Optical wireless communication (OWC) has inherent location aware and spatial reuse advantages over RF-based technologies due to the Line-of-Sight (LoS) propagation of optical signals. Hence, OWC presents a fresh opportunity for effective and secure IoT connectivity and data transmission. However, most OWC systems design transmitter as a point source without considering its spatial diversity in data delivery in 3D space, which is not suitable for real-world mobile IoT connections among devices and users. In this paper, we design and implement HoloCube, which provides 3D optical IoT connections via software defined optical camera communication and Pepper's ghost effect. At the heart of the HoloCube design is multiple virtual 3D hollowed-out cubes with adaptive Spatial-Color Shift Keying (SCSK) modulation. Specifically, the virtual cube seen from various directions has constant structure but embeds different data over time. The cube's positioning elements provide double reference for both 3D reconstruction (spatial) and robust color decoding (spectral). Our comprehensive experiments demonstrate that HoloCube achieves practical 3D omnidirectional IoT connections with 70 Kbps goodput at 4 m in real-world indoor setting.

Optical wireless communication (OWC) shows great potential due to its broad spectrum and the exceptional intensity switching speed of LEDs. Under poor conditions, most OWC systems switch from complex and more error prone high-order modulation schemes to more robust On-Off Keying (OOK) modulation defined in the IEEE OWC standard. This paper presents LiFOD, a high-speed indoor OOK-based OWC system with fine-grained dimming support. While ensuring fine-grained dimming, LiFOD remarkably achieves robust communication at up to 400 Kbps at a distance of 6 meters. This is the first time that the data rate has improved via OWC dimming in comparison to the previous approaches that consider trading off dimming and communication. LiFOD makes two key technical contributions. First, LiFOD utilizes Compensation Symbols (CS) as a reliable side-channel to represent bit patterns dynamically and improve throughput. We firstly design greedy-based bit pattern mining. Then we propose 2D feature enhancement via YOLO model for real-time bit pattern mining. Second, LiFOD synchronously redesigns optical symbols and CS relocation schemes for fine-grained dimming and robust decoding. Experiments on low-cost Beaglebone prototypes with commercial LED lamps and the photodiode (PD) demonstrate that LiFOD significantly outperforms the state-of-the-art system with 2.1× throughput on the SIGCOMM17 data-trace.

Optical Camera Communication (OCC) appears as a promising technology to provide secure and pervasive wireless services with users' daily smart devices. Rolling shutter based modulations can improve the frequency response of the camera. This paper introduces a 2D Rolling Block (2DRB) based OCC modulation to use un-exploited spatial diversity to improve OCC's data rate for real-world applications. 2DRB outperforms traditional 1D strip based modulations. Using our 2DRB prototype with commercial devices, we show a significant data rate enhancement. We also discuss one promising real-world use case: indoor office integrated lighting and communication.

Optical wireless communication (OWC) shows great potential for high-speed communication due to its broad spectrum and the exceptional intensity switching speed of LEDs. Under poor conditions, most OWC systems switch from complex and more error prone high-order modulation schemes to the more robust On-Off Keying (OOK) modulation defined in the IEEE OWC standard. This paper presents LiFOD, a high-speed indoor OOK-based OWC system with fine-grained dimming support. While ensuring fine-grained dimming, LiFOD remark-ably achieves robust communication at up to 400 Kbps at a distance of 6 meters. This is the first time that the data rate has improved via OWC dimming in comparison to the previous approaches that consider trading off dimming and communication. LiFOD makes two key technical contributions. First, LiFOD utilizes Compensation Symbols (CS) as a reliable side-channel to represent bit patterns dynamically and improve throughput. Second, LiFOD synchronously redesigns optical symbols and CS relocation schemes for fine-grained dimming and robust decoding. Experiments on low-cost Beaglebone prototypes with commercial LED lamps and the photodiode (PD) demonstrate that LiFOD significantly outperforms the state-of-art system with at least 2.1x throughput on the SIGCOMM17 data-trace.

Large volumes of data are being generated daily from IoT networks, healthcare, and many other applications, which makes secure, reliable, and cost-effective data storage a critical infrastructure of the computing system. Existing data storage largely depends on centralized clouds, which is not only costly but also vulnerable to single points of failure and other types of security attacks. Moreover, cloud providers will have full access to user data and revision history beyond user control. To provide data security, data encryption has to be used, which requires extensive computing power and cumbersome key management. Distributed storage system (DSS) is being widely viewed as a natural solution to future online data storage due to improved access time and lower storage cost. However, the existing DSS also has the limitations of low storage efficiency and weak data security. In this article, we investigate multi-layer code-based distributed data storage systems that can achieve inherit content confidentiality and optimal storage efficiency. Our comprehensive performance analysis shows that the optimal code can improve the feasible region in reliable data storage by 50% under various adversarial attack scenarios.

Current systems used by medical institutions for the management and transfer of Electronic Medical Records (EMRs) can be vulnerable to security and privacy threats. In addition, these systems are centralized, often lack interoperability, and give patients limited or no access to their own EMRs. In this article, we propose a novel distributed data sharing scheme that applies the security benefits of blockchain to address these concerns. We deploy smart contracts on Ethereum blockchain and utilize a distributed storage system to alleviate the dependence on the record-generating institutions to manage and share patient records. To preserve privacy of patient records, we implement our smart contracts as a method to allow patients to verify attributes prior to granting access rights. Our proposed scheme also facilitates selective sharing of medical records among staff members that belong to different levels of a hierarchical institution. We provide extensive security, privacy, and evaluation analyses to show that our proposed scheme is both efficient and practical.

Blockchain is a technology that was proposed to enable the decentralized digital currency, Bitcoin. Since its inception, blockchain has been widely used in many other areas, including tracing sensor data and mitigating its duplication in IoT applications, the healthcare industry, and e-voting. In this article, we provide a comprehensive review and analysis of the major security and privacy issues of Bitcoin and blockchain, the major challenges, and opportunities in utilizing the technology. First, we present a comprehensive background of Bitcoin and the preliminary on security. Second, the major security threats and countermeasures of Bitcoin are investigated. We analyze the risk of double-spending attacks, evaluate the probability of success in performing the attacks, and derive the profitability for the attacker to perform such attacks. Third, we analyze the underlying Bitcoin peer-to-peer network security risks and Bitcoin storage security. We compare three types of Bitcoin wallets in terms of security, types of services, and their tradeoffs. Finally, we discuss the security and privacy features of alternative cryptocurrencies and present an overview of emerging technologies today. Our results can help Bitcoin users to determine a tradeoff between the risk of double-spending attempts and the transaction time delay or confidence before accepting transactions. These results can also assist miners to develop suitable strategies to get involved in the mining process and maximize their profits.

Automated tasks play an important role in both consumer and industrial IoT environments. In many scenarios, the IoT tasks are performed given certain conditions. To facilitate the tasks, it is necessary to delegate a third party to listen to events that trigger the conditions and issue commands to the IoT resources accordingly. However, without restriction, the third party may be over-privileged and able to control the resources unconditionally. We define the third party's permission to act under some conditions as a conditional action. We propose PPCA, a privacy-preserving service that allows users to create conditional actions in a decentralized platform using smart contracts. PPCA can guarantee strict privilege at the third party that holds conditional actions. By generalizing a variety of conditions into simple forms of conditional logic, the conditions can be verified in a privacy-preserving manner. We build a prototype of PPCA on Ethereum. The performance shows the feasibility of PPCA in IoT environments.

Secure access control to a wide variety of Internet of Things (IoT)devices has become critical. Blockchain-based access control frameworks are promising technologies to support secure access to IoT devices in pervasive computing applications. However, in most of the proposed solutions, the IoT devices rely on a trusted server to retrieve critical access control data from the blockchains. We propose a method for IoT devices to validate blockchain data without solely being dependent on a central server. In our approach, several witnesses on the network can be selected randomly by the devices to validate access control information. Our method is aided by Bloom filters, which are shown to be lightweight for resource-constrained devices.

Devices to support pervasive computing and the Internet of Things (IoT) are becoming present in almost every aspect of our lives. Due to their limited power and computation, these devices often need to rely on some more powerful outsourced cloud services, which raises a security and privacy concern as IoT data is often sensitive. On the other hand, blockchain technology has recently gained much attention due to its decentralized, trustless and immutable design. We propose CapChain - an access control framework based on blockchain that allows users to share and delegate their access rights easily to IoT devices in public but still maintain privacy. To protect privacy, we adapt multiple techniques from anonymous crypto-currency blockchain systems to hide sensitive information, including users' identities and related information about the capabilities. We also build a testbed as a proof of concept.

Smartphones are equipped with many low-cost sensors. As a result, opportunities open for smartphones to serve as a platform for many challenging ubiquitous applications, including indoor localization. By employing accelerometers on smartphones, dead reckoning is an intuitive and common approach to generate a user's indoor motion trace. Nevertheless, dead reckoning often deviates from the ground truth due to noise in the sensing data. We propose iLoom, an indoor localization approach that benefits by transferring learning from tracking outdoor motions to the indoor environment. Via sensing data on a smartphone, iLoom constructs two datasets: relatively accurate outdoor motions from GPS and less accurate indoor motions from accelerometers. Then, iLoom leverages an Acceleration Range Box to improve a user's acceleration value used for computing dead reckoning. After using a transfer learning algorithm to the two datasets, iLoom boosts the Acceleration Range Box to achieve better indoor localization results. In addition, iLoom exploits indoor GPS exception cases and pedometer to further improve dead reckoning. Through case studies on 15 volunteers for the indoor and outdoor scenarios, we show iLoom is a non-infrastructure and low-training complexity indoor positioning approach that achieved a localization accuracy of 0.28~0.51m in multiple scenarios.

Indoor positioning systems provide location information without the ability to use GPS. Indoor positioning faces challenges of accuracies and pervasiveness. In this paper, we present SilentWhistle, a mobile system that incorporates acoustic information and motion traces on smart phones to locate users. SilentWhistle does not expose the identity of a mobile device as does Bluetooth or Wi-Fi communications. By detecting and filtering the received audio frequencies, we encode the frequencies to location information. When users encounter each other or related beacons, by measuring the relation between sound strength and distance, the initial location information obtained by dead reckoning can be enhanced by triangulations transferred from sound strength. Centralized and distributed models of SilentWhistle can avoid the spreading of incorrect location messages. Our case studies agree on SilentWhistle is capable of obtaining location with error of less than 1.25m.

Many pervasive computing applications depend upon maps for navigation and support of location based services. Maps are commonly available for outdoor pervasive applications from a variety of sources. An individual can determine their location outdoors on these maps via GPS. Indoor pervasive applications may also need to know the layout of rooms, doorways and hallways of buildings, and the objects and obstacles within them, however indoor maps of buildings are less prevalent. Moreover, indoor maps may need to be dynamic and updated regularly since the layout changes when objects and obstacles are added or removed by people within the building. In this paper, we present iFrame, a dynamic approach that leverages existing mobile sensing capabilities for constructing indoor floor plans. We explore how iFrame users may collaborate and contribute to constructing 2-dimensional indoor maps by merely carrying smartphones or other mobile devices, and to allow their mobile devices to share information with other users' devices. The iFrame approach consists of four steps: 1) Abstract the unknown indoor map as a matrix; 2) Leverage collaborating mobile devices that incorporate three mobile sensing technologies - accelerometers to support dead reckoning, Bluetooth RSSI detection, and WiFi RSSI detection; 3) Combine the three methods by Curve Fit Fusion (CFF), and 4) Extend iFrame from one room to a whole building by shadow rates and anchor points analysis. We conducted a deployment study that shows iFrame is a light-weight and unattended approach that provides a skeleton map of a real building effectively and automatically. The layouts of 12 rooms are reconstructed within 5-10 minutes. Changes of layout in indoor maps can be detected and the resolution of the reconstructed indoor floor plans can be improved when there is an increase in the number of cooperating users.

People carry smartphones that have a variety of radios and sensors. Increasingly, smartphone applications use the radios and sensors to determine a user's location and to sense motion. Nevertheless, most existing smartphone applications cannot avoid accumulative errors when calculating position and movement. In this paper, we propose a novel approach, Air Loc - Adopting mobile robots to assist indoor Localization of smartphones. A moving robot employs a Bluetooth adapter and a known map to assist a smartphone to reduce its localization error. When a robot is near a smartphone, the robot sends accurate location information to users' smartphones via Bluetooth. We design a path planning strategy for a robot to enhance the localization accuracies of smartphones over extended time periods. Moreover, in order to promote the single robot approach, we extend it to the multi-robot assisted indoor localization. The multi-robots are organized by an unbalanced tree and serve areas by the Distance/Density First Algorithm. Through experimentation and simulation in a multi-room building, we evaluate Air Loc and believe it is promising as a cost-efficient means to yield average positioning error below 0.9 meter and possibly lead to better localization results for some scenarios, including shopping mall and hospital.

Accurate indoor location information remains a challenge without incorporating extensive fingerprinting approaches or sophisticated infrastructures within buildings. Nevertheless, modern smartphones are equipped with sensors and radios that can detect movement and can be used to predict location. Dead reckoning applications on a smartphone may attempt to track a person's movement or locate a person within an indoor environment. Nevertheless, smartphone positioning applications continue to be inaccurate. We propose a new approach, CRISP - CoopeRating to Improve Smartphone Positioning, which assumes that dead reckoning approaches have inaccuracies, but leverages opportunities of the interaction of multiple smartphones. Each smartphone computes its own position, and then shares it with other nearby smartphones. The signal strengths of multiple radios that are used on smartphones estimate distances between the devices. While individual smartphones may provide some positioning (possibly inaccurate) information, accuracy may improve when several smartphones cooperate and share position information through multiple iterations. Via indoor experimentation and simulation, we evaluate our approach and believe it is promising as an inexpensive means to improve position information and possibly lead to better results for a number of applications, including exercise profiling.

Abstract The erratic nature of spectrum availability and diversity imposes the use of a probabilistic framework for channel selection in cognitive radio networks protocol design. In this work, two probability distributions called ArgMax and ArgMin are proposed, which have broad applications in channel selection mechanisms, routing, and media access control protocols. The ArgMax probability distribution locates the maximum random variable among a set of random variables, while the ArgMin locates the minimum random variable. We show that the ArgMax probability distribution is a better candidate than the frequently used odds‐on‐mean probability distribution through theoretical analysis and simulation. The ArgMin probability distribution has a variety of applications and is shown to be useful in achieving a lower bound on the network's minimum spectral capacity. In simulation, we develop a probabilistic selection routing procedure (PSRP) that adopts the ArgMax probability distribution to guide packets throughout the network. The stochastic framework of probabilistic selection routing procedure is also an appropriate skeleton for building stochastic‐based routing protocols for dynamic networks such as cognitive radio networks. The simulation results suggest that ArgMax enables the routing scheme to adapt to the network dynamic more quickly and to more accurately locate the best candidate to route to than the odds‐on‐mean probability distribution. The ArgMax enhances the network throughput and end‐to‐end delay by over 30% when network load increases. Copyright © 2013 John Wiley & Sons, Ltd.

Abstract Routing in a cognitive radio network operating in a dynamic environment is a complex decision problem. Diversity in the number of available spectrum bands and their stability, in addition to the secondary users' heterogeneities, affect the consequence of the routing decision. We use a decision theory framework to model the problem of routing under uncertainties involved in a cognitive radio network. A utility function is designed to capture the effect of spectrum measurement, fluctuation of bandwidth availability, and path quality. A node cognitively decides its best candidate among its neighbors by utilizing a decision tree. Each branch of the tree is quantified by the utility function and a posterior probability distribution that predicts the suitability of available neighbors. In decision tree cognitive routing (DTCR), nodes learn their operational environment and adapt their decision‐making accordingly. We compared our scheme with the optimal performance in a highly dynamic environment and local coordination‐based routing and spectrum assignment protocol [1]. Our results show that the DTCR tends to perform near optimum. It easily adapts to environmental dynamics. Copyright © 2013 John Wiley & Sons, Ltd.

In this paper, we present the design and development of a miniature robot that is able to run and jump. This robot can use wheeled locomotion to travel on the flat ground. When it encounters a large obstacle compared to its size, it can stand up and leap over the obstacle. The robot has a mass of 25 grams and a maximum size of 9 centimeters. Experimental results show that with a take-off angle 80°, the robot can jump up to 1.44 meter in height and 0.59 meter in distance. Moreover, it has on-board energy, control, and communication abilities, which enables tetherless or autonomous operation. With the multi-modal locomotion abilities, the robot is expected to have many applications ranging from environmental monitoring, search and rescue, to military surveillance.

Time synchronization is a fundamental service for wireless sensor networks (WSNs). Although a number of message passing protocols can achieve satisfactory synchronization accuracy, they suffer poor scalability and high transmission overhead. An alternative approach is to utilize the global time references such as those induced by GPS and timekeeping radios. However, they require the hardware receiver to decode the out of band clock signal, which introduces extra cost and design complexity. This paper proposes a novel WSN time synchronization approach by exploiting the existing Wi-Fi infrastructure. Our approach leverages the fact that 802.15.4 sensors and Wi-Fi nodes often occupy the same or overlapping radio frequency bands in the 2.4 GHz unlicensed spectrum. As a result, a 802.15.4 node can detect and synchronize to the periodic beacons broadcasted by Wi-Fi access points (APs). A key advantage of our approach is that, due to the long communication range of Wi-Fi, a large number of 802.15.4 sensors can synchronize clock rates to the same beacons without any message exchange. This paper makes several key contributions. First, we experimentally characterize the spatial and temporal characteristics of Wi-Fi beacons in an enterprise Wi-Fi network consisting of over 50 APs deployed in a 300,000 square foot office building. Motivated by our measurement results, we design a novel synchronization protocol called WizSync. WizSync employs digital signal processing (DSP) techniques to detect periodic Wi-Fi beacons and use them to calibrate the frequency of native clocks. WizSync can intelligently predict the clock skew and adaptively schedules nodes to sleep to conserve energy. We implement WizSync in TinyOS 2.1.1 and conduct extensive evaluation on a testbed consisting of 19 TelosB motes. Our results show that WizSync can achieve an average synchronization error of 0.12 milliseconds over a period of 10 days with radio power consumption of 50.9 microwatts/node.

In this paper, we present the design and experimentation of a miniature robot that can jump, run, and perform aerial maneuvering. Specifically, this robot can use wheeled locomotion to run on the ground. Encountering an obstacle, it can jump up to overcome the obstacle. After leaping into the air, the robot can control its body angle using its tail for aerial maneuvering. To the best of our knowledge, this is the first miniature (maximum size 6.5 centimeters) and lightweight (28.0 grams) robot that having all the three capabilities. Furthermore, this robot is equipped with on-board energy, sensing, control, and wireless communication capabilities, which enables the tetherless operation. It can be potentially employed for mobile sensor networks in environments with obstacles.

Cognitive radio networks are developed to solve the under utilization problem of available spectrum. Typically, available spectrum is not fully utilized without supporting multimedia applications. In this work we translate video routing in a dynamic cognitive radio network into a decision theory problem. Then terminal analysis backward induction is used to produce our routing scheme that improves the peak signal-to-noise ratio of the received video. In the proposed Video aware Cognitive Routing strategy (VCR), two components are introduced that improve the precision of correct decision making in a highly dynamic environment; First, a sample and posterior distribution are introduced to explain the status of channels and nodes in supporting video frame quality of service. Second, a utility function is introduced to capture the effects of spectrum stability, fluctuation of bandwidth availability and path quality. In comparison to a deterministic routing scheme developed for dynamic environment (OSDRP), our simulation results show that VCR improves the video quality by at least 30% at the receiver.

Mobile surveillance and sensing systems need a networking infrastructure that enables the mobile systems to transmit information gathered to a base station. We consider the problem of an efficient use of mobile robots to sense not only the region but also deploy relays to build the networking infrastructure. To develop an efficient solution to the above problem, we first present a problem called precedence constrained two traveling salesman (PC2TSP). We propose a near-optimal heuristic to PC2TSP to generate tours by clustering points, generating optimal single-traveler tours, and tour pruning and balance. By modeling in part by PC2TSP, we then solve the problem of minimum time two-robot real-time search with online relay deployment. We call the solution STAtic Relay aided Search (STARS), which identifies visiting positions, assigns the precedence constraint, and finally generates tours by PC2TSP. STARS enables solutions for remote robotic sensing and control. In addition, STARS substantially reduces cost compared to a homogeneous mobile robot system and enables constant monitoring of suspicious areas. STARS and our solution to PC2TSP are extensible to deal with more than two travelers. Extensive simulations show that our solution to PC2TSP achieves near-optimal performance with less than 2 percent average difference from optimal.

ABSTRACT Although there has been substantial progress for multi‐robot exploration of an unknown area, little attention has been given to communication, especially bandwidth constraints in time‐sensitive and bandwidth‐consuming tasks such as search and surveillance. In such tasks, video/audio streams of a newly explored area should be sent back to the base station in a timely manner. To address this issue, we propose connectivity and bandwidth‐aware exploration (CBAX), which is an efficient iteration based real‐time exploration. CBAX divides the problem into frontier node placement, relay node placement with routing path selection, and matching of each robot with its target position. Moreover, we model bandwidth‐constrained relay node placement into a new variant of the Steiner minimum tree problem and present our solution. While reducing the exploration time, CBAX maintains the network's connectivity and ensures the aggregated data flows are under the link capacity in transmission. Simulation shows that CBAX outperforms two recent exploration schemes qualitatively by demonstrating major improvement in terms of non‐overflow transmission time and fully connected transmission time. With enhanced communication quality, CBAX still reduces the exploration time, on average, by 40% and 15%, respectively. In moderately dense scenarios, CBAX even decreases time by 50% and 25%. Copyright © 2011 John Wiley & Sons, Ltd.

In the multi-robot exploration task of an unknown environment, human operators often need to control the robots remotely and obtain the sensed information by real-time bandwidth-consuming multimedia streams. The task has military and civilian applications, such as reconnaissance, search and rescue missions in earthquake, radioactive, and other dangerous or hostile regions. Due to the nature of such applications, infrastructure networks or pre-deployed relays are often not available to support the stream transmission. To address this issue, we present a novel exploration scheme called Bandwidth-aware Exploration with a Steiner Traveler (BEST). BEST has a heterogeneous robot team with a fixed number of frontier nodes (FNs) to sense the area iteratively. In addition, a relay-deployment node (RDN) tracks the FNs movement and places relays when necessary to support the video/audio streams aggregation to the base station. Therefore, the main problem is to find a minimum path for the relay-deployment robot to travel and the positions to deploy necessary relays to support the stream aggregation in each movement iteration. This problem inherits characteristics of both the Steiner minimum tree and traveling salesman problems. We model the novel problem as the minimum velocity Flow constrained Steiner Traveler problem (FST). Extensive simulations show BEST improves exploration efficiency by 62% on average compared to the state-of-the-art homogeneous robot exploration strategies. BEST also saves cost by using only half the number of robots compared to the counterpart, while still achieving a 24% exploration time reduction.

This paper together with the accompanied video presents our improved single motor actuated miniature jumping robot. The robot has a maximum size 6.5 centimeter and a mass 23.5 gram. It can jump towards a desired direction and jump continuously. With a take-off angle 75°, the average jumping height is 0.9 meter. In the video, the detailed robot design is illustrated, and experiments in various situations are presented. These scenarios suggest potential applications of such miniature jumping robots such as surveillance, environmental monitoring, or locomotion in environments with obstacles.

With respect to ground level, wireless communication signal strength increases with the elevation of communicating wireless sensor network devices, within practical bounds. Jumping sensors are mobile sensors that provide relocation capabilities and a temporary increase in elevation can be utilized for improving communication. This paper provides a comprehensive multidimensional analysis for jumping sensors. It studies the main factors that impact the Received Signal Strength (RSS) in sensor communication, and performs a comparative analysis between theoretical and experimental results. Sensor elevation from ground level is a key factor, which is often neglected, and plays an important role for successful wireless communication. The impact of jump height manipulation on a jumping sensor to the packet transmission goodput is presented. An airborne two-way communication scheme is defined and studied with experiments. The results indicate the effectiveness of utilizing the change in elevation of a jumping sensor to increase communication range. Since energy is at premium in sensor nodes, the operational energy cost of a jumping sensor prototype is studied in detail. A jumping sensor network is simulated with the parameters learned from the experimental results and the jumping sensor prototype analysis. Simulation results show the enhancement in connectivity and the feasibility of a jumping sensor network.

The relay placement problem has been studied extensively in wireless networks. Existing work typically focuses on connectivity to prolong the network time or to achieve fault-tolerance. In contrast, we tackle the problem with the goal of achieving bandwidth sufficiency when real-time multimedia streams need to be sent to the sink. We consider the critical condition of heterogeneous link capacity and transmission range. Besides, we consider the relay placement and routing jointly because routing decides the path on which a stream traverses; and the bandwidth sufficiency depends on both supply (the link capacity) and demand (which streams use the link given the routing paths). We formulate the problem as a new variant of the Steiner tree problem called the heterogeneous bandwidth Steiner routing problem. Extensive simulations show that our scheme reduces the number of relays by an average of 44% compared to the widely used minimum spanning tree based approximation algorithm for relay placement. We also found that considering heterogeneous range and rate is beneficial in relay placement. Compared to the uniform range and rate placement algorithm, our scheme reduces the number of relays by 25%-39%. Besides, our scheme notably improves the movement efficiency when applied to a real-time multi-robot exploration strategy.

A miniature robot with continuous jumping ability is presented in this paper. The robot has a dimension about 6cm×8cm×2cm and weighs 20 grams. To achieve continuous jumping, various mechanisms are needed including the jumping mechanism, energy store and release mechanism, self-righting mechanism, and jumping direction changing mechanism. The design and analysis for those mechanisms are elaborated in this paper. Moreover, implementation and experimental results are also presented. It is shown that the robot can jump higher than 55cm with a 75° takeoff angle. The robot can be used as mobile sensors and deployed in the areas of rugged terrain and natural obstacles which are not suitable for sensors with wheels.

In this paper, we propose a new opportunistic multicast protocol to improve multicast throughput in Wireless Mesh Networks (WMN). It builds upon opportunistic routing (OR) strategies that have been designed to improve unicast throughput in wireless networks. The key concept in our multicast protocol is a tree backbone. Our tree backbone protocol represents a tradeoff between traditional structured multicast protocols where a complete multicast tree is constructed and unstructured protocols where multicast is treated as a collection of unicasts. Tree backbone selects multiple nodes as intermediate nodes. Each pair of upstream and downstream nodes may be multiple hops away, and packet delivery between them takes advantage of OR. For single-rate WMNs, we show that constructing an efficient tree backbone that minimizes the number of transmissions is NP-hard, and we devise one effective heuristic algorithm for it. For multi-rate WMNs, we investigate the inherent rate-distance tradeoff and propose a Euclidean opportunistic multicast protocol by devising a Euclidean tree backbone as well as an efficient rate selection scheme to minimize the number of transmissions. In our simulations, our tree backbone multicast protocols outperform both the completely structured traditional multicast protocols and the completely unstructured unicast-based protocols augmented with OR in both throughput and delay.

Time synchronization is a fundamental service for Wireless Sensor Networks (WSNs). This paper proposes a novel WSN time synchronization approach by exploiting the existing Wi-Fi infrastructure. Our approach leverages the fact that ZigBee sensors and Wi-Fi nodes often occupy the same or overlapping radio frequency bands in the 2.4 GHz unlicensed spectrum. As a result, a ZigBee node can detect and synchronize to the periodic beacons broadcasted by Wi-Fi access points (APs). We experimentally characterize the spatial and temporal characteristics of Wi-Fi beacons in an enterprise Wi-Fi network consisting of over 50 APs deployed in a 300,000 square foot office building. Motivated by our measurement results, we design a novel synchronization protocol called WizSync. WizSync employs advanced Digital Signal Processing (DSP) techniques to detect periodic Wi-Fi beacons and use them to calibrate the frequency of native clocks. WizSync can intelligently predict the clock skew and adaptively schedules nodes to sleep to conserve energy. We implement WizSync in TinyOS 2.1x and conduct extensive evaluation on a testbed consisting of 19 TelosB motes. Our results show that WizSync can achieve an average synchronization error of 0.12 milliseconds over a period of 10 days with radio power consumption of 50.9 microwatts/node.

Redundant mobile sensors might be moved in order to cover sensing holes or replace power-exhausted sensors. Within rugged terrains, the use of hopping sensors may be more suitable than wheeled mobile sensors. Since WSN communication is data-centric, globally unique ID allocation that is used for MANETs is usually not applicable for WSNs. A recent study classifies the locally unique ID allocation scheme for WSNs into two representative types: a proactive and a reactive scheme. In the reactive scheme, energy preservation is improved because ID conflict resolution is delayed until data communication is needed. Although a typical reactive ID assignment scheme is used, local uniqueness cannot be guaranteed if hopping sensors are relocated. In order to overcome the weakness, we propose the recycled ID assignment scheme for relocation of hopping sensors. Simulation results show that the proposed recycled ID assignment scheme outperforms the typical reactive scheme for relocation of hopping sensors.

Multi-robot real-time exploration calls for joint consideration of mobility and communication: It requires video and audio streams of a newly explored area be transmitted to the base station in a timely fashion as robots explore the area. We address a central problem: How to place a minimum number of relay nodes, within connectivity and bandwidth constraints, to support the real-time stream aggregation from frontier nodes as they proceed? Particularly, we tackle this problem considering two critical and real-world conditions: (1) the heterogeneous transmission ranges and link capacities; (2) the impact of interference. The conditions increase the model complexity but significantly influence the actual available bandwidth and the required node size in placement. We found considering heterogeneous range and rate is beneficial. Our scheme markedly outperforms the uniform link and range relay placement by reduced relay number and enhanced exploration efficiency.

Adaptability and accuracy in decision making of routing protocols play an important role in the performance of the network. This role is even more crucial in a cognitive radio mesh network operating in a densely populated urban area where the environment is dynamic due to the erratic nature of spectrum availability and spectrum diversity. In this work, a probability distribution called ArgMax is proposed, which can be used as the transitional probability distribution in probabilistic routing and selective protocols. A probabilistic selection routing procedure (PSRP) is also proposed that adopts ArgMax probability distribution to guide packets throughout the network. We have compared the performance of PSRP using ArgMax with PSRP incorporating the well-known and frequently used distribution Odds-On-Mean (OOM) in evaluating its transitional probability distribution. OOM is the distribution that is used in many MAC and routing protocols that select the next node probabilistically. The simulation result suggests that ArgMax enables the routing scheme to adapt to the network dynamic more quickly, and locates the best candidate to route to, more accurately. Hence, the network throughput increased and the end-to-end delay improved.

While there has been substantial progress for multi-robot exploration of an unknown area, little attention has been given to communication, especially bandwidth constraints in time-sensitive and bandwidth-consuming tasks such as search and surveillance. In such tasks, video/audio streams of a newly explored area should be sent back to the base station in a timely manner. To address this issue, we propose Connectivity and Bandwidth Aware eXploration (CBAX), which is an efficient iteration based real-time exploration. CBAX divides the problem into frontier node placement, relay node placement with routing path selection, and the match of each robot with its target position. Moreover, we model bandwidth-constrained relay node placement into a new variant of the Steiner Minimum Tree problem and present our solution. While reducing the exploration time, CBAX maintains the network's connectivity and ensures the aggregated data flows are under the link capacity in transmission. Simulation shows that CBAX outperforms two recent exploration schemes qualitatively by demonstrating major improvement in terms of non-overflow transmission time and fully-connected transmission time. With enhanced communication quality, CBAX still reduces the exploration time, on average, by 40% and 15% respectively. In moderately dense scenarios, CBAX even decreases time by 50% and 25%.

Mobile sensors with jumping ability provide several advantages compared with the traditional wheeled sensors such as ability to move in rugged terrain. A controllable jumping robot for this purpose is described in this paper. The robot has dimension about 9.5cm × 9cm × 3cm and weighs 54.1 grams. It can perform the jumping process continuously. This paper focuses on the mechanisms to achieve such a continuous jumping ability, including the jumping mechanism, energy store and release mechanism, and self-righting mechanism. Detail implementation and experimental results are also given in this paper. It is shown that with a 75° takeoff angle, the robot can jump about 20cm in height.

This work presents the organization and operation of a hopping sensor wireless network. It defines two decentralized algorithms for the discovery of isolated nodes, aggressive and smart discovery, to propagate base station connectivity. Both algorithms rely on the usage of hopping sensors on the boundary of a cluster, without prior topology information. We studied the efficiency of the algorithms in terms of network energy consumption and connectivity propagation. A cluster to cluster (C-to-C) packet forwarding scheme, which relies upon boundary hopping sensor gateway nodes, is defined and simulated, and proves to have remarkable low energy consumption. In-field measurements were performed to obtain real data to serve as input parameters for simulations. Simulation results indicate significant savings in network wide energy consumption (57% for aggressive discovery and 79% for smart discovery).

In TDMA based wireless mesh networks, routing and scheduling algorithms are essential to provide QoS support for mesh clients. In order to maximize the network throughput and minimize session delay, the routing and scheduling algorithms should produce a minimum length schedule. A linear programming formulation enables an optimal solution, however has very high computational cost. In this paper, we consider network scenarios where multiple orthogonal channels are available. With a channel assignment algorithm to eliminate secondary interference, we are able to use a scheduling algorithm that yields the minimum length schedule given a specific routing tree. We then propose a heuristic routing algorithm that aims to build the routing tree that results in the minimum length schedule. Our routing algorithm performs significantly better than simple routing algorithms, which are based on Breadth First Search or Dijkstra algorithms.

In pervasive computing environments, personal information is typically expressed in digital forms. Daily activities and personal preferences with regard to pervasive computing applications are easily associated with personal identities. Privacy protection is a serious challenge. The fundamental problem is the lack of a mechanism to help people expose appropriate amounts of their identity information when accessing pervasive computing applications. In this paper, the authors propose the Hierarchical Identity model, which enables the expression of one’s identity information ranging from precise detail to vague identity information. The authors model privacy exposure as an extensive game. By finding subgame perfect equilibria in the game, the approach achieves optimal exposure. It finds the most general identity information that a user should expose and which the service provider would accept. The authors’ experiments show that their models can reduce unnecessary identity exposure effectively.

Abstract A mobile node in a MANET must be assigned a free IP address before it may participate in unicast communications. This is a fundamental and difficult problem in the practical application of any MANET. There have been several solutions proposed, among which prophet address allocation outperforms others in terms of communication overhead, latency, and scalability. However, none of the approaches can survive attacks in an insecure environment. Although there are a few secure autoconfiguration schemes proposed, they all have some disadvantages. Based on studies of insecure scenarios, attack schemes, and our previous work, a secure autoconfiguration algorithm, namely secure prophet address allocation, is proposed in the paper. The proposed approach is able to maintain uniqueness of address assignment in the presence of IP spoofing attacks, [state pollution] attacks, and Sybil attacks. The invulnerability of the scheme is supported by both theoretical analysis and simulation results. Copyright © 2009 John Wiley & Sons, Ltd.

The wireless mesh network is an emerging technology that provides high quality service to end users as the "last milerdquo of the Internet. Furthermore, multicast communication is a key technology for wireless mesh networks. Multicast provides efficient data distribution among a group of nodes. However, unlike other wireless networks, such as sensor networks and MANETs, where multicast algorithms are designed to be energy efficient and to achieve optimal route discovery among mobile nodes, wireless mesh networks need to maximize throughput. This paper proposes two multicast algorithms: the level channel assignment (LCA) algorithm and the multichannel multicast (MCM) to improve the throughput for multichannel and multi-interface mesh networks. The algorithms build efficient multicast trees by minimizing the number of relay nodes and total hop count distances of the trees. The algorithms use dedicated channel assignment strategies to reduce the interference to improve the network capacity. We also demonstrate that using partially overlapping channels can further diminish the interference. Furthermore, additional interfaces help to increase the bandwidth, and multiple gateways can further shorten the total hop count distance. Simulations show that those algorithms greatly outperform the single-channel multicast algorithm. We also observe that MCM achieves better throughput and shorter delay while LCA can be realized in distributed manner.

In wireless sensor networks, communication signal strength weakens as the distance between sensors increases, which increases the tendency for transmitted packets to be lost. This paper provides a novel method of incorporating the hopping capability of a sensor to increase its communication range, which results in increased connectivity and sensed coverage area. Furthermore, jump heights can be manipulated to enhance packet transmissions. Since energy is at premium within sensor nodes, we present a Hopping Sensor Network Model (HSNM) and an energy conserving Hopping Sensor Routing Protocol (HSRP), which aims to optimize communication paths while balancing energy depletion in the network. Results from practical in-field experiments and simulations demonstrate the effectiveness of the approach when employed over a wireless hopping sensor network by showing increased network connectivity and the total area covered. HSRP simulations demonstrated 20% energy saving while increasing the packet delivery. The HSRP results in far less number of dead nodes, especially the high traffic nodes that are closer to the base station.

Wireless mesh networks (WMN) have emerged as an economical means for delivering last-mile Internet access. Multicast is a fundamental service in WMNs because it efficiently distributes data among a group of nodes. Multicast algorithms in WMNs are designed to maximize system throughput and minimize delay. Previous work has unrealistically assumed that the underlying WMN is link-homogeneous. We consider one important form of link heterogeneity: different link loss ratios, or equivalently different ETX. We model different link loss ratios by defining a new graph theory problem, HW-SCDS, on an edge-weighted directed graph, where the edge weights model ETX, the reciprocal of link loss ratios. We minimize transmissions in a multicast by computing a minimum HW-SCDS in the edge-weighted graph. We prove HW-SCDS is NP-hard and devise a greedy algorithm for it. Simulations show that our algorithm significantly outperforms the current best WMN multicast algorithm by both increasing throughput and reducing delay.

When sensors in wireless sensor networks fail or become energy-exhausted, redundant mobile sensors might be moved to cover the sensing holes created by the failed sensors. Within rugged terrains where wheeled sensors are unsuitable, other types of mobile sensors, such as hopping sensors, are needed. In this paper, we address the problem of relocating hopping sensors to the sensing holes. Recent study for this problem considered moving sensors along the shortest path. The shortest path might be used repeatedly and therefore create other sensing holes. In order to overcome these weak nesses, we propose multipath-based schemes considering the balanced assignment for the relocation of hopping sensors. Simulation results show that the proposed schemes guarantee a more balanced migration distribution of efficient sensors and a higher movement success ratio of required sensors than those of the shortest path-based schemes.

Hopping sensors are a type of low cost mobile sensors that are small in size, have limited capability and imprecise movement. However, their unique method of movement makes them suitable for rugged terrains. Sensors may fail when deployed in a rugged terrain or in an obstacle-abundant environment. Therefore, redundant sensors may be identified and relocated to the sensor holes. This paper addresses the problem of relocating such capability-constrained sensors in an obstructive environment. We propose an enhanced quorum-grid solution with binary splitting message forwarding (BSMF), which is decentralized and can detect both existing and newly appearing obstructions in the supplier and consumer cells matching process. Furthermore, a grid-based movement model is introduced for the hopping sensors. Simulation shows that our scheme significantly reduces the communication overhead and achieves relatively constant total energy consumption with varying amount of obstructions.

We present the design and implementation of a new jumping robot for mobile sensor network. Unlike other jumping robots, the robot is based on a simple two-mass-spring model. After we throw it on ground, it can stabilize itself and then jump once. The detailed mechanism design including the load holding and self-stabilization are presented. Jumping heights and distances with different robot weights are measured and compared with calculated values from the two-mass-spring model.

Security is extremely important for the deployment of a mobile ad-hoc networks (MANET) due to its openness to attackers, the absence of an infrastructure, and the lack of centralized administration. Most research efforts have been focused on secure routing protocols, the distributed certificate authority, and key distribution, while a few projects have focused on secure autoconfiguration. However, the importance of integration of a secure autoconfiguration and public-key distribution has been neglected. This paper presents a secure autoconfiguration and public-key distribution algorithm to achieve uniqueness of address allocation and secure public-key distribution when a new node joins a MANET, which provides the bootstrapping for building a distributed certificate authority (DCA) in the network where a trust relationship is absent.

Wireless mesh networking is a promising technology for building broadband wireless access networks. However, wireless mesh networks based on CSMA/CA MAC protocols suffer from unfairness and poor QoS support. Using TCP as a rate control mechanism in such networks further exacerbates the problem. Efficient rate allocation and scheduling algorithms that handle both multicast and unicast traffic in wireless mesh networks are needed with the increasing popularity of multicast and multimedia applications. In this paper, we propose a framework that performs both rate allocation and scheduling for unicast and multicast traffic in TDMA-based wireless mesh networks. The rate allocation algorithm is based on network utility maximization. The graph coloring-based scheduling algorithm achieves the allocated rates. Simulation results show that our framework provides guaranteed throughput and low delay for both multicast and unicast traffic. Furthermore, our framework significantly outperforms a previously published framework that has a similar objective.

Hopping sensors are a class of mobile sensors whose mobility design are inspired by creatures such as grasshoppers. Such sensors are able to maintain mobility in harsh terrains but may lack movement accuracy of those sensors that are powered by wheels. We examine the opportunities and challenges for utilizing the mobility of low cost hopping sensors to ensure coverage and maintain energy efficiency within a sensing field. We focus on the problem of transporting a number of hopping sensors from multiple sources to a destination. Probabilistic methods are used to contain the movement inaccuracies along the hopping course. We also consider the impact of wind under an aerodynamic setting. Two transport schemes are designed to minimize the number of hops needed while considering other constraints, such as sustaining the capability of relocating sensors within the whole network. In one scheme we use upper and lower hopping limits to apply the network mobility constraints. The other scheme uses a balancing coefficient to construct a new optimization target to meet the requirement of path optimality and network mobility dynamically. Simulation results show that both schemes work well regardless of the wind factors, while the dynamic scheme is also shown to be resilient to topological changes of the network.

Multimedia applications over wireless mobile networks become more popular with the increasing deployment of wireless infrastructures. IEEE 802.16 standard has become an emerging technology to support broadband access and quality of service (QoS) for real-time multimedia applications over wireless networks. This paper discusses the path selection problem in IEEE 802.16 mobile multihop relay (MMR) networks where relay stations are used to extend network coverage and enhance network capacity. For real-time applications that have explicit rate and delay requirements, choosing an appropriate path between any mobile station and the base station becomes essential. In this paper, we propose a path selection metric, named normalized number of minislots (NNM), which enables a mobile station to choose a path that satisfies its application rate and delay requirements. Simulation results show that NNM outperforms existing path selection metrics, especially when network has high traffic load.

Multicast is a key technology that provides efficient data communication among a set of nodes for wireless multi-hop networks. In sensor networks and MANETs, multicast algorithms are designed to be energy efficient and to achieve optimal route discovery among mobile nodes, respectively. However, in wireless mesh networks, which are required to provide high quality service to end users as the "last-mile" of the Internet, throughput maximization conflicting with scarce bandwidth has the paramount priority. We propose a Level Channel Assignment (LCA) algorithm and a Multi-Channel Multicast (MCM) algorithm to optimize throughput for multi-channel and multi-interface mesh networks. The algorithms first build a multicast structure by minimizing the number of relay nodes and hop count distances between the source and destinations, and use dedicated channel assignment strategies to improve the network capacity by reducing interference. We also illustrate that the use of partially overlapping channels can further improve the throughput. Simulations show that our algorithms greatly out-perform the single-channel multicast algorithm. We observe that MCM achieves better throughput and shorter delay while LCA can be realized in distributed manner.

Network surveillance systems provide extended perception and distributed sensing capability in monitored environments through real time monitoring of the target area and target objects using multiple networked sensors. The development of wireless communication and sensing technology make it possible to deploy networked surveillance systems in various environments. We consider a surveillance network where the sensors are static. The task of tracking targets in a surveillance network is challenging because of the following reasons: (1) the location of the sensors need to be optimally deployed. (2) The view of the sensors need to be optimized so that at a given time the targets are shown with a discernable resolution for feature identification. (3) It is important to devise stable control algorithms for accomplishing the surveillance task. When the target moves, it is important to switch the sensing task between sensors to maintain the visibility of the target with adequate resolution. This paper presents a novel method to deploy static sensors given a target region and a dynamic programming method to optimally switch sensors when the target moves. Finally, simulation results demonstrate the efficacy of the proposed approach for tracking targets over an area.

The task of visual surveillance involves pervasively observing multiple targets as they move through a field of sensor nodes. Mutational analysis and shape based control have been proposed to overcome the limitations of current feature (point) based visual servoing and tracking techniques generally employed to provide an optimal solution for the surveillance task. Hausdorff tracking paradigm for visual tracking of multiple targets using a single sensor has been proposed for accomplishing the surveillance task. However, Hausdorff tracking incorporates some redundancy in the actuation mechanism. This paper exploits this redundancy in the camera motion in order to accomplish various sub-tasks which can be assigned to the system, such as minimization of consumed energy maintaining manipulability etc. The complete task can then be expressed in a multi-objective constrained optimization framework and can be solved, i.e., the input to the camera can be derived, using various methods such as physical programming, nonlinear programming, weighted sum method, etc. In this paper, we use the physical programming method based on the various advantages such as ease of expressing multiple objectives in a physically significant manner. Experimental results are provided which show the advantages of using the physical programming approach over the weighted sum method for constructing the task criterion for multi-objective optimization problems.

This paper presents our development of a network-enabled human/robot cooperative interface for tele- diagnostics of breast pathology. To enhance telepresence capabilities, our human/robot interface is comprised of an anthropomorphic arm/hand equipped with haptic and tactile sensing, ultrasound imaging capabilities, a physician interface capable of rendering both haptic and tactile information, and two-way audio and video. This cooperative and multimedia interface was tested via the Internet and enables tele-diagnostics. Preliminary experiments had demonstrated the effectiveness of the developed human/robot tele-diagnostic interface. That is, it will greatly enhance and improve the diagnostic performance as well as promote the tele-diagnostics of breast pathology in remote areas a reality.

The involvement of only the necessary users and service providers for service discovery in pervasive computing environments is challenging. Without prudence, users' and service providers' requests or service information, their identities, and their presence information may be sacrificed. We identify that the problem may be as difficult as a chicken-and-egg problem, in which both users and service providers want the other parties to expose sensitive information first. In this paper, we propose a progressive and probabilistic approach to solve the problem. Users and service providers expose partial information in turn and avoid unnecessary exposure if there is any mismatch. Although 1 or 2 bits of information are exchanged in each message, we prove that the process converges and that the false-positive overhead decreases quickly. Experiments and hypothesis tests show that security properties hold. We implemented the approach and the performance measurements show that the approach runs efficiently on PDAs.

A distributed processing and communication approach is applied to networked surveillance systems providing an extended perception and sensing capability in monitored environments. By pervasive we mean that the entire surveyed area is covered by a heterogeneous collection of fixed and mobile sensors. The sensor network uses a cooperative tracking technique that allows for the deployment of mobile sensors based on data provided by other sensors in the network. Also, an image-based tracking technique is used for tracking when the target is in view. The task of tracking multiple targets in a distributed surveillance network is a challenging problem because of the following reasons: (1) multiple targets need to be monitored and tracked continuously and must remain in view of at least one of the sensors; (2) the view of the sensors needs to be optimized so that the targets are observed with a discernible resolution for feature identification; (3) it is important to devise stable control algorithms for accomplishing the surveillance task; (4) assigning tracking tasks to sensors must consider load balancing and efficient use of all sensors. This paper presents a distributed communication and processing model that allows for a fast deployment of sensor nodes and implementation of ad hoc tracking in a multi-target surveillance scenario. Also, experimental results demonstrate the efficacy of the proposed approach for tracking multiple targets over a large area with fixed and mobile sensors

A robotic device with haptic, tactile, and ultrasound capabilities, which can acquire and render information of breast pathology was developed. A physician interface that can examine the human breast remotely and accurately, using such a robotic device was also developed. Such a robotic device can be used to do screening or focused breast exams for patients in remote areas without convenient access to physicians. Because of in-situ ultrasound imaging, examination by the robotic device may prove to be more accurate than examination by the physicians own hand. In addition, the robotic device can also be used to train healthcare professionals in breast pathology

Pervasive surveillance can be defined as continuous monitoring and tracking of multiple targets in a large monitored region so that they do not leave the field of view (FOV) of the sensors observing them. Despite the limited sensing capability and range of the individual sensors, the surveillance network can track targets over a large region based on transferring the target tracking task. The challenge for such large scale networked systems is to design an efficient and scalable modeling and analysis tool and devise stable control algorithms for accomplishing the surveillance task. Mutational analysis and shape based control have been proposed to overcome the limitations of current feature (point) based visual servoing techniques, however, they fail to capture the discrete switching nature of the surveillance task of tracking the target using multiple sensors. This paper presents a mutational hybrid model for such pervasive surveillance networks which retains the advantages of using mutational equations while also being able to model the discrete switching between various sensors. We also present an example pervasive surveillance scenario modeled using the proposed method and experimental results verifying the proposed approach. © 2006 IEEE.

In a heterogeneous wireless network environment, the network nodes are equipped with both wireless local area network (WLAN) and cellular interfaces. It is desirable to combine the higher bandwidth of a WLAN and the ubiquitous nature of cellular networks to provide the transport service for QoS demanding applications, such as remote sensing and control systems. Common solutions exploit the diversity of cellular channels by recruiting multiple WLAN peers to work as proxies for a MANET node that needs to communicate through the cellular network. One important problem when utilizing channel diversity in a heterogeneous wireless network environment is to balance the trade-off of channel diversity gains with MANET peer contentions. A greater number of proxies will inevitably increase the MANET contention and possibly QoS degrading of the cell, and fewer proxies may not be able to provide sufficient diversity. This paper aims to build a dynamic mechanism to determine the appropriate number of proxies to use. The mechanism uses the MAC layer retransmission rate as an indicator of the contention level in MANET. Simulation using cellular channel fading models and prevalent cell scheduling policies indicate the scheme can provide better QoS through channel diversity by using the appropriate number of proxies

We propose a novel entity authentication approach for pervasive computing environments. A person uses a single device, the master key, which aggregates all his digital forms of access tokens for entity authentication. The master key discovers and selects proper tokens for its owner. With an emphasis on usability, the master key secures authentication, protects privacy information from outsiders and insiders, and supports various claimant-verifier relations. We analyze privacy and security properties of our approach and protocols, and we investigate the overhead. Performance measurements show that our protocols are efficient

Service Discovery as an essential element in pervasive computing environments is widely accepted. Much research on service discovery has been conducted, but privacy and security have been ignored and may be sacrificed. While it is essential that legitimate users should be able to discover services, it is also necessary that services be hidden from illegitimate users. Since service information, service provider's information, service requests, user presence information, and user's identities may be sensitive, we may want to keep them private during service discovery processes. There appears to be no existing service discovery protocols that solve these problems. We present a user-centric model, called Prudent Exposure, which exposes minimal information privately and securely. Users and service owners exchange code words in an efficient and scalable form to establish mutual trust. Based on the trust, secure service discovery sessions are set up. The model is further improved to counter attacks. We analyze the mathematical properties of our model, formally verify our security protocol, and measure the performance of our prototype system.

Available bandwidth (AB) defined as a minimum spare capacity of links constituting a network path is an important QoS characteristic of the path. We propose to improve a whole range of "probe-rate" AB measurement tools that send sequences of measurement packets (called "trains") across the network path. If transmission times of packets in the train, called one way delays (OWD), show an increasing trend as packet sequence number in the train increases, then AB is believed to be lower than the rate at which the train was sent. In contrast, an absence of a trend indicates that AB is higher than the rate of the train. We propose an algorithm for efficient OWD trend detection and compare it to widely used OWD trend detection tests.

Most prevalent distributed certificate authority (DCA) schemes in the MANET are based upon threshold cryptography, which is invulnerable to mobile adversaries and tolerable to missing or faulty DCA server nodes, and thus becomes the "de facto" standard for the security framework in the MANET. However, this scheme cannot defeat Sybil attacks, in which a malicious node impersonates many identities. To solve the problem, a multiple-key cryptography-based DCA scheme, namely the MC-DCA scheme, is proposed in the paper. It is invulnerable to Sybil attacks, and achieves lower communication overhead and moderate latency compared with the threshold-based scheme, which is supported by the simulation results.

Current cellular data networks provide relatively low throughput, which results in long delays when downloading large files. We propose a cooperative parallel file downloading scheme to reduce latency in cellular data networks. Mobile nodes form a mobile ad hoc network (MANET) via their IEEE 802.11-based links to share their cellular link capacity. A file is split into pieces and downloaded simultaneously by the client and several neighbor nodes that act as relay proxies. The proxies then use the MANET to forward packets to the client. Thus, the client uses multiple paths for parallel downloading. No special hardware or modifications on the base stations are needed. An on-demand proxy discovery algorithm is proposed for fast and efficient proxy discovery. Experimental and simulation results show that cooperative parallel file downloading may significantly improve cellular network utilization and file download performance.

For Internet based real-time teleoperation systems, random time delay can cause instability in the closed loop control system and hence hinder task accomplishment. Event based control systems have been proposed to overcome the instability caused by the random time delay. High latency at the transport layer can still impede effective and reliable execution of tasks with high dexterity requirements. Network QoS based dynamic resource allocation has been proposed to increase the efficiency and reliability of task execution. However, these approaches only try to mitigate or overcome the effects of random time delay and do not address the cause of latency issues in the communication channel. This paper addresses the efficiency and reliability requirements for supermedia enhanced teleoperated systems by reducing the end-to-end transmission latency through the use of overlay networks. The proposed system reduces the transmission latency by using multiple, disjoint paths in overlay networks. The proposed system facilitates reliable and efficient task completion for tasks with high dexterity requirements. Experimental validation of the proposed teleoperated system using the PlanetLab Network is provided for the task of teleoperating a mobile manipulator system.

In supermedia enhanced Internet based teleoperation systems, the data flowing between the operator and the robot include robotic control commands, video, audio, haptic feedback and other media types. The difference between an Internet based teleoperation system and other Internet applications are that (1) there are many media types involved in teleoperation systems and each of them has a particular quality of service (QoS) requirement; and (2) some media types are very latency sensitive. Overlay networks have been proposed to improve the QoS of teleoperation applications. However efficient use the overlay network resources and the distribution of these resources optimally to all supermedia streams remains an important problem. This paper aims to provide a framework of QoS management for teleoperation systems over overlay networks. The validity and performance of the system is evaluated using the PlanetLab overlay network.

Networked surveillance systems provide an extended perception and distributed reasoning capability in monitored environments through the use of multiple networked sensors. The challenge for such large scale networked systems is to design an efficient modeling and analysis tool and devise stable control algorithms for accomplishing the surveillance task. Current feature (point) based visual servo and tracking techniques generally employed do not provide an optimal solution for the surveillance task. This paper presents a mutational analysis approach for shapes, and shape based control to model and design mechanisms for such active surveillance systems. The techniques of image based Hausdorff tracking and cooperative Hausdorff tracking are introduced. Finally, experimental results demonstrate the efficacy of the proposed approach for tracking targets over a large area.

In a bilateral teleoperated system, the signal transmissions between the operator and the slave manipulators have different QoS requirements in comparison to traditional network traffic. Running teleoperated systems over wireless networks poses more challenges in comparison to wired networks. The media streams involved differentiate themselves from other media types in that they require both reliable and smooth delivery. Reliable delivery requires the transport service to have TCP style semantics. By being smooth, the transport service should be able to deliver the control and sensing data with bounded and reduced latency and its variation. For example, we have conducted numerous teleoperated experiments using our system. We have found in some of our applications that if the end-to-end latency variance becomes larger than 0.3 second, the operator has difficulty maintaining smooth control of the slave manipulator. However, our simulations show that using TCP, the end-to-end latency variance can be as much as 2.5 seconds in an ad hoc wireless network. This paper proposes an improved transport service for remote sensing and control (TRSC). The service reduces the end-to-end latency and latency variance (jitter) for real-time reliable media in mobile ad hoc networks by using forward error correction encoding and multiple network paths. Simulation using NS2 shows the approach performs well under different wireless scenarios.

Globally unique ID allocation is usually not applicable in a sensor network due to the massive production of cheap sensor nodes, the limited bandwidth, and the size of the payload. However, locally unique IDs are still necessary for nodes to implement unicast communications to save power consumption. Several solutions have been proposed for locally unique ID assignment in sensor networks. However, they bring much communication overhead, which is not desirable due to the limited power supply in a sensor node. Combined with a directed diffusion communication paradigm, a reactive ID assignment scheme with security mechanisms is proposed in this paper. It defers ID conflict resolution until data communications are initiated and thus saves communication overhead.

It may be costly for mobile pervasive computing device users to download content from the Internet using their 3G connections if the 3G connection cost is a function of the amount of data downloaded. This paper introduces an approach in which mobile pervasive computing devices form an ad hoc network and share downloaded content with each other. In order to improve privacy when sharing content, this paper describes an anonymous connection between the sending peer and the receiving peer. Simulation results show that the transmission overhead of the anonymous connection may increase 50% or less as the number of peers increase or the peers are scattered over the larger area.

In pervasive computing environments, service discovery facilitates users to access network services by automating tedious manual configurations. When network services become pervasive, the number of service providers also increase dramatically. Because of security and privacy concerns, network services are segmented by service providers. Existing service discovery protocols, however, do not address how to facilitate users to properly identify and authenticate with existing service providers. Without prudence, sensitive information may be exposed. Conversely, with prudence both users and service providers prefer the other party to expose sensitive information first. We identify that even among legitimate users and service providers, there are privacy concerns that may be expressed as a chicken-and-egg problem. In this paper, we propose a progressive approach to solve the problem. Users and service providers expose minimal sensitive information in turn and identify necessary exposure during the process. Theoretical analysis, simulation, and experiments show that our approach protects sensitive information with little overhead.

Abstract This paper provides a scheme to reduce the cost to distribute multimedia content to a set of nearby mobile peers, which we call chums. One peer, called the proxy, downloads multimedia content via a telecommunication link, and distributes it (which we call chumcast) to the ad hoc network formed from the set of nearby peers. Each peer in the ad hoc network takes turns serving as a proxy. Every peer is associated with a server that resides in the internet. The server for the proxy, called the active server, manages peer information, schedules the next proxy, selects a set of rebroadcasting peers, and detects partitioning of the ad hoc network. With support from the servers in the internet, peers receive benefits of reduced telecommunication bandwidth, computation power, as well as several security features. Simulation results show that 80% of the telecommunication cost is saved with as few as six peers. Copyright © 2005 John Wiley & Sons, Ltd.

When compared with a fixed host that is connected to a hardwired network, a mobile nude in the MANET may change its IP address more frequently due to the deployment of autoconfiguration, global connectivity, and hierarchical addressing schemes. When an IP address changes, the performance of unicast routing protocols and real-time communications may degrade, and privacy may be compromised within the MANET. Although there have been some autoconfiguration algorithms proposed for the assignment of unique IP addresses to mobile nodes, the overhead resulting from address changes has not been carefully examined. Based on studies of the overhead caused by address change, an IP address handoff solution, which extends the unicast routing protocol and network address translation (NAT) scheme, is proposed in the paper. The proposed approach is able to offset the overhead of broken routing fabrics and on-going communications, which is supported by our analysis and a prototype implementation.

Via peer-to-peer sharing, we envision highly mobile users cooperating by sharing telecommunication connections to support a continuous messaging notification channel. Peer-to-peer sharing would enable a reduction of users' telecommunication charges and devices' battery consumption. Nevertheless, without a centralized trust authority, people lack the incentive to cooperate with a group of strangers. We present a new distributed trust framework and a credit system to solve this problem. Trust is evaluated based on a user's own experience and information obtained from others. The credit system is built on top of the trust system to ensure that each user appropriately takes turns providing the proxy service for the group of peers. No centralized authority or long-term accountability is needed. Simulation results demonstrate that this framework is stable and efficient. Fairness is maintained among users and each user may benefit in proportion to its contribution to the group.

Service discovery as an essential element in pervasive computing environments is widely accepted. Much active research on service discovery has been conducted, but privacy has been ignored and may be sacrificed. While it is essential that legitimate users should be able to discover services of which they have credentials, it is also necessary that services be hidden from illegitimate users. Since service information, service provider's information, service requests, and credentials to access services via service discovery protocols may be sensitive, we may want to keep them private. Existing service discovery protocols do not solve these problems. We present a user-centric model, called Prudentexposure, as the first approach designed for exposing minimal information privately, securely, and automatically for both service providers and users of service discovery protocols. We analyze the mathematical properties of our model and formally verify our security protocol.

Some mobile devices are beginning to support both cellular and IEEE 802.11 based network interfaces. Although rates are increasing, current cellular networks provide relatively low bandwidth that do not meet the QoS requirements of many high-demanding multimedia applications. In this paper, we propose an integrated network architecture that utilizes both wireless interfaces to provide better QoS support by QoS aware wireless bandwidth aggregation (QAWBA). Via QAWBA, mobile nodes form a mobile ad hoc network (MANET) using their IEEE 802.11 interfaces to share their cellular link capacity. Some mobile nodes act as proxies to contribute their idle cellular links to support a QoS request that may exceed the available bandwidth of any individual mobile node. A K-path proxy discovery algorithm is proposed for fast and efficient proxy discovery. Simulation results show that QAWBA can significantly improve network utilization and the admission rate of QoS requests.

Securely accessing unfamiliar services in public environments using ad hoc wireless networks is challenging. We present a proxy-based approach that uses other existing network channels to set up a secure and trust relationship between communication parties to facilitate ad hoc wireless communications. Based on a service discovery protocol, our models achieve secure, trusted, anonymous, efficient, and economical communications between unfamiliar parties. Our protocols are formally verified using BAN logic.

A mobile device in a MANET must be assigned a free IP address before it may participate in unicast communication. This is a fundamental and difficult problem in the practical use of any MANET. Several solutions have been proposed. However, these approaches have different drawbacks. A new IP address allocation algorithm, namely prophet allocation, is proposed in the paper. The proposed scheme may be applied to large scale MANETs with low complexity, low communication overhead, even address distribution, and low latency. Both theoretical analysis and simulation experiments are conducted to demonstrate the superiority of the proposed algorithm over other known algorithms. Moreover, the proposed prophet allocation is able to solve the problem of network partition and merger efficiently.

Continuous wireless wide area network (WWAN) access for mobile devices in future pervasive systems may be limited by battery power and may generate extensive data telecommunication costs. In this paper we develop a new message notification protocol (MNP) to enable mobile users to maintain a continuous presence at their instant messaging (IM) server while avoiding long, idle connections. In MNP, mobile users cooperatively share a single message notification channel to reduce users' telecommunication charges and extend a device's battery life. A device may turn off its WWAN interface for most of the time to save power, and only needs to contact the IM server when needed. Precise group information does not need to be maintained by a mobile device. Message notification exchanged between the IM server and the peer group is represented by a compressed Bloom filter to further reduce the protocol overhead and provide additional privacy and security.

In pervasive computing environments, powerful handheld devices with wireless connections create opportunities for many new nomadic applications. We propose a new service discovery model, called Splendor, supporting nomadic users and services in public environments. Splendor emphasizes security and supports privacy. Location awareness is integrated for location dependent services discovery and is used to lessen service discovery network infrastructure requirements. We analyze the Splendor system performance and provide our experimental results.

Abstract A new software technology for on‐line performance analysis and the visualization of complex parallel and distributed systems is presented. Often heterogeneous, these systems need capabilities for the flexible integration and configuration of performance analysis and visualization. Our technology is based on an object‐oriented framework for the rapid prototyping and development of distributable visual objects. The visual objects consist of two levels, a platform/device‐specific low level and an analysis‐ and visualization‐specific high level. We have developed a very high‐level markup language called VOML and a compiler for the component‐based development of high‐level visual objects. The VOML is based on a software architecture for on‐line event processing and performance visualization called EPIRA. The technology lends itself to constructing high‐level visual objects from globally distributed component definitions. Details of the technology and tools used, as well as how an example visual object can be rapidly prototyped from several reusable components, are presented. Copyright © 2003 John Wiley & Sons, Ltd.

Peer-to-peer file systems are typically vulnerable to denial-of-service or free-loader problems. Those that address these issues employ approaches that are either simplistic or require a centralized authority. We explore how a zero-sum trading system can provide strong quotas to a peer-to-peer distributed file system without any centralized authority. We treat each member of such a peer-to-peer system as an autonomous agent, interested in preserving its own disk storage. We develop a model for these agents, and present experimental simulation and external emulation results from a multi-agent reinforcement learning model demonstrating the validity of this approach.

An ad hoc network is a rapidly deployable wireless network that has no centralized control mechanism. Mobile devices in an ad hoc network request a variety of data types, including text and multimedia data. Different types of data need to be treated with different qualities of service. The implementation of service differentiation in wireless networks is very difficult because of device mobility and wireless channel contention. A backoff algorithm is used for resolving contention. Modification of the conventional backoff algorithm allows the design of several classes of flows. This paper specifies three types of flow classes: gold, silver, and bronze. Simulation results illustrate that the gold class flows receive almost up to their requested target bandwidth and the silver class flows are treated with reasonably high bandwidth allocation compared to the bronze class flows.

Some type of transmission rate control protocol is required in order to support multicast video applications over the Internet. Previously, we proposed a protocol, the layered multicast control protocol (LMCP), which utilizes both the sender and receiver to control the rate of the video transmission. The sender stripes the video signal across multiple multicast channels, and each receiver selectively adds and drops channels to meet their individual needs. The receivers also send feedback to the sender, and the sender uses this feedback to adjust the transmission rate for each channel. One weakness of this approach is that it did not share the available bandwidth fairly among multiple video applications. In this paper we introduce a new router based approach for determining a video applications fair share of the available network bandwidth. This approach builds on the strengths of the LMCP approach while allowing multiple video applications to share the available bandwidth. This approach requires low overhead on the network routers, scales well to hundreds of video sources and is independent of the number of video receivers. We show through our simulation results that this approach allows the network to be shared fairly among video applications and adjusts gracefully to fluctuations in available bandwidth.

Emerging parallel or distributed heterogeneous real-time computer systems with many disparate constraints and requirements would benefit from a unifying and comprehensive systems engineering support in the design, testing and deployment phases, which interfaces with a human at a very high level and efficiently handles the system complexity. We present an approach to integration of: a compiler and constraint logic programming-based approach to design and engineering of complex real-time systems; and an online performance analysis and visualization technology with steering. An example distributed real-time system is used to help describe the integrated approach. Details are presented about how the involved technologies are used to help system developers and users achieve better system performance through on-line repair and reconfiguration.

Researchers and practitioners in the area of parallel and distributed computing have been lacking a portable, flexible and robust distributed instrumentation system. This paper presents the reference implementation of Baseline Reduced Instrumentation System Kernel (BRISK). BRISK was developed as a part of a realtime system instrumentation and performance visualization project. The design is based on a simple distributed instrumentation system model for flexibility and extensibility. The basic implementation poses minimalistic system requirements and achieves high performance. The paper also shows evaluations of BRISK on both basic and advanced configurations. The first evaluation emphasizes local, simple performance metrics; and the second highlights aggregate performance, built-in clock synchronization and dynamic on-line sorting. Copyright © 2000 John Wiley & Sons, Ltd.

We present a compiler-based approach to the design and engineering of complex real-time systems. The systems are built from computation, communication and I/O subsystems, based on different extant real-time models and schemes. We have defined a high-level system specification language, called Real-Time System Markup Language (RTSML), for integration of model-specific subsystems. We have developed a prototype extensible compiler from RTSML to a Constraint Logic Programming (CLP) language. Model-specific compiler modules can be added that generate CLP code for subsystems based on the corresponding real-time models and schemes, and their integration with other subsystems of a complex real-time system being specified. We specify an example system consisting of dozens of communicating real-time tasks that share real-time computation and communication resources, and map it to two problem solving approaches. The first one is the conventional CLP search, while the second one is suitable for system reconfiguration when system parameters change dynamically. We compare the two approaches and present their timings for the example system. Based on the results obtained, and potentials of the software technologies used in our compiler-based approach, it appears promising for large-scale complex real-time systems.

Van Jacobson (VJ) TCP header compression significantly reduces TCP protocol overhead in a noiseless environment. Unfortunately, when the algorithm operates in error prone environments similar to wireless, the performance of the compressor drops to below that of not using header compression. This work describe modifications to the VJ algorithm that allow it to better tolerate errors. By removing many of the dependencies that are implicitly transmitted on the link, one is able to generate a noise tolerant VJ compressor. On noiseless links, the new algorithm shows similar performance to the original algorithm. On random or burst error channels, the new algorithm significantly outperforms the original.

In this paper we introduce a video smoothing algorithm for MPEG compressed live video. This algorithm, called pattern smoothing, transmits compressed video via both constant bit rate (CBR) and variable bit rate (VBR) channels. In order to take advantage of the gains achieved through statistical multiplexing of multiple sources over a single link, this algorithm utilizes a CBR channel to reduce the peak rate and variance of the VBR transmission. In addition to presenting this new algorithm, we compare it against three smoothing techniques presented in the literature. Key attributes used for comparison include receiver buffer size, live video support, startup delay, losslessness versus lossiness, and smoothing scale. Because network utilization is the most important performance metric for any smoothing algorithm, we provide a performance analysis of the pattern smoothing algorithm via simulation and compare these results to the best of the three presented smoothing algorithms.

Statistical gain is achieved in asynchronous transfer mode (ATM) networks by making bursty connections share resources stochastically. When connections with different QOS requirements share the same resources, the highest QOS requirements would typically be the limiting factor in determining the admissible load at a link. This may lead to connections with low QOS requirements getting better service than they require, leading to an underutilization of the resources. To alleviate this problem, a burst-level priority scheme is proposed. In the proposal, burst of related cells are to be handled in the network on a burst-by-burst basis. Bandwidth is allocated to bursts on-the-fly according to their priorities. This proposal includes a two-level priority CAC scheme for controlling the burst-level blocking rates of independent heterogeneous on-off sources.

ATM networks are intended to accommodate all traffic types, including highly bursty traffic. In this paper, we present a traffic control framework for handling bursty traffic on a burst-by-burst basis. The protocol and associated mechanisms are designed to handle bursts of related cells as units. Hence, cells in a burst are forwarded or dropped as a unit. The framework includes mechanisms to allow a connection to acquire resources at a switch when a burst arrives and to release them when a burst leaves. In addition, techniques for bundling such bursty connections into virtual paths are described. A candidate burst-oriented call admission control scheme is also presented. The performance of the burst-oriented approach is then analyzed.

As network capacities increase, wide-area distributed parallel computing may become feasible. This paper addresses one of the issues involved in using an asynchronous transfer mode (ATM) network for such a purpose that of developing an appropriate call admission control (CAC) procedure for such applications given the special nature of their traffic. In this proposal, connections belonging to the same application and sharing the same link are allowed to utilize the link bandwidth in a strongly correlated manner. However, connections belonging to different applications are still assumed to be independent. This allows the development of a tabular approach for keeping track of the aggregate bandwidth demand of the applications sharing the same link. The proposed approach is compared with two related approaches (one more conservative and another more aggressive) and is shown to strike a balance between utilization and loss rate.

The development of a unimodular transformation theory and associated algorithms has renewed interest in FORTRAN DO loops that are not perfectly (or tightly) nested. We summarize a number of techniques that convert imperfectly nested loops into perfectly nested loops. We examined over 25,000 lines of scientific FORTRAN kernels and benchmarks. Statistics are reported on how often imperfect loops occur and how effective two transformations (scalar forward substitution and loop distribution) are at converting imperfectly nested loops into perfectly nested loops. Further, we describe a compiler that integrates scalar forward substitution, loop distribution, and unimodular transformations while maintaining the basic philosophy of unimodular transformation theory. While our data indicate that imperfectly nested loops still present a problem, the compiler we describe is no more limited by perfectly nested loops than other restructuring compilers available today.>

The author analyzes workstation patterns in order to understand opportunities for exploiting idle capacity. This study is based on traces of users workstation activity in a university environment. It identifies two areas where enhancements can be made. One area is the ability of a manager of the shared capacity of a workstation cluster to schedule jobs with deadline constraints. This opportunity is the result of the ability to make good predictions of the time-varying amount of capacity that is available for sharing. A prediction strategy is developed that is shown to have only a small amount of error. For the second area of enhancement, it is shown that it is feasible to allocate partitions of workstations for specific periods. This aids those users who on occasion need exclusive access to several machines. The author examines the profile of periods during which exclusive access to partitions can be given, the rate that owners preempt users of partitions, and the distribution of interpreemption intervals.>

A system that considers users' deadlines when scheduling background jobs is described which will enhance the quality of the computing environments it serves by exploiting underutilized workstation capacity without interfering with an owner's local workstation stage. By developing and evaluating a simulation model of the structure, the author shows that this scheduler can effectively schedule jobs according to their deadline constraints to improve the quality of service for the users. In the proposed approach, adaptive techniques for estimating the amount of capacity available for sharing in a workstation cluster are combined with user supplied information of the expected demand of their jobs. The improvement in deadline miss ratio due to the proposed structure was evaluated by means of simulation. The scheduling structure showed improvements over a wide range of user loads and tightness of deadlines.>

The design, implementation, and performance of the Condor scheduling system, which operates in a workstation environment, are presented. The system aims to maximize the utilization of workstations with as little interference as possible between the jobs it schedules and the activities of the people who own workstations. It identifies idle workstations and schedules background jobs on them. When the owner of a workstation resumes activity at a station, Condor checkpoints the remote job running on the station and transfers it to another workstation. The system guarantees that the job will eventually complete, and that very little, if any, work will be performed more than once. A performance profile of the system is presented that is based on data accumulated from 23 stations during one month.>