforts to bring the very high data rate (up to several Gbps) WPANs into reality. In this work, we develop an NS-2 extension for simulating 60 GHz WPANs, based on which we conduct a comprehensive simulation study to investigate the impacts of antenna directivity and CSMA/CA operation modes on the throughput of 60 GHz WPANs. Observations from extensive simulation results provide valuable insights and guidelines in designing future MAC schemes for 60 GHz WPANs with directional antennas.

With in-network sensor data storage and query, storage nodes are responsible for storing the data collected by sensor nodes and answering queries from users. Thus, without proper protection for data types and user queries, compromise of storage nodes and/or sensor nodes may reveal sensitive information about the sensed environment as well as users' private interests and query patterns. In this paper, we explore trade-offs between privacy, computation overhead, communication overhead, network flexibility and network complexity, and propose ElliPS (Elliptic curve based Privacy Scheme) to provide joint protection on data type privacy and query privacy in the presence of sensor node compromise, storage node compromise, or under collusive attacks by compromised sensor nodes and storage nodes together. Extensive analysis and simulation are conducted to verify the security properties and efficiency of the proposed scheme.

Sensor networks have been deployed for many barrier coverage applications such as intrusion detection and border surveillance. In these applications, it is critical to operate a sensor network in an energy-efficient manner so the barrier can be covered with as few active sensors as possible. In this paper, we study barrier information coverage which exploits collaborations and information fusion between neighboring sensors to reduce the number of active sensors needed to cover a barrier and hence to prolong the network lifetime. Moreover, we propose a practical solution to identify the barrier information coverage set which can information-cover the barrier with a small number of active sensors. The effectiveness of the proposed solution is demonstrated by numerical and simulation results.

Mobile devices like laptops, iPhones and PDAs are highly susceptible to theft in public places like airport terminal, library and cafe. Moreover, the exposure of sensitive data stored in the mobile device could be more damaging than the loss of device itself. In this work, we propose and implement a

Channel asymmetry and high fluctuation of channel conditions are two salient characteristics of wireless channels in mobile environments. Therefore, when using IEEE 802.11 devices in mobile environments such as vehicular networks, it is critical to have an effective rate adaptation scheme that can deal with these issues. In this paper, we propose a practical rate adaptation scheme called RAM (rate adaptation in mobile environments) and implement it in the Madwifi device driver. RAM uses a receiver-based approach to handle channel asymmetry and a conservative SNR prediction algorithm to deal with high channel fluctuation. More importantly, RAM allows the receiver to convey the feedback information in a creative manner via ACK transmission rate variation, which does not require changes to the device firmware and hence is implementable at the device driver level. The effectiveness of RAM is demonstrated through experimental evaluation in indoor static and mobile environments and outdoor vehicular environments, as well as simulation study based on SNR traces collected from the experiments.

Wireless Mesh Network (WMN) has been recognized as one of the promising technologies to provide wireless broadband access. In addition to the multi-radio multi-channel network architecture often seen in WMNs, employment of directional antennas on each mesh node could further improve the system throughput via alleviating the interference between nearby nodes thus allowing more concurrent transmissions in the network. In this paper, we describe a novel algorithm to produce joint decisions on routing and channel assignment with practical implementation considerations for WMNs with directional antennas. In particular, we formulate this joint optimization problem as a Mixed Integer Programming (MIP) problem with all practical considerations modeled explicitly as MIP constraints. For example, our scheme only considers dual-path routes and one- to-one association between access points and gateway nodes, so as to facilitate its deployment with commercial wireless networking devices such as IEEE 802.11 compliant devices. The objective is to maximize the aggregate system throughput and to provide fair and satisfactory services to all access points. Simulation results show that our scheme (i.e., the solution to the MIP problem) fully exploits the multi-radio multi-channel network architecture and directional antennas in WMNs, and is able to achieve the design objectives with significantly reduced implementation complexity.

Quality of object detection and network lifetime hold critical importance to many sensor network applications such as military surveillance. Unfortunately, improving one of these aspects comes at the expense of the other. In this paper, based on the probabilistic sensing model, we propose a novel framework for object detection in sensor networks, called DeCODe (on-demand framework for collaborative object detection), which provides a desired object detection performance (characterized in terms of detection probability and false detection probability), while attempting to prolong the network lifetime. The design of DeCODe is motivated by a counterintuitive observation that simple collaboration among active sensors indeed degrades the object detection performance. By contrast, each active sensor in DeCODe can trigger its neighboring inactive sensors to participate in the detection process in an on-demand fashion, so as to achieve the same low false detection probability while increasing the probability of detection. The effectiveness of the proposed DeCODe framework is supported by theoretical analysis and simulation-based validation.

The overlay-based network architecture has been recognized as an effective way to deal with the funneling effect in sensor networks, where sensors closer to the sink are usually responsible for relaying more network traffic. Such funneling effect is particularly harmful when the number of sensors in the network is vast. In an overlay-based sensor network, a special type of resource-rich multi-radio mobile wireless devices (we call them syphons) are deployed along with sensors. Syphons form an overlay network and help nearby sensors relay their data to the sink via the overlay network, thus mitigating the funneling effect. In this paper, we study one of the fundamental challenges in overlay-based sensor networks: syphon deployment problem, i.e., how to deploy a limited number of syphons to cover a vast sensing field while maintaining the connectivity and balanced loads among them. We propose a novel sensor-aided overlay deployment and relocation (SODaR) protocolas a possible solution. The key idea is to take advantage of sensors' assistance and to relocate syphons by circling them around the sink in an orderly manner until all syphons are connected. Simulation results show that, with SODaR, syphons are able to self-form and self-maintain a connected tree structure which provides excellent load balancing among syphons with modest message and movement overhead.

Many sensor networks are deployed for the purpose of covering and monitoring a particular region, and detecting the object of interest in the region. In this paper, based on the probabilistic sensing model, we conduct comprehensive analytical and simulation studies on collaborative information coverage and object detection in wireless sensor networks. More specifically, we first define point information coverage and based on that we define p-coverage as a measure of the coverage performance for a randomly-deployed wireless sensor network. Then, we investigate the coverage and object detection performances of several simple decision fusion-based collaborative mechanisms and find that simple collaborations among active sensors indeed degrade the coverage performance due to the requirement of maintaining the target false detection probability. This motivates us to develop an on-demand collaborative framework for object detection, whose effectiveness is supported by detailed theoretical analysis and simulation-based validation. Finally, we investigate the energy efficiency performance of our proposed framework and identify the trade-offs among various system parameters in network power consumption.

Today, IEEE 802.11 Wireless LAN (WLAN) has become a prevailing solution for broadband wireless Internet access while Transport Control Protocol (TCP) is the dominant transport protocol in the Internet. It is known that, in an infrastructure-based WLAN with multiple stations carrying long-lived TCP flows, the number of stations that are actively contending to access the channel is very small. Therefore, the aggregate TCP throughput is basically independent of the total number of stations. This phenomenon is due to the closed-loop nature of TCP flow control and the bottleneck downlink (i.e., AP-to-station) transmissions in infrastructure-based WLANs. In the emerging Enhanced Distributed Channel Access (EDCA)-based IEEE 802.11e WLANs, with a proper configuration, packet congestion at the bottleneck downlink could be alleviated since the AP and stations are allowed to use different channel access parameters. In this paper, we first conduct a rigorous, comprehensive analysis of the TCP dynamics over the 802.11e EDCA. Then, the effects of minimum contention window sizes (of both AP and stations) on the aggregate TCP throughput are evaluated via mathematical analysis and simulation. We also show that the best TCP aggregate throughput performance can be achieved via AP’s contention-free access for downlink packet transmissions. Finally, some of the simplifying assumptions used in our mathematical model are evaluated via simulation, and results show that our model is reasonably accurate when the wireline delay is small and the packet loss rate is low.

Collision awareness has been recognized as a critical component for effective rate adaptation schemes. Recently, several collision-aware rate adaptation schemes have been proposed for IEEE 802.11 Wireless LANs (WLANs), such as CARA (Collision Aware Rate Adaptation) and RRAA (Robust Rate Adaptation Algorithm). These schemes are able to distinguish between channel- error-induced and collision-induced frame losses via adaptive and appropriate usage of RTS/CTS; hence the multiple transmission rates provided by 802.11 physical layers (PHYs) may be fully exploited. In this paper, we propose a unique collision-aware rate adaptation scheme, called PBRA (Probabilistic-Based Rate Adaptation). The key ideas of PBRA include (i) probabilistic-based adaptive usage of RTS/CTS, which is in direct contrast to trial- based RTS Probing in CARA and window-based adaptive usage of RTS/CTS in RRAA; and (ii) threshold-based rate adjustment, which allows a station to make more appropriate rate adjustment decisions, thanks to its accurate estimation of the channel-error-induced frame loss ratio. Simulation results show that PBRA clearly outperforms all other testing schemes (including CARA and RRAA), particularly in random topology networks with fading wireless channels.

Wireless sensor networks have been deployed for various critical monitoring applications in hostile environments such as monitoring the concentration levels of hazardous gas species in a battle field. Due to the sensitivity of such applications, it becomes mandatory to record the transient variations in the phenomenon, and take corrective actions, if necessary. At the same time it is important to shield the network from false data injection by adversaries who intend to disrupt the functioning of the system. While many schemes exist to prevent false data injection, they are counterproductive to preserving the transient observations. We devise a robust statistical scheme to monitor transient phenomenon while being immune to false data injection attacks. The key idea of our scheme is to require each sensor node to report a statistical digest of recent sensed readings in addition to the current reading; then inter-sensor statistical tests are designed and utilized to help preserve transient data while restricting the impact of false data injection significantly. Detailed theoretical analysis and in-depth simulations are presented to corroborate our scheme.

Today, most wireless hotspots deploy multiple APs (Access Points) to improve the network performance and to provide fair and satisfactory services to clients. However, without a well-defined fairness objective function and the corresponding service provision schemes, the desired improvements may not be achieved. On the other hand, it has been realized that existing fairness notions proposed for single-AP wireless hotspots exhibit various performance anomalies in multi-AP wireless hotspots:bandwidthanomalywith Bandwidth-based Fairness (BbF) andassociationanomalywith Timeshare-based Fairness (TbF). To answer this challenge, we propose a new fairness notion, called the Fulfillment-based Fairness (FbF), for multi-AP wireless hotspots. It emphasizes allocation of bandwidth to clients in proportion to their respective maximum attainable bandwidth allocations. Extensive simulation shows that FbF outperforms BbF and TbF in terms of aggregate system throughput by up to 40% and 70%, respectively. It performs particularly well when the clients present a high degree of transmission rate diversity and/or in the presence of bottleneck clients that can only communicate with a single AP at low transmission rates.

This paper considers the energy-conservation problem in multi-rate multi-power-level wireless local area networks (WLANs). This problem is addressed from a unique angle — the system-level fair-ness which is significantly different from most of current research that focuses on improving the performance of each individual wire-less station. To emphasize fair energy-consumption among con-tending stations, we introduce a new fairness notion, called energy-conservation fairness, in contrast to the conventional throughput fairness and airtime fairness. Another contribution of the paper is an energy-efficient airtime allocation scheme, which allocates air-time shares to contending stations in such a way that the combined airtime and energy-conservation fairness is achieved. Our simu-lation results show that, when the energy-conservation fairness is considered, both aggregate system throughput and overall system energy-efficiency can be improved significantly with all contend-ing stations consuming a similar amount of energy.

Numerous schemes have been proposed to facilitate data collection and provision in sensor networks, among which the Data-Centric Storage (DCS) scheme is an energy-efficient solution and a popular choice for many sensor network applications. However, since each sensor node in the DCS system knows the locations of all storage nodes, the DCS system is extremely vulnerable to security attacks as a single compromised sensor node will expose all the storage locations to the adversary. To address this problem, we propose a randomized storage concealment scheme along with a supplementary storage migration scheme. In the randomized storage concealment scheme, sensor nodes cooperate to forward data towards the storage nodes without keeping explicit storage locations; instead, each sensor node only maintains the IDs of its randomly-picked next-hop nodes towards the storage nodes. This scheme increases the difficulty significantly for the adversary to derive the storage locations. Nevertheless, the protection provided by this scheme degrades gradually as more and more sensor nodes are compromised. Hence, we further introduce a storage migration scheme to supplement the randomized storage concealment scheme, which directs the storage duties to migrate periodically among sensor nodes. Extensive analysis and simulations are conducted to show that the proposed schemes can effectively protect the storage location privacy with modestly added overhead.

Today’s IEEE 802.11 WLANs (Wireless LANs) provide multiple transmission rates so that different rates can be exploited in an adaptive manner depending on the underlying channel condition in order to maximize the system performance. Many rate adaptation schemes have been proposed so far while most (if not all) of the commercial devices implement a simple open-loop rate adaptation scheme (i.e., without feedback from the receiver), called ARF (Automatic Rate Fallback) due to its simplicity. A key problem with such open-loop rate adaptation schemes is that they do not consider the collision effect, and hence, malfunction severely when many transmission failures are due to collisions. In this paper, we propose a novel rate-adaptation scheme, called CARA (Collision-Aware Rate Adaptation). The key idea of CARA is that the transmitter station combines adaptively the Request-to-Send/Clear-to-Send (RTS/CTS) exchange with the Clear Channel Assessment (CCA) functionality to differentiate frame collisions from frame transmission failures caused by channel errors. Therefore, compared with other open-loop rateadaptation schemes, CARA is more likely to make the correct rate adaptation decisions. Through extensive simulation runs, we evaluate our proposed scheme to show that our scheme yields significantly higher throughput performance than the existing schemes

The multi-radio multi-channel network architecture has been recognized as one of the promising approaches to improve the system throughput of IEEE 802.11-based multi-hop wireless networks. In this paper, we study the routing issues under this new network architecture and propose a new routing metric, called AETD (adjusted expected transfer delay). The key idea of AETD is to consider both delay and jitter of candidate routes when making the routing decision. It is designed to select a route on which hops operating on the same frequency channel are separated as far as possible. This way, interference and channel contention may be minimized along the selected route and the system throughput may be improved. Our in-depth simulation shows that the proposed AETD routing metric outperforms several other routing metrics significantly, including HOP (hop count), ETX (cumulative expected transmission count), CETT (cumulative expected transmission time), and WCETT (weighted cumulative expected transmission time)

Recently, there has been extensive research interest in increasing the data rates supported by IEEE 802.11 wireless LANs. For this purpose, IEEE 802.11 formed Task Group N to develop specifications for high-data-rate wireless LANs. The medium access in the legacy 802.11 is not scalable as it exhibits a large control overhead when the data rates increase and a large collision rate when the number of stations is large. In this paper, we introduce a group-based medium access control (GMAC) protocol for wireless LANs with high data rates and a large number of stations. With GMAC, stations are divided into groups that are free of hidden nodes. Each group has a leader and only group leaders contend using CSMA/CA. Once a group leader wins the contention, it reserves transmission time for all the stations in its group and issues a polling packet specifying the group's schedule. Stations in the same group transmit after their leader according to the polling packet. GMAC achieves significant throughput gain over DCF by reducing the collision rate and the control overhead. Simulation studies show that GMAC maintains a high throughput as the data rates and the number of stations increase

The mechanism to select one out of multiple available transmission rates at a given time is referred to as link adaptation. The effectiveness of a link adaptation scheme depends on how fast it can respond to the wireless channel variation. In this paper, we propose a truly-adaptive fast-responsive link adaptation scheme for IEEE 802.11 WLAN (wireless LAN). The key idea is to direct the transmitter station's rate-increasing attempts in a controlled manner such that the responsiveness of the link adaptation scheme can be guaranteed with minimum number of rate-increasing attempts. Since our scheme allows the transmitter station to make the link adaptation decision solely based on its local acknowledgment information, it does not require any change to the current 802.11 standard, thus facilitating its deployment with existing 802.11 devices. Our in-depth simulation shows that our scheme yields significantly higher throughput than other existing schemes including single-rate schemes, the ARF (auto rate fallback) scheme and its variants, in various fading channels.

Static PSM (power-saving mode) schemes employed in the current IEEE 802.11 implementations could not provide any delay-performance guarantee because of their fixed wakeup intervals. In this paper, we propose a smart PSM (SPSM) scheme, which directs a wireless station to sleep/wake up according to an "optimal" sequence, such that the desired delay performance is guaranteed with minimum energy consumption. Instead of constructing the sequence directly, SPSM takes a unique two-step approach. First, it translates an arbitrary user-desired delay performance into a generic penalty function. Second, it provides a generic algorithm that takes the penalty function as the input and produces the optimal station action sequence automatically. This way, the potentially-complicated energy-consumption-minimization problem subject to delay-performance constraints is simplified and solved systematically. Our simulation results show that, with a two-stair penalty function, SPSM achieves delay performance similar to the BSD (bounded slowdown) protocol under various scenarios, but always with less energy consumption, thanks to its capability to adapt to changes in the response-time distribution. Moreover, because of SPSM's two-step design feature, it is more flexible than BSD in the sense of being able to meet arbitrary user-desired delay requirement, e.g., providing soft delay-bound guarantees with power penalty functions.

Reducing the energy consumption by wireless communication devices is perhaps the most important issue in the widely-deployed and exponentially-growing IEEE 802.11 Wireless LANs (WLANs). TPC (Transmit Power Control) and PHY (physical layer) rate adaptation have been recognized as two most effective ways to achieve this goal. The emerging 802.11h standard, which is an extension to the current 802.11 MAC and the high-speed 802.11a PHY, will provide a structured means to support intelligent TPC.In this paper, we propose a novel scheme, called MiSer, that minimizes the communication energy consumption in 802.11a/h systems by combining TPC with PHY rate adaptation. The key idea is to compute offline an optimal rate-power combination table, and then at runtime, a wireless station determines the most energy-efficient transmission strategy for each data frame by a simple table lookup. Another key contribution of this paper is to provide a rigorous analysis of the relation among different radio ranges and TPC's effect on the interference in 802.11a/h systems, which justifies MiSer's approach to ameliorating the TPC-caused interference by transmitting the CTS frames at a stronger power level. Our simulation results show that MiSer delivers about 20% more data per unit of energy consumption than the PHY rate adaptation scheme without TPC, while outperforming single-rate TPC schemes significantly thanks to the excellent energy-saving capability of PHY rate adaptation.

The current IEEE 802.11 wireless LAN (WLAN) systems are unable to support real-time applications because the underlying contention-based MAC (medium access control) protocol causes unpredictable delays. In this paper, we present the implementation details of a new RT-WLAN device driver module, which extends the original Linux device driver for the popular Agere ORiNOCO cards to support soft real-time communications. To our best knowledge, this is the first effort in providing real-time support in the WLAN environment at the device driver level. By shifting the design focus from the MAC layer, which is normally hard-coded in the NIC (network interface card), to the device driver level, which is between the system kernel and the MAC layer, our scheme has a clear advantage. Users can simply replace the original ORiNOCO driver with RT-WLAN, and then enjoy the benefits of real-time communications without having to change the NIC firmware or re-compile the Linux kernel. RT-WLAN uses two separate queues for real-time and non-real-time traffic. The real-time queue is served according to the EDF (earliest-deadline-first) policy, while the non-real-time queue is served in a FIFO (first-in-first-out) manner. Besides, an adaptive traffic smoother is implemented in RT-WLAN to regulate bursty non-real-time traffic before they are injected into the network, thus giving higher priority to in-progress real-time transmissions. Experimental results show that the desired real-time support and service differentiation among multiple real-time sessions are achieved by using RT-WLAN.

In this paper, we demonstrate the energy-efficient point coordination function (PCF) operation of IEEE 802.11a wireless LAN (WLAN) via both transmit power control (TPC) and physical layer (PHY) rate adaptation. First, we derive the energy-consumption performance analytically for uplink data transmissions under the PCF. From the evaluation results, we observe that significant energy savings can be achieved by combining TPC with adaptive PHY rate selection. A key requirement for a transmitter to select the most energy-efficient combination of transmit power level and PHY rate is the knowledge of the path loss between the receiver and itself. We present a novel scheme for accurate path loss estimation in 802.11 WLAN. Results and conclusions presented in this paper can serve as a valuable guidance or reference for the design of future 5 GHz 802.11 WLAN systems.

Link adaptation to dynamically select the data transmission rate at a given time has been recognized as an effective way to improve the goodput performance of the IEEE 802.11 wireless local-area networks (WLANs). Recently, with the introduction of the new high-speed 802.11a physical layer (PHY), it is even more important to have a well-designed link adaptation scheme work with the 802.11a PHY such that its multiple transmission rates can be exploited. In this paper, we first present a generic method to analyze the goodput performance of an 802.11a system under the distributed coordination function (DCF) and express the expected effective goodput as a closed-form function of the data payload length, the frame retry count, the wireless channel condition, and the selected data transmission rate. Then, based on the theoretical analysis, we propose a novel MPDU (MAC protocol data unit)-based link adaptation scheme for the 802.11a systems. It is a simple table-driven approach and the basic idea is to preestablish a best PHY mode table by applying the dynamic programming technique. The best PHY mode table is indexed by the system status triplet that consists of the data payload length, the wireless channel condition, and the frame retry count. At runtime, a wireless station determines the most appropriate PHY mode for the next transmission attempt by a simple table lookup, using the most up-to-date system status as the index. Our in-depth simulation shows that the proposed MPDU-based link adaptation scheme outperforms the single-mode schemes and the autorate fallback (ARF) scheme-which is used in Lucent Technologies' WaveLAN-II networking devices-significantly in terms of the average goodput, the frame drop rate, and the average number of transmission attempts per data frame delivery.

Dependability of service (DoS) has become an important requirement for real-time applications, such as remote medical services, business-critical network meetings and command-and-control applications. The Dependable Real-Time Protocol (DRTP), in which each dependable real-time connection is realized with one primary and one or more backup channels, has been shown to be an effective way of providing DoS. How to route both primary and backup channels for each dependable real-time connection is of vital importance to the success of failure recovery and to overhead reduction in providing DoS. In this paper, we propose and evaluate three different schemes for routing the primary and backup channels of each dependable real-time connection. Specifically, we present methods based on link-state information and bounded flooding to discover routes for the primary and backup channels while satisfying the required quality of service (QoS). The costs of the link-state and flooding algorithms are reduced significantly by using the fact that the probability of success in failure recovery can be estimated with simple link-state information, and by bounding the flooded region within an ellipse with the two communication end-points as loci. Our in-depth simulations have shown that the proposed routing schemes are highly effective, providing a fault tolerance of 87% or higher with a network capacity overhead of less than 85%.

IEEE 802.11a is a new high-speed physical layer (PHY) defined for the 5 GHz U-NII bands as a supplement to the existing IEEE 802.11 wireless LAN (WLAN) standard. We give an overview of the IEEE 802.11a orthogonal frequency domain multiplexing (OFDM) PHY with eight different PHY rates as well as the distributed coordination function (DCF) of the IEEE 802.11 MAC, then derive the goodput performance analytically for peer-to-peer communication under the DCF. Based on the numerical results, we claim that link adaptation, which performs both dynamic fragmentation and PHY rate selection depending on the wireless channel condition between the transmitter and receiver, is an attractive way to improve the goodput performance of an IEEE 802.11a wireless LAN. Finally, we propose a system architecture to perform link adaptation.

In this paper, we investigate the transmission of H.263 video sequences over wireless networks with error recovery provided by a two-step adaptive hybrid ARQ scheme using RS codes. Each video frame is divided into data packets for transmission. For each packet transmission, by using a simple table-driven approach, the best RS code is selected from a given set of codes to minimize the transmission overhead. Further, an additional adaptation step is used to guarantee certain QoS requirement. Simulation results show that the proposed error recovery scheme outperforms the traditional single-code schemes and the single-step error recovery schemes thanks to its adaptability to both the wireless channel conditions and the actual frame loss events.