Showing papers in "IEEE Transactions on Mobile Computing in 2012"

Received-Signal-Strength-Based Indoor Positioning Using Compressive Sensing

Abstract: The recent growing interest for indoor Location-Based Services (LBSs) has created a need for more accurate and real-time indoor positioning solutions. The sparse nature of location finding makes the theory of Compressive Sensing (CS) desirable for accurate indoor positioning using Received Signal Strength (RSS) from Wireless Local Area Network (WLAN) Access Points (APs). We propose an accurate RSS-based indoor positioning system using the theory of compressive sensing, which is a method to recover sparse signals from a small number of noisy measurements by solving an `1-minimization problem. Our location estimator consists of a coarse localizer, where the RSS is compared to a number of clusters to detect in which cluster the node is located, followed by a fine localization step, using the theory of compressive sensing, to further refine the location estimation. We have investigated different coarse localization schemes and AP selection approaches to increase the accuracy. We also show that the CS theory can be used to reconstruct the RSS radio map from measurements at only a small number of fingerprints, reducing the number of measurements significantly. We have implemented the proposed system on a WiFi-integrated mobile device and have evaluated the performance. Experimental results indicate that the proposed system leads to substantial improvement on localization accuracy and complexity over the widely used traditional fingerprinting methods.

Mobile Data Offloading through Opportunistic Communications and Social Participation

Abstract: 3G networks are currently overloaded, due to the increasing popularity of various applications for smartphones. Offloading mobile data traffic through opportunistic communications is a promising solution to partially solve this problem, because there is almost no monetary cost for it. We propose to exploit opportunistic communications to facilitate information dissemination in the emerging Mobile Social Networks (MoSoNets) and thus reduce the amount of mobile data traffic. As a case study, we investigate the target-set selection problem for information delivery. In particular, we study how to select the target set with only k users, such that we can minimize the mobile data traffic over cellular networks. We propose three algorithms, called Greedy, Heuristic, and Random, for this problem and evaluate their performance through an extensive trace-driven simulation study. Our simulation results verify the efficiency of these algorithms for both synthetic and real-world mobility traces. For example, the Heuristic algorithm can offload mobile data traffic by up to 73.66 percent for a real-world mobility trace. Moreover, to investigate the feasibility of opportunistic communications for mobile phones, we implement a proof-of-concept prototype, called Opp-off, on Nokia N900 smartphones, which utilizes their Bluetooth interface for device/service discovery and content transfer.

Fast Data Collection in Tree-Based Wireless Sensor Networks

Abstract: We investigate the following fundamental question-how fast can information be collected from a wireless sensor network organized as tree? To address this, we explore and evaluate a number of different techniques using realistic simulation models under the many-to-one communication paradigm known as convergecast. We first consider time scheduling on a single frequency channel with the aim of minimizing the number of time slots required (schedule length) to complete a convergecast. Next, we combine scheduling with transmission power control to mitigate the effects of interference, and show that while power control helps in reducing the schedule length under a single frequency, scheduling transmissions using multiple frequencies is more efficient. We give lower bounds on the schedule length when interference is completely eliminated, and propose algorithms that achieve these bounds. We also evaluate the performance of various channel assignment methods and find empirically that for moderate size networks of about 100 nodes, the use of multifrequency scheduling can suffice to eliminate most of the interference. Then, the data collection rate no longer remains limited by interference but by the topology of the routing tree. To this end, we construct degree-constrained spanning trees and capacitated minimal spanning trees, and show significant improvement in scheduling performance over different deployment densities. Lastly, we evaluate the impact of different interference and channel models on the schedule length.

Target Tracking in Wireless Sensor Networks Based on the Combination of KF and MLE Using Distance Measurements

Abstract: A common technical difficulty in target tracking in a wireless sensor network is that individual homogeneous sensors only measure their distances to the target whereas the state of the target composes of its position and velocity in the Cartesian coordinates. That is, the senor measurements are nonlinear in the target state. Extended Kalman filtering is a commonly used method to deal with the nonlinearity, but this often leads to unsatisfactory or even unstable tracking performances. In this paper, we present a new target tracking approach which avoids the instability problem and offers superior tracking performances. We first propose an improved noise model which incorporates both additive noises and multiplicative noises in distance sensing. We then use a maximum likelihood estimator for prelocalization to remove the sensing nonlinearity before applying a standard Kalman filter. The advantages of the proposed approach are demonstrated via experimental and simulation results.

A Fade-Level Skew-Laplace Signal Strength Model for Device-Free Localization with Wireless Networks

Abstract: Device-free localization (DFL) is the estimation of the position of a person or object that does not carry any electronic device or tag. Existing model-based methods for DFL from RSS measurements are unable to locate stationary people in heavily obstructed environments. This paper introduces measurement-based statistical models that can be used to estimate the locations of both moving and stationary people using received signal strength (RSS) measurements in wireless networks. A key observation is that the statistics of RSS during human motion are strongly dependent on the RSS "fade level” during no motion. We define fade level and demonstrate, using extensive experimental data, that changes in signal strength measurements due to human motion can be modeled by the skew-Laplace distribution, with parameters dependent on the position of person and the fade level. Using the fade-level skew-Laplace model, we apply a particle filter to experimentally estimate the location of moving and stationary people in very different environments without changing the model parameters. We also show the ability to track more than one person with the model.

Modeling and Analysis for Spectrum Handoffs in Cognitive Radio Networks

Abstract: In this paper, we present an analytical framework to evaluate the latency performance of connection-based spectrum handoffs in cognitive radio (CR) networks. During the transmission period of a secondary connection, multiple interruptions from the primary users result in multiple spectrum handoffs and the need of predetermining a set of target channels for spectrum handoffs. To quantify the effects of channel obsolete issue on the target channel predetermination, we should consider the three key design features: 1) general service time distribution of the primary and secondary connections; 2) different operating channels in multiple handoffs; and 3) queuing delay due to channel contention from multiple secondary connections. To this end, we propose the preemptive resume priority (PRP) M/G/1 queuing network model to characterize the spectrum usage behaviors with all the three design features. This model aims to analyze the extended data delivery time of the secondary connections with proactively designed target channel sequences under various traffic arrival rates and service time distributions. These analytical results are applied to evaluate the latency performance of the connection-based spectrum handoff based on the target channel sequences mentioned in the IEEE 802.22 wireless regional area networks standard. Then, to reduce the extended data delivery time, a traffic-adaptive spectrum handoff is proposed, which changes the target channel sequence of spectrum handoffs based on traffic conditions. Compared to the existing target channel selection methods, this traffic-adaptive target channel selection approach can reduce the extended data transmission time by 35 percent, especially for the heavy traffic loads of the primary users.

Acknowledgment-Based Broadcast Protocol for Reliable and Efficient Data Dissemination in Vehicular Ad Hoc Networks

Abstract: We propose a broadcast algorithm suitable for a wide range of vehicular scenarios, which only employs local information acquired via periodic beacon messages, containing acknowledgments of the circulated broadcast messages. Each vehicle decides whether it belongs to a connected dominating set (CDS). Vehicles in the CDS use a shorter waiting period before possible retransmission. At time-out expiration, a vehicle retransmits if it is aware of at least one neighbor in need of the message. To address intermittent connectivity and appearance of new neighbors, the evaluation timer can be restarted. Our algorithm resolves propagation at road intersections without any need to even recognize intersections. It is inherently adaptable to different mobility regimes, without the need to classify network or vehicle speeds. In a thorough simulation-based performance evaluation, our algorithm is shown to provide higher reliability and message efficiency than existing approaches for nonsafety applications.

Protecting Location Privacy in Sensor Networks against a Global Eavesdropper

Abstract: While many protocols for sensor network security provide confidentiality for the content of messages, contextual information usually remains exposed Such contextual information can be exploited by an adversary to derive sensitive information such as the locations of monitored objects and data sinks in the field Attacks on these components can significantly undermine any network application Existing techniques defend the leakage of location information from a limited adversary who can only observe network traffic in a small region However, a stronger adversary, the global eavesdropper, is realistic and can defeat these existing techniques This paper first formalizes the location privacy issues in sensor networks under this strong adversary model and computes a lower bound on the communication overhead needed for achieving a given level of location privacy The paper then proposes two techniques to provide location privacy to monitored objects (source-location privacy)-periodic collection and source simulation-and two techniques to provide location privacy to data sinks (sink-location privacy)-sink simulation and backbone flooding These techniques provide trade-offs between privacy, communication cost, and latency Through analysis and simulation, we demonstrate that the proposed techniques are efficient and effective for source and sink-location privacy in sensor networks

Mining Spectrum Usage Data: A Large-Scale Spectrum Measurement Study

Abstract: Dynamic spectrum access has been a subject of extensive study in recent years. The increasing volume of literatures calls for a deeper understanding of the characteristics of current spectrum utilization. In this paper, we present a detailed spectrum measurement study, with data collected in the 20 MHz to 3 GHz spectrum band and at four locations concurrently in Guangdong province of China. We examine the statistics of the collected data, including channel vacancy statistics, channel utilization within each individual wireless service, and the spectral and spatial correlation of these measures. Main findings include that the channel vacancy durations follow an exponential-like distribution, but are not independently distributed over time, and that significant spectral and spatial correlations are found between channels of the same service. We then exploit such spectrum correlation to develop a 2D frequent pattern mining algorithm that can predict channel availability based on past observations with considerable accuracy.

Spectrum-Aware Mobility Management in Cognitive Radio Cellular Networks

Abstract: Cognitive radio (CR) networks have been proposed as a solution to both spectrum inefficiency and spectrum scarcity problems. However, they face several challenges based on the fluctuating nature of the available spectrum, making it more difficult to support seamless communications, especially in CR cellular networks. In this paper, a spectrum-aware mobility management scheme is proposed for CR cellular networks. First, a novel network architecture is introduced to mitigate heterogeneous spectrum availability. Based on this architecture, a unified mobility management framework is developed to support diverse mobility events in CR networks, which consists of spectrum mobility management, user mobility management, and intercell resource allocation. The spectrum mobility management scheme determines a target cell and spectrum band for CR users adaptively dependent on time-varying spectrum opportunities, leading to increase in cell capacity. In the user mobility management scheme, a mobile user selects a proper handoff mechanism so as to minimize a switching latency at the cell boundary by considering spatially heterogeneous spectrum availability. Intercell resource allocation helps to improve the performance of both mobility management schemes by efficiently sharing spectrum resources with multiple cells. Simulation results show that the proposed method can achieve better performance than conventional handoff schemes in terms of both cell capacity as well as mobility support in communications.

TV White Space in Europe

Abstract: In this paper, we study the availability of TV white spaces in Europe. Specifically, we focus on the 470-790 MHz UHF band, which will predominantly remain in use for TV broadcasting after the analog-to-digital switch-over and the assignment of the 800 MHz band to licensed services have been completed. The expected number of unused, available TV channels in any location of the 11 countries we studied is 56 percent when we adopt the statistical channel model of the ITU-R. Similarly, a person residing in these countries can expect to enjoy 49 percent unused TV channels. If, in addition, restrictions apply to the use of adjacent TV channels, these numbers reduce to 25 and 18 percent, respectively. These figures are significantly smaller than those recently reported for the United States. We also study how these results change when we use the Longley-Rice irregular terrain model instead. We show that while the overall expected availability of white spaces is essentially the same, the local variability of the available spectrum shows significant changes. This underlines the importance of using appropriate system models before making far-reaching conclusions.

ProSpect: A Proactive Spectrum Handoff Framework for Cognitive Radio Ad Hoc Networks without Common Control Channel

Abstract: Cognitive Radio (CR) technology is a promising solution to enhance the spectrum utilization by enabling unlicensed users to exploit the spectrum in an opportunistic manner. Since unlicensed users are temporary visitors to the licensed spectrum, they are required to vacate the spectrum when a licensed user reclaims it. Due to the randomness of the appearance of licensed users, disruptions to both licensed and unlicensed communications are often difficult to prevent, which may lead to low throughput of both licensed and unlicensed communications. In this paper, a proactive spectrum handoff framework for CR ad hoc networks, ProSpect, is proposed to address these concerns. In the proposed framework, Channel-Switching (CW) policies and a proactive spectrum handoff protocol are proposed to let unlicensed users vacate a channel before a licensed user utilizes it to avoid unwanted interference. Network coordination schemes for unlicensed users are also incorporated into the spectrum handoff protocol design. Moreover, a distributed channel selection scheme to eliminate collisions among unlicensed users in a multiuser spectrum handoff scenario is proposed. In our proposed framework, unlicensed users coordinate with each other without using a Common Control Channel (CCC), which is highly adaptable in a spectrum-varying environment. We compare our proposed proactive spectrum handoff protocol with a reactive spectrum handoff protocol, under which unlicensed users switch channels after collisions with licensed transmissions occur. Simulation results show that our proactive spectrum handoff outperforms the reactive spectrum handoff approach in terms of higher throughput and fewer collisions to licensed users. Furthermore, our distributed channel selection can achieve higher packet delivery rate in a multiuser spectrum handoff scenario, compared with existing channel selection schemes.

E-MiLi: Energy-Minimizing Idle Listening in Wireless Networks

Abstract: WiFi interface is known to be a primary energy consumer in mobile devices, and idle listening (IL) is the dominant source of energy consumption in WiFi. Most existing protocols, such as the 802.11 power-saving mode (PSM), attempt to reduce the time spent in IL by sleep scheduling. However, through an extensive analysis of real-world traffic, we found more than 60 percent of energy is consumed in IL, even with PSM enabled. To remedy this problem, we propose Energy-Minimizing idle Listening (E-MiLi) that reduces the power consumption in IL, given that the time spent in IL has already been optimized by sleep scheduling. Observing that radio power consumption decreases proportionally to its clock rate, E-MiLi adaptively downclocks the radio during IL, and reverts to full clock rate when an incoming packet is detected or a packet has to be transmitted. E-MiLi incorporates sampling rate invariant detection, ensuring accurate packet detection and address filtering even when the receiver's sampling clock rate is much lower than the signal bandwidth. Further, it employs an opportunistic downclocking mechanism to optimize the efficiency of switching clock rate, based on a simple interface to existing MAC-layer scheduling protocols. We have implemented E-MiLi on the USRP software radio platform. Our experimental evaluation shows that E-MiLi can detect packets with close to 100 percent accuracy even with downclocking by a factor of 16. When integrated with 802.11, E-MiLi can reduce energy consumption by around 44 percent for 92 percent of users in real-world wireless networks.

Compressed-Sensing-Enabled Video Streaming for Wireless Multimedia Sensor Networks

Abstract: This paper presents the design of a networked system for joint compression, rate control and error correction of video over resource-constrained embedded devices based on the theory of Compressed Sensing (CS). The objective of this work is to design a cross-layer system that jointly controls the video encoding rate, the transmission rate, and the channel coding rate to maximize the received video quality. First, compressed sensing-based video encoding for transmission over Wireless Multimedia Sensor Networks (WMSNs) is studied. It is shown that compressed sensing can overcome many of the current problems of video over WMSNs, primarily encoder complexity and low resiliency to channel errors. A rate controller is then developed with the objective of maintaining fairness among different videos while maximizing the received video quality. It is shown that the rate of Compressed Sensed Video (CSV) can be predictably controlled by varying only the compressed sensing sampling rate. It is then shown that the developed rate controller can be interpreted as the iterative solution to a convex optimization problem representing the optimization of the rate allocation across the network. The error resiliency properties of compressed sensed images and videos are then studied, and an optimal error detection and correction scheme is presented for video transmission over lossy channels. Finally, the entire system is evaluated through simulation and test bed evaluation. The rate controller is shown to outperform existing TCP-friendly rate control schemes in terms of both fairness and received video quality. The test bed results show that the rates converge to stable values in real channels.

Game-Theoretic Analysis of Cooperation Incentive Strategies in Mobile Ad Hoc Networks

Abstract: In mobile ad hoc networks (MANETs), tasks are conducted based on the cooperation of nodes in the networks. However, since the nodes are usually constrained by limited computation resources, selfish nodes may refuse to be cooperative. Reputation systems and price-based systems are two main solutions to the node noncooperation problem. A reputation system evaluates node behaviors by reputation values and uses a reputation threshold to distinguish trustworthy nodes and untrustworthy nodes. A price-based system uses virtual cash to control the transactions of a packet forwarding service. Although these two kinds of systems have been widely used, very little research has been devoted to investigating the effectiveness of the node cooperation incentives provided by the systems. In this paper, we use game theory to analyze the cooperation incentives provided by these two systems and by a system with no cooperation incentive strategy. We find that the strategies of using a threshold to determine the trustworthiness of a node in the reputation system and of rewarding cooperative nodes in the price-based system may be manipulated by clever or wealthy but selfish nodes. Illumined by the investigation results, we propose and study an integrated system. Theoretical and simulation results show the superiority of the integrated system over an individual reputation system and a price-based system in terms of the effectiveness of cooperation incentives and selfish node detection.

Principal Component Localization in Indoor WLAN Environments

Abstract: This paper presents a novel approach to building a WLAN-based location fingerprinting system. Our algorithm intelligently transforms received signal strength (RSS) into principal components (PCs) such that the information of all access points (APs) is more efficiently utilized. Instead of selecting APs, the proposed technique replaces the elements with a subset of PCs to simultaneously improve the accuracy and reduce the online computation. Our experiments are conducted in a realistic WLAN environment. The results show that the mean error is reduced by 33.75 percent, and the complexity by 40 percent, as compared to the existing methods. Moreover, several benefits of our algorithm are demonstrated, such as requiring fewer training samples and enhancing the robustness to RSS anomalies.

Mobile Ad Hoc Nanonetworks with Collision-Based Molecular Communication

Abstract: Recent developments in nanotechnology have enabled the fabrication of nanomachines with very limited sensing, computation, communication, and action capabilities. The network of communicating nanomachines is envisaged as nanonetworks that are designed to accomplish complex tasks such as drug delivery and health monitoring. For the realization of future nanonetworks, it is essential to develop novel and efficient communication and networking paradigms. In this paper, the first step toward designing a mobile ad hoc molecular nanonetwork (MAMNET) with electrochemical communication is taken. MAMNET consists of mobile nanomachines and infostations that share nanoscale information using electrochemical communication whenever they have a physical contact with each other. In MAMNET, the intermittent connectivity introduced by the mobility of nanomachines and infostations is a critical issue to be addressed. An analytical framework that incorporates the effect of mobility into the performance of electrochemical communication among nanomachines is presented. Using the analytical model, numerical analysis for the performance evaluation of MAMNET is obtained. Results reveal that MAMNET achieves adequately high throughput to enable frontier nanonetwork applications with acceptable communication latency.

MAC in Motion: Impact of Mobility on the MAC of Drive-Thru Internet

Abstract: The pervasive adoption of IEEE 802.11 radios in the past decade has made possible for the easy Internet access from a vehicle, notably drive-thru Internet. Originally designed for the static indoor applications, the throughput performance of IEEE 802.11 in the outdoor vehicular environment is, however, still unclear especially when a large number of fast-moving users transmitting simultaneously. In this paper, we investigate the performance of IEEE 802.11 DCF in the highly mobile vehicular networks. We first propose a simple yet accurate analytical model to evaluate the throughput of DCF in the large scale drive-thru Internet scenario. Our model incorporates the high-node mobility with the modeling of DCF and unveils the impacts of mobility (characterized by node velocity and moving directions) on the resultant throughput. Based on the model, we show that the throughput of DCF will be reduced with increasing node velocity due to the mismatch between the MAC and the transient high-throughput connectivity of vehicles. We then propose several enhancement schemes to adaptively adjust the MAC in tune with the node mobility. Extensive simulations are carried out to validate the accuracy of the developed analytical model and the effectiveness of the proposed enhancement schemes.

Avoiding the Rush Hours: WiFi Energy Management via Traffic Isolation

Abstract: WiFi continues to be a prime source of energy consumption in mobile devices. This paper observes that, despite a rich body of research in WiFi energy management, there is room for improvement. Our key finding is that WiFi energy optimizations have conventionally been designed with a single AP in mind. However, network contention among different APs can dramatically increase a client's energy consumption. Each client may have to keep awake for long durations before its own AP gets a chance to send it packets to it. As AP density increases, the waiting time inflates, resulting in a proportional decrease in battery life. We design SleepWell, a system that achieves energy efficiency by evading network contention. The APs regulate the sleeping window of their clients in a way that different APs are active/inactive during nonoverlapping time windows. The solution is analogous to the common wisdom of going late to office and coming back late, thereby avoiding the rush hours. We implement SleepWell on a testbed of eight Laptops and nine Android phones, and evaluate it over a wide variety of scenarios and traffic patterns. Results show a median gain of up to 2x when WiFi links are strong; when links are weak and the network density is high, the gains can be even more.

Two-Tiered Constrained Relay Node Placement in Wireless Sensor Networks: Computational Complexity and Efficient Approximations

Abstract: In wireless sensor networks, relay node placement has been proposed to improve energy efficiency. In this paper, we study two-tiered constrained relay node placement problems, where the relay nodes can be placed only at some prespecified candidate locations. To meet the connectivity requirement, we study the connected single-cover problem where each sensor node is covered by a base station or a relay node (to which the sensor node can transmit data), and the relay nodes form a connected network with the base stations. To meet the survivability requirement, we study the 2-connected double-cover problem where each sensor node is covered by two base stations or relay nodes, and the relay nodes form a 2-connected network with the base stations. We study these problems under the assumption that R \ge 2r > 0, where R and r are the communication ranges of the relay nodes and the sensor nodes, respectively. We investigate the corresponding computational complexities, and propose novel polynomial time approximation algorithms for these problems. Specifically, for the connected single-cover problem, our algorithms have {\cal O}(1)-approximation ratios. For the 2-connected double-cover problem, our algorithms have {\cal O}(1)-approximation ratios for practical settings and {\cal O}(\ln n)-approximation ratios for arbitrary settings. Experimental results show that the number of relay nodes used by our algorithms is no more than twice of that used in an optimal solution.

Duopoly Competition in Dynamic Spectrum Leasing and Pricing

Abstract: This paper presents a comprehensive analytical study of two competitive secondary operators' investment (ie, spectrum leasing) and pricing strategies, taking into account operators' heterogeneity in leasing costs and users' heterogeneity in transmission power and channel conditions We model the interactions between operators and users as a three-stage dynamic game, where operators simultaneously make spectrum leasing decisions in Stage I, and pricing decisions in Stage II, and then users make purchase decisions in Stage III Using backward induction, we are able to completely characterize the dynamic game's equilibria We show that both operators' investment and pricing equilibrium decisions process interesting threshold properties For example, when the two operators' leasing costs are close, both operators will lease positive spectrum Otherwise, one operator will choose not to lease and the other operator becomes the monopolist For pricing, a positive pure strategy equilibrium exists only when the total spectrum investment of both operators is less than a threshold Moreover, two operators always choose the same equilibrium price despite their heterogeneity in leasing costs Each user fairly achieves the same service quality in terms of signal-to-noise ratio (SNR) at the equilibrium, and the obtained predictable payoff is linear in its transmission power and channel gain We also compare the duopoly equilibrium with the coordinated case where two operators cooperate to maximize their total profit We show that the maximum loss of total profit due to operators' competition is no larger than 25 percent The users, however, always benefit from operators' competition in terms of their payoffs We show that most of these insights are robust in the general SNR regime

Toward Reliable Data Delivery for Highly Dynamic Mobile Ad Hoc Networks

Abstract: This paper addresses the problem of delivering data packets for highly dynamic mobile ad hoc networks in a reliable and timely manner. Most existing ad hoc routing protocols are susceptible to node mobility, especially for large-scale networks. Driven by this issue, we propose an efficient Position-based Opportunistic Routing (POR) protocol which takes advantage of the stateless property of geographic routing and the broadcast nature of wireless medium. When a data packet is sent out, some of the neighbor nodes that have overheard the transmission will serve as forwarding candidates, and take turn to forward the packet if it is not relayed by the specific best forwarder within a certain period of time. By utilizing such in-the-air backup, communication is maintained without being interrupted. The additional latency incurred by local route recovery is greatly reduced and the duplicate relaying caused by packet reroute is also decreased. In the case of communication hole, a Virtual Destination-based Void Handling (VDVH) scheme is further proposed to work together with POR. Both theoretical analysis and simulation results show that POR achieves excellent performance even under high node mobility with acceptable overhead and the new void handling scheme also works well.

Temporal Correlation of Interference in Wireless Networks with Rayleigh Block Fading

Abstract: The temporal correlation of interference is a key performance factor of several technologies and protocols for wireless communications. A comprehensive understanding of interference correlation is especially important in the design of diversity schemes, whose performance can severely degrade in case of highly correlated interference. Taking into account three sources of correlation-node locations, channel, and traffic-and using common modeling assumptions-random homogeneous node positions, Rayleigh block fading, and slotted ALOHA traffic-we derive closed-form expressions and calculation rules for the correlation coefficient of the overall interference power received at a certain point in space. Plots give an intuitive understanding as to how model parameters influence the interference correlation.

Monitoring breathing via signal strength in wireless networks

Abstract: Systems and methods are disclosed for the use of sensor links in a network to estimate the breathing rate of a breathing subject within a structure, estimate the location of the subject within the structure, and detect if the subject is breathing. The structure may be a bed, a building, or a room in the building. The received signal strength of the sensor links is obtained and is then used in various breathing models to determine the breathing rate estimation, the location estimation, and the breathing detection.

Tight Performance Bounds of Multihop Fair Access for MAC Protocols in Wireless Sensor Networks and Underwater Sensor Networks

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

Efficient Rendezvous Algorithms for Mobility-Enabled Wireless Sensor Networks

Abstract: Recent research shows that significant energy saving can be achieved in mobility-enabled wireless sensor networks (WSNs) that visit sensor nodes and collect data from them via short-range communications. However, a major performance bottleneck of such WSNs is the significantly increased latency in data collection due to the low movement speed of mobile base stations. To address this issue, we propose a rendezvous-based data collection approach in which a subset of nodes serve as rendezvous points that buffer and aggregate data originated from sources and transfer to the base station when it arrives. This approach combines the advantages of controlled mobility and in-network data caching and can achieve a desirable balance between network energy saving and data collection delay. We propose efficient rendezvous design algorithms with provable performance bounds for mobile base stations with variable and fixed tracks, respectively. The effectiveness of our approach is validated through both theoretical analysis and extensive simulations.

Cross-Layer Optimization of Correlated Data Gathering in Wireless Sensor Networks

Abstract: We consider the problem of gathering correlated sensor data by a single sink node in a wireless sensor network. We assume that the sensor nodes are energy constrained and design efficient distributed protocols to maximize the network lifetime. Many existing approaches focus on optimizing the routing layer only, but in fact the routing strategy is often coupled with power control in the physical layer and link access in the MAC layer. This paper represents a first effort on network lifetime maximization that jointly considers the three layers. We first assume that link access probabilities are known and consider the joint optimal design of power control and routing. We show that the formulated optimization problem is convex and propose a distributed algorithm, JRPA, for the solution. We also discuss the convergence of JRPA. When the optimal link access probabilities are unknown, as in many practical networks, we generalize the problem formulation to encompass all the three layers of routing, power control, and link-layer random access. In this case, the problem cannot be converted into a convex optimization problem, but there exists a duality gap when the Lagrangian dual method is employed. We propose an efficient heuristic algorithm, JRPRA, to solve the general problem, and show through numerical experiments that it can significantly narrow the gap between the computed and optimal solutions. Moreover, even without a priori knowledge of the best link access probabilities predetermined for JRPA, JRPRA achieves extremely competitive performance with JRPA. Beyond the metric of network lifetime, we also discuss how to solve the problem of correlated data gathering under general utility functions. Numerical results are provided to show the convergence of the algorithms and their advantages over existing solutions.

Improving QoS in High-Speed Mobility Using Bandwidth Maps

Abstract: It is widely evidenced that location has a significant influence on the actual bandwidth that can be expected from Wireless Wide Area Networks (WWANs), e.g., 3G. Because a fast-moving vehicle continuously changes its location, vehicular mobile computing is confronted with the possibility of significant variations in available network bandwidth. While it is difficult for providers to eliminate bandwidth disparity over a large service area, it may be possible to map network bandwidth to the road network through repeated measurements. In this paper, we report results of an extensive measurement campaign to demonstrate the viability of such bandwidth maps. We show how bandwidth maps can be interfaced with adaptive multimedia servers and the emerging vehicular communication systems that use on-board mobile routers to deliver Internet services to the passengers. Using simulation experiments driven by our measurement data, we quantify the improvement in Quality of Service (QoS) that can be achieved by taking advantage of the geographical knowledge of bandwidth provided by the bandwidth maps. We find that our approach reduces the frequency of disruptions in perceived QoS for both audio and video applications in high-speed vehicular mobility by several orders of magnitude.

Leveraging Smartphone Cameras for Collaborative Road Advisories

Abstract: Ubiquitous smartphones are increasingly becoming the dominant platform for collaborative sensing. Smartphones, with their ever richer set of sensors, are being used to enable collaborative driver-assistance services like traffic advisory and road condition monitoring. To enable such services, the smartphones' GPS, accelerometer, and gyro sensors have been widely used. On the contrary, smartphone cameras, despite being very powerful sensors, have largely been neglected. In this paper, we introduce a collaborative sensing platform that exploits the cameras of windshield-mounted smartphones. To demonstrate the potential of this platform, we propose several services that it can support, and prototype SignalGuru, a novel service that leverages windshield-mounted smartphones and their cameras to collaboratively detect and predict the schedule of traffic signals, enabling Green Light Optimal Speed Advisory (GLOSA) and other novel applications. Results from two deployments of SignalGuru, using iPhones in cars in Cambridge (MA, USA) and Singapore, show that traffic signal schedules can be predicted accurately. On average, SignalGuru comes within 0.66 s, for pretimed traffic signals and within 2.45 s, for traffic-adaptive traffic signals. Feeding SignalGuru's predicted traffic schedule to our GLOSA application, our vehicle fuel consumption measurements show savings of 20.3 percent, on average.

An Iterative Algorithm for Trust Management and Adversary Detection for Delay-Tolerant Networks

Abstract: Delay/Disruption Tolerant Networks (DTNs) have been identified as one of the key areas in the field of wireless communication, wherein sparseness and delay are particularly high. They are emerging as a promising technology in vehicular, planetary/interplanetary, military/tactical, disaster response, underwater and satellite networks. DTNs are characterized by large end-to-end communication latency and the lack of end-to-end path from a source to its destination. These characteristics pose several challenges to the security of DTNs. Especially, Byzantine attacks in which one or more legitimate nodes have been compromised and fully controlled by the adversary can give serious damages to the network in terms of latency and data availability. Using reputation-based trust management systems is shown to be an effective way to handle the adversarial behavior in Mobile Ad hoc Networks (MANETs). However, because of the unique characteristics of DTNs, those traditional techniques do not apply to DTNs. Our main objective in this paper is to develop a robust trust mechanism and an efficient and low cost malicious node detection technique for DTNs. Inspired by our recent results on reputation management for online systems and e-commerce, we develop an iterative malicious node detection mechanism for DTNs referred as ITRM. The proposed scheme is a graph-based iterative algorithm motivated by the prior success of message passing techniques for decoding low-density parity-check codes over bipartite graphs. Applying ITRM to DTNs for various mobility models, we observed that the proposed iterative reputation management scheme is far more effective than well-known reputation management techniques such as the Bayesian framework and EigenTrust. Further, we concluded that the proposed scheme provides high data availability and packet-delivery ratio with low latency in DTNs under various adversary attacks which attempt to both undermine the trust and detection scheme and the packet delivery protocol.