Showing papers in "IEEE Transactions on Mobile Computing in 2011"

BUBBLE Rap: Social-Based Forwarding in Delay-Tolerant Networks

Abstract: The increasing penetration of smart devices with networking capability form novel networks Such networks, also referred as pocket switched networks (PSNs), are intermittently connected and represent a paradigm shift of forwarding data in an ad hoc manner The social structure and interaction of users of such devices dictate the performance of routing protocols in PSNs To that end, social information is an essential metric for designing forwarding algorithms for such types of networks Previous methods relied on building and updating routing tables to cope with dynamic network conditions On the downside, it has been shown that such approaches end up being cost ineffective due to the partial capture of the transient network behavior A more promising approach would be to capture the intrinsic characteristics of such networks and utilize them in the design of routing algorithms In this paper, we exploit two social and structural metrics, namely centrality and community, using real human mobility traces The contributions of this paper are two-fold First, we design and evaluate BUBBLE, a novel social-based forwarding algorithm, that utilizes the aforementioned metrics to enhance delivery performance Second, we empirically show that BUBBLE can substantially improve forwarding performance compared to a number of previously proposed algorithms including the benchmarking history-based PROPHET algorithm, and social-based forwarding SimBet algorithm

Bidirectionally Coupled Network and Road Traffic Simulation for Improved IVC Analysis

Abstract: Recently, many efforts have been made to develop more efficient Inter-Vehicle Communication (IVC) protocols for on-demand route planning according to observed traffic congestion or incidents, as well as for safety applications. Because practical experiments are often not feasible, simulation of network protocol behavior in Vehicular Ad Hoc Network (VANET) scenarios is strongly demanded for evaluating the applicability of developed network protocols. In this work, we discuss the need for bidirectional coupling of network simulation and road traffic microsimulation for evaluating IVC protocols. As the selection of a mobility model influences the outcome of simulations to a great extent, the use of a representative model is necessary for producing meaningful evaluation results. Based on these observations, we developed the hybrid simulation framework Veins (Vehicles in Network Simulation), composed of the network simulator OMNeT++ and the road traffic simulator SUMO. In a proof-of-concept study, we demonstrate its advantages and the need for bidirectionally coupled simulation based on the evaluation of two protocols for incident warning over VANETs. With our developed methodology, we can advance the state-of-the-art in performance evaluation of IVC and provide means to evaluate developed protocols more accurately.

See-Through Walls: Motion Tracking Using Variance-Based Radio Tomography Networks

Abstract: This paper presents a new method for imaging, localizing, and tracking motion behind walls in real time. The method takes advantage of the motion-induced variance of received signal strength measurements made in a wireless peer-to-peer network. Using a multipath channel model, we show that the signal strength on a wireless link is largely dependent on the power contained in multipath components that travel through space containing moving objects. A statistical model relating variance to spatial locations of movement is presented and used as a framework for the estimation of a motion image. From the motion image, the Kalman filter is applied to recursively track the coordinates of a moving target. Experimental results for a 34-node through-wall imaging and tracking system over a 780 square foot area are presented.

Cognitive Medium Access: Exploration, Exploitation, and Competition

Abstract: This paper considers the design of efficient strategies that allow cognitive users to choose frequency bands to sense and access among multiple bands with unknown parameters. First, the scenario in which a single cognitive user wishes to opportunistically exploit the availability of frequency bands is considered. By adopting tools from the classical bandit problem, optimal as well as low complexity asymptotically optimal solutions are developed. Next, the multiple cognitive user scenario is considered. The situation in which the availability probability of each channel is known is first considered. An optimal symmetric strategy that maximizes the total throughput of the cognitive users is developed. To avoid the possible selfish behavior of the cognitive users, a game-theoretic model is then developed. The performance of both models is characterized analytically. Then, the situation in which the availability probability of each channel is unknown a priori is considered. Low-complexity medium access protocols, which strike an optimal balance between exploration and exploitation in such competitive environments, are developed. The operating points of these low-complexity protocols are shown to converge to those of the scenario in which the availability probabilities are known. Finally, numerical results are provided to illustrate the impact of sensing errors and other practical considerations.

Rendezvous for Cognitive Radios

Abstract: Cognitive radios have been touted as a solution to communicating in a Dynamic Spectrum Access environment. This paper examines how cognitive radios initially find one another among the expanse of ever-changing open spectrum, termed the rendezvous problem. Specifically, it addresses the problem of rendezvous under varying levels of system capabilities, spectrum policies, and environmental conditions. The focus is on rendezvous when there are are no control channels or centralized controllers, which we term the blind rendezvous problem. Under these conditions, a sequence-based and modular clock blind rendezvous algorithms are proposed, and it is shown that the performance of these algorithms compares favorably to that of a random blind rendezvous algorithm. Specifically, the sequence-based algorithm provides a bounded Time To Rendezvous (TTR) and the ability to prioritize channels where rendezvous is more likely to occur; the modular clock algorithm reduces the expected TTR, requires little precoordination among radios attempting to rendezvous, and is robust to radios sensing different sets of available channels.

Scalable Localization with Mobility Prediction for Underwater Sensor Networks

Abstract: Due to harsh aqueous environments, non-negligible node mobility and large network scale, localization for large-scale mobile underwater sensor networks is very challenging. In this paper, by utilizing the predictable mobility patterns of underwater objects, we propose a scheme, called Scalable Localization scheme with Mobility Prediction (SLMP), for underwater sensor networks. In SLMP, localization is performed in a hierarchical way, and the whole localization process is divided into two parts: anchor node localization and ordinary node localization. During the localization process, every node predicts its future mobility pattern according to its past known location information, and it can estimate its future location based on the predicted mobility pattern. Anchor nodes with known locations in the network will control the localization process in order to balance the trade-off between localization accuracy, localization coverage, and communication cost. We conduct extensive simulations, and our results show that SLMP can greatly reduce localization communication cost while maintaining relatively high localization coverage and localization accuracy.

Efficient Data Collection in Wireless Sensor Networks with Path-Constrained Mobile Sinks

Abstract: Recent work has shown that sink mobility along a constrained path can improve the energy efficiency in wireless sensor networks. However, due to the path constraint, a mobile sink with constant speed has limited communication time to collect data from the sensor nodes deployed randomly. This poses significant challenges in jointly improving the amount of data collected and reducing the energy consumption. To address this issue, we propose a novel data collection scheme, called the Maximum Amount Shortest Path (MASP), that increases network throughput as well as conserves energy by optimizing the assignment of sensor nodes. MASP is formulated as an integer linear programming problem and then solved with the help of a genetic algorithm. A two-phase communication protocol based on zone partition is designed to implement the MASP scheme. We also develop a practical distributed approximate algorithm to solve the MASP problem. In addition, the impact of different overlapping time partition methods is studied. The proposed algorithms and protocols are validated through simulation experiments using OMNET++.

MAP: Multiauctioneer Progressive Auction for Dynamic Spectrum Access

Abstract: Cognitive radio (CR) is a promising paradigm to achieve efficient utilization of the limited spectrum resource by allowing the unlicensed users to access the licensed spectrum, and dynamic spectrum access (DSA) is one of the fundamental functions of CR networks. Market-driven spectrum auction has been recognized as an effective way to achieve DSA. In spectrum auction, the primary spectrum owners (POs) act as auctioneers who are willing to sell idle spectrum bands for additional revenue, and the secondary users (SUs) act as bidders who are willing to buy spectrum bands from POs for their services. However, conventional spectrum auction designs are restricted within the scenario of single auctioneer. In this paper, we study the spectrum auction with multiple auctioneers and multiple bidders, which is more realistic for practical CR networks. We propose MAP, a Multiauctioneer Progressive auction mechanism, in which each auctioneer systematically raises the trading price and each bidder subsequently chooses one auctioneer for bidding. The equilibrium is defined as the state that no auctioneer and bidder would like to change his decision. We show analytically that MAP converges to the equilibrium with maximum spectrum utilization of the whole system. We further analyze the incentive for POs and SUs joining the auction and accepting the auction result. Simulation results show that MAP well converges to the equilibrium, and the spectrum utilization is arbitrary closed to the global optimal solution according to the length of step.

A Spectrum Decision Framework for Cognitive Radio Networks

Abstract: Cognitive radio networks have been proposed as a solution to both spectrum inefficiency and spectrum scarcity problems. However, they face to a unique challenge based on the fluctuating nature of heterogeneous spectrum bands as well as the diverse service requirements of various applications. In this paper, a spectrum decision framework is proposed to determine a set of spectrum bands by considering the application requirements as well as the dynamic nature of spectrum bands. To this end, first, each spectrum is characterized by jointly considering primary user activity and spectrum sensing operations. Based on this, a minimum variance-based spectrum decision is proposed for real-time applications, which minimizes the capacity variance of the decided spectrum bands subject to the capacity constraints. For best-effort applications, a maximum capacity-based spectrum decision is proposed where spectrum bands are decided to maximize the total network capacity. Moreover, a dynamic resource management scheme is developed to coordinate the spectrum decision adaptively dependent on the time-varying cognitive radio network capacity. Simulation results show that the proposed methods provide efficient bandwidth utilization while satisfying service requirements.

Secret Key Establishment Using Temporally and Spatially Correlated Wireless Channel Coefficients

Abstract: When implementing data encryption and decryption in a symmetric cryptosystem, secure distribution of the secret key to legitimate nodes can be a challenge. In this paper, we consider establishing secret keys using the common wireless channel, with particular emphasis on the spatial and temporal correlations of the channel coefficients. Specifically, we investigate the influence of channel correlation on the bound of the key size generated from the common channel using a simple single-input single-output channel model, and we verify the existence of a sampling approach able to generate a key using the minimum possible sampling window. We also explore decorrelation of the channel coefficients in a multiple-input multiple-output channel, and we use a statistical independence test to demonstrate that this process cannot be separated into spatial and temporal decorrelation processes. The insights gained from these studies assist in the development of a practical key generation protocol based on a published channel coefficient quantization method and incorporating flexible quantization levels, transmission of the correlation eigenvector matrix, and LDPC coding to improve key agreement in an authenticated public channel. Finally, we present simulations with real channel measurements that solidify the fundamental conclusions.

Investment and Pricing with Spectrum Uncertainty: A Cognitive Operator's Perspective

Abstract: This paper studies the optimal investment and pricing decisions of a cognitive mobile virtual network operator (C-MVNO) under spectrum supply uncertainty. Compared with a traditional MVNO who often leases spectrum via long-term contracts, a C-MVNO can acquire spectrum dynamically in short-term by both sensing the empty “spectrum holes” of licensed bands and dynamically leasing from the spectrum owner. As a result, a C-MVNO can make flexible investment and pricing decisions to match demands of the secondary unlicensed users. Compared to dynamic spectrum leasing, spectrum sensing is typically cheaper, but the obtained useful spectrum amount is random due to primary licensed users' stochastic traffic. The C-MVNO needs to determine the optimal amounts of spectrum sensing and leasing by evaluating the trade-off between cost and uncertainty. The C-MVNO also needs to determine the optimal price to sell the spectrum to the secondary unlicensed users, taking into account wireless heterogeneity of users such as different maximum transmission power levels and channel gains. We model and analyze the interactions between the C-MVNO and secondary unlicensed users as a Stackelberg game. We show several interesting properties of the network equilibrium, including threshold structures of the optimal investment and pricing decisions, the independence of the optimal price on users' wireless characteristics, and guaranteed fair and predictable QoS among users. We prove that these properties hold for general SNR regime and general continuous distributions of sensing uncertainty. We show that spectrum sensing can significantly improve the C-MVNO's expected profit and users' payoffs.

ALARM: Anonymous Location-Aided Routing in Suspicious MANETs

Abstract: In most common mobile ad hoc networking (MANET) scenarios, nodes establish communication based on long-lasting public identities. However, in some hostile and suspicious settings, node identities must not be exposed and node movements should be untraceable. Instead, nodes need to communicate on the basis of their current locations. While such MANET settings are not very common, they do occur in military and law enforcement domains and require high security and privacy guarantees. In this paper, we address a number of issues arising in suspicious location-based MANET settings by designing and analyzing a privacy-preserving and secure link-state based routing protocol (ALARM). ALARM uses nodes' current locations to securely disseminate and construct topology snapshots and forward data. With the aid of advanced cryptographic techniques (e.g., group signatures), ALARM provides both security and privacy features, including node authentication, data integrity, anonymity, and untraceability (tracking-resistance). It also offers protection against passive and active insider and outsider attacks. To the best of our knowledge, this work represents the first comprehensive study of security, privacy, and performance tradeoffs in the context of link-state MANET routing.

Anticollision Protocols for Single-Reader RFID Systems: Temporal Analysis and Optimization

Abstract: One of the major challenges in the use of Radio Frequency-based Identification (RFID) on a large scale is the ability to read a large number of tags quickly. Central to solving this problem is resolving collisions that occur when multiple tags reply to the query of a reader. To this purpose, several MAC protocols for passive RFID systems have been proposed. These typically build on traditional MAC schemes, such as aloha and tree-based protocols. In this paper, we propose a new performance metric by which to judge these anticollision protocols: time system efficiency. This metric provides a direct measure of the time taken to read a group of tags. We then evaluate a set of well-known RFID MAC protocols in light of this metric. Based on the insights gained, we propose a new anticollision protocol, and show that it significantly outperforms previously proposed mechanisms.

Sweep Coverage with Mobile Sensors

Abstract: Many efforts have been made for addressing coverage problems in sensor networks. They fall into two categories, full coverage and barrier coverage, featured as static coverage. In this work, we study a new coverage scenario, sweep coverage, which differs with the previous static coverage. In sweep coverage, we only need to monitor certain points of interest (POIs) periodically so the coverage at each POI is time-variant, and thus we are able to utilize a small number of mobile sensors to achieve sweep coverage among a much larger number of POIs. We investigate the definitions and model for sweep coverage. Given a set of POIs and their sweep period requirements, we prove that determining the minimum number of required sensors (min-sensor sweep-coverage problem) is NP-hard, and it cannot be approximated within a factor of 2. We propose a centralized algorithm with constant approximation ratio 3 for the min-sensor sweep-coverage problem. We further characterize the nonlocality of the problem and design a distributed sweep algorithm, DSWEEP, cooperating sensors to provide efficiency with the best effort. We conduct extensive simulations to study the performance of the proposed algorithms. Our simulations show that DSWEEP outperforms the randomized scheme in both effectiveness and efficiency.

Hedonic Coalition Formation for Distributed Task Allocation among Wireless Agents

Abstract: Autonomous wireless agents such as unmanned aerial vehicles, mobile base stations, cognitive devices, or self-operating wireless nodes present a great potential for deployment in next-generation wireless networks. While current literature has been mainly focused on the use of agents within robotics or software engineering applications, this paper proposes a novel usage model for self-organizing agents suitable for wireless communication networks. In the proposed model, a number of agents are required to collect data from several arbitrarily located tasks. Each task represents a queue of packets that require collection and subsequent wireless transmission by the agents to a central receiver. The problem is modeled as a hedonic coalition formation game between the agents and the tasks that interact in order to form disjoint coalitions. Each formed coalition is modeled as a polling system consisting of a number of agents, designated as collectors, which move between the different tasks present in the coalition, collect and transmit the packets. Within each coalition, some agents might also take the role of a relay for improving the packet success rate of the transmission. The proposed hedonic coalition formation algorithm allows the tasks and the agents to take distributed decisions to join or leave a coalition, based on the achieved benefit in terms of effective throughput, and the cost in terms of polling system delay. As a result of these decisions, the agents and tasks structure themselves into independent disjoint coalitions which constitute a Nash-stable network partition. Moreover, the proposed coalition formation algorithm allows the agents and tasks to adapt the topology to environmental changes, such as the arrival of new tasks, the removal of existing tasks, or the mobility of the tasks. Simulation results show how the proposed algorithm allows the agents and tasks to self-organize into independent coalitions, while improving the performance, in terms of average player (agent or task) payoff, of at least 30.26 percent (for a network of five agents with up to 25 tasks) relatively to a scheme that allocates nearby tasks equally among agents.

Model and Protocol for Energy-Efficient Routing over Mobile Ad Hoc Networks

Abstract: Many minimum energy (energy-efficient) routing protocols have been proposed in recent years. However, very limited effort has been made in studying routing overhead, route setup time, and route maintenance issues associated with these protocols. Without a careful design, an energy-efficient routing protocol can perform much worse than a normal routing protocol. In this paper, we first show that the minimum energy routing schemes in the literature could fail without considering the routing overhead involved and node mobility. We then propose a more accurate analytical model to track the energy consumptions due to various factors, and a simple energy-efficient routing scheme PEER to improve the performance during path discovery and in mobility scenarios. Our simulation results indicate that compared to a conventional energy-efficient routing protocol, PEER protocol can reduce up to 2/3 path discovery overhead and delay, and 50 percent transmission energy consumption.

MUSTER: Adaptive Energy-Aware Multisink Routing in Wireless Sensor Networks

Abstract: Wireless sensor networks (WSNs) are increasingly proposed for applications characterized by many-to-many communication, where multiple sources report their data to multiple sinks. Unfortunately, mainstream WSN collection protocols are generally designed to account for a single sink and, dually, WSN multicast protocols optimize communication from a single source. In this paper, we present MUSTER, a routing protocol expressly designed for many-to-many communication. First, we devise an analytical model to compute, in a centralized manner, the optimal solution to the problem of simultaneously routing from multiple sources to multiple sinks. Next, we illustrate heuristics approximating the optimal solution in a distributed setting, and their implementation in MUSTER. To increase network lifetime, MUSTER minimizes the number of nodes involved in many-to-many routing and balances their forwarding load. We evaluate MUSTER in emulation and in a real WSN testbed. Results indicate that our protocol builds near-optimal routing paths, doubles the WSN lifetime, and overall delivers to the user 2.5 times the amount of raw data w.r.t. mainstream protocols. Moreover, MUSTER is intrinsically amenable to in-network aggregation, pushing the improvements up to a 180 percent increase in lifetime and a four-time increase in data yield.

Strictly Localized Sensor Self-Deployment for Optimal Focused Coverage

Abstract: We consider sensor self-deployment problem, constructing FOCUSED coverage (F-coverage) around a Point of Interest (POI), with novel evaluation metric, coverage radius. We propose to deploy sensors in polygon layers over a locally computable equilateral triangle tessellation (TT) for optimal F-coverage formation, and introduce two types of deployment polygon, H-polygon and C-polygon. We propose two strictly localized solution algorithms, Greedy Advance (GA), and Greedy-Rotation-Greedy (GRG). The two algorithms drive sensors to move along the TT graph to surround POI. In GA, nodes greedily proceed as close to POI as they can; in GRG, when their greedy advance is blocked, nodes rotate around POI along locally computed H- or C-polygon to a vertex where greedy advance can resume. We prove that they both yield a connected network with maximized hole-free area coverage. To our knowledge, they are the first localized sensor self-deployment algorithms that provide such coverage guarantee. We further analyze their coverage radius property. Our study shows that GRG guarantees optimal or near optimal coverage radius. Through extensive simulation we as well evaluate their performance on convergence time, energy consumption, and node collision.

The Capacity of Wireless Ad Hoc Networks Using Directional Antennas

Abstract: Considering a disk of unit area with n nodes, we investigate the capacity of wireless networks using directional antennas. First, we study the throughput capacity of random directional networks with multihop relay schemes, and find that the capacity gain compared to random omnidirectional networks is O(log n), which is tighter than previous results. We also show that using directional antennas can significantly reduce power consumption in the networks. Second, for the first time, we explore the throughput capacity of random directional networks with one-hop relay schemes. Interestingly and against our intuition, we find that one-hop instead of multihop delivery schemes can make random directional networks scale. Third, we investigate the trade-offs between transmission range and throughput in random directional networks and show that using larger transmission range can result in higher throughput. Finally, we present a lower bound on the transport capacity of arbitrary directional networks, and find that without side lobe directional antenna gain, arbitrary directional networks can also scale.

Dynamic Switching-Based Data Forwarding for Low-Duty-Cycle Wireless Sensor Networks

Abstract: In this work, we introduce the concept of Dynamic Switch-based Forwarding (DSF) that optimizes the 1) expected data delivery ratio, 2) expected communication delay, or 3) expected energy consumption for low-duty-cycle wireless sensor networks under unreliable communication links. DSF is designed for networks with possibly unreliable communication links and predetermined node communication schedules. To our knowledge, these are the most encouraging results to date in this new research direction. In this paper, DSF is evaluated with a theoretical analysis, extensive simulation, and physical testbed consisting of 20 MicaZ motes. Results reveal the remarkable advantage of DSF in extremely low-duty-cycle sensor networks in comparison to three well-known solutions (ETX [1], PRR × D [2], and DESS [3]). We also demonstrate our solution defaults into ETX in always-awake networks and DESS in perfect-link networks.

Breath: An Adaptive Protocol for Industrial Control Applications Using Wireless Sensor Networks

Abstract: An energy-efficient, reliable and timely data transmission is essential for Wireless Sensor Networks (WSNs) employed in scenarios where plant information must be available for control applications. To reach a maximum efficiency, cross-layer interaction is a major design paradigm to exploit the complex interaction among the layers of the protocol stack. This is challenging because latency, reliability, and energy are at odds, and resource-constrained nodes support only simple algorithms. In this paper, the novel protocol Breath is proposed for control applications. Breath is designed for WSNs where nodes attached to plants must transmit information via multihop routing to a sink. Breath ensures a desired packet delivery and delay probabilities while minimizing the energy consumption of the network. The protocol is based on randomized routing, medium access control, and duty-cycling jointly optimized for energy efficiency. The design approach relies on a constrained optimization problem, whereby the objective function is the energy consumption and the constraints are the packet reliability and delay. The challenging part is the modeling of the interactions among the layers by simple expressions of adequate accuracy, which are then used for the optimization by in-network processing. The optimal working point of the protocol is achieved by a simple algorithm, which adapts to traffic variations and channel conditions with negligible overhead. The protocol has been implemented and experimentally evaluated on a testbed with off-the-shelf wireless sensor nodes, and it has been compared with a standard IEEE 802.15.4 solution. Analytical and experimental results show that Breath is tunable and meets reliability and delay requirements. Breath exhibits a good distribution of the working load, thus ensuring a long lifetime of the network. Therefore, Breath is a good candidate for efficient, reliable, and timely data gathering for control applications.

Optimal Channel Access Management with QoS Support for Cognitive Vehicular Networks

Abstract: We consider the problem of optimal channel access to provide quality of service (QoS) for data transmission in cognitive vehicular networks. In such a network, the vehicular nodes can opportunistically access the radio channels (referred to as shared-use channels) which are allocated to licensed users. Also, they are able to reserve a channel for dedicated access (referred to as exclusive-use channel) for data transmission. A channel access management framework is developed for cluster-based communication among vehicular nodes. This framework has three components: opportunistic access to shared-use channels, reservation of exclusive-use channel, and cluster size control. A hierarchical optimization model is then developed for this framework to obtain the optimal policy. The objective of the optimization model is to maximize the utility of the vehicular nodes in a cluster and to minimize the cost of reserving exclusive-use channel while the QoS requirements of data transmission (for vehicle-to-vehicle and vehicle-to-roadside communications) are met, and also the constraint on probability of collision with licensed users is satisfied. This hierarchical optimization model comprises of two constrained Markov decision process (CMDP) formulations - one for opportunistic channel access, and the other for joint exclusive-use channel reservation and cluster size control. An algorithm is presented to solve this hierarchical optimization model. Performance evaluation results show the effectiveness of the optimal channel access management policy. The proposed optimal channel access management framework will be useful to support mobile computing and intelligent transportation system (ITS) applications in vehicular networks.

OFDM-Based Common Control Channel Design for Cognitive Radio Ad Hoc Networks

Abstract: Cognitive radio (CR) technology allows devices to opportunistically use the vacant portions of the licensed wireless spectrum. However, the available spectrum changes dynamically with the primary user (PU) activity, necessitating frequent PU sensing coordination and exchanging network topology information in a multihop CR ad hoc network. To facilitate these tasks, an always-on, out-of-band common control channel (CCC) design is proposed that uses noncontiguous OFDM subcarriers placed within the guard bands separating the channels of the licensed spectrum. First, the task of choosing the OFDM-specific parameters, including the number, power, and bandwidth of the subcarriers is formulated as a feasibility problem to ensure that the CCC does not adversely interfere with the PU operation. Second, for unicast messaging between a given pair of users, a subset of the guard bands may be chosen, which allows an additional measure of protection for the adjacent PU spectrum. For this, the multiarm bandit algorithm is used that allows the guard band selection to evolve over time based on the observed interference from the PU. Results reveal that our proposed CCC ensures connectivity and improved PU protection with a limited trade-off in data rate when compared to frequency-hopping and cluster-based CCC schemes.

Maximizing Capacity in Multihop Cognitive Radio Networks under the SINR Model

Abstract: Cognitive radio networks (CRNs) have the potential to utilize spectrum efficiently and are positioned to be the core technology for the next-generation multihop wireless networks. An important problem for such networks is its capacity. We study this problem for CRNs in the SINR (signal-to-interference-and-noise-ratio) model, which is considered to be a better characterization of interference (but also more difficult to analyze) than disk graph model. The main difficulties of this problem are two-fold. First, SINR is a nonconvex function of transmission powers; an optimization problem in the SINR model is usually a nonconvex program and NP-hard in general. Second, in the SINR model, scheduling feasibility and the maximum allowed flow rate on each link are determined by SINR at the physical layer. To maximize capacity, it is essential to follow a cross-layer approach, but joint optimization at physical (power control), link (scheduling), and network (flow routing) layers with the SINR function is inherently difficult. In this paper, we give a mathematical characterization of the joint relationship among these layers. We devise a solution procedure that provides a (1- \varepsilon ) optimal solution to this complex problem, where \varepsilon is the required accuracy. Our theoretical result offers a performance benchmark for any other algorithms developed for practical implementation. Using numerical results, we demonstrate the efficacy of the solution procedure and offer quantitative understanding on the interaction of power control, scheduling, and flow routing in a CRN.

Fast Detection of Mobile Replica Node Attacks in Wireless Sensor Networks Using Sequential Hypothesis Testing

Abstract: Due to the unattended nature of wireless sensor networks, an adversary can capture and compromise sensor nodes, make replicas of them, and then mount a variety of attacks with these replicas. These replica node attacks are dangerous because they allow the attacker to leverage the compromise of a few nodes to exert control over much of the network. Several replica node detection schemes have been proposed in the literature to defend against such attacks in static sensor networks. However, these schemes rely on fixed sensor locations and hence do not work in mobile sensor networks, where sensors are expected to move. In this work, we propose a fast and effective mobile replica node detection scheme using the Sequential Probability Ratio Test. To the best of our knowledge, this is the first work to tackle the problem of replica node attacks in mobile sensor networks. We show analytically and through simulation experiments that our scheme detects mobile replicas in an efficient and robust manner at the cost of reasonable overheads.

Secure Cooperative Sensing in IEEE 802.22 WRANs Using Shadow Fading Correlation

Abstract: Cooperative (or distributed) sensing has been recognized as a viable means to enhance the incumbent signal detection by exploiting the diversity of sensors. However, it is challenging to secure such distributed sensing due mainly to the unique features of dynamic spectrum access networks-openness of low-layer protocol stacks in software-defined radio devices and the absence of interactions/coordination between primary and secondary devices. To meet this challenge, we propose an attack-tolerant distributed sensing protocol (ADSP) for DTV signal detection in IEEE 802.22 WRANs, under which sensors in close proximity are grouped as a cluster, and sensors within a cluster cooperate to safeguard the integrity of sensing. The heart of ADSP is a novel filter based on shadow-fading correlation, by which the fusion center cross-validates reports from the sensors to identify and penalize abnormal sensing reports. By realizing this correlation filter, ADSP significantly reduces the impact of an attack on the performance of distributed sensing, while incurring minimal processing and communication overheads. ADSP also guarantees the detectability requirements of 802.22 to be met even with the presence of sensing report manipulation attacks by scheduling sensing within the framework of sequential hypothesis testing. The efficacy of ADSP is validated on a realistic 2D shadow-fading field. Our extensive simulation-based study shows that ADSP reduces the false-alarm rate by 99.2 percent while achieving 97.4 percent of maximum achievable detection rate, and meets the detection requirements of IEEE 802.22 in various attack scenarios.

A Cooperative Clustering Protocol for Energy Saving of Mobile Devices with WLAN and Bluetooth Interfaces

Abstract: One of the most widely used wireless communication standards is a Wireless Local Area Network (WLAN) (IEEE 802.11). However, WLAN has a serious power consumption problem. In this paper, we propose a novel energy saving approach that exploits the multiradio feature of recent mobile devices equipped with WLAN and Bluetooth interfaces. Unlike previous approaches, our work is based on clustering. In our work, a cluster is a Bluetooth Personal Area Network (PAN), which consists of one cluster head and several regular nodes. The cluster head acts as a gateway between the PAN and the WLAN, enabling the regular nodes to access the WLAN infrastructure via low-power Bluetooth. We present a distributed clustering protocol, Cooperative Networking protocol (CONET), which dynamically reforms clusters according to each node's bandwidth requirement, energy use, and application type. CONET does not require modifications of existing wireless infrastructures because clustering is performed independently of WLAN access points. We implemented the CONET prototype with four wearable computing devices to evaluate the performance on real hardware. We also simulated CONET for large networks of more than 100 mobile nodes. Both results demonstrate that our approach is effective in reducing the power consumption of WLAN.

Traffic-Differentiation-Based Modular QoS Localized Routing for Wireless Sensor Networks

Abstract: A new localized quality of service (QoS) routing protocol for wireless sensor networks (WSN) is proposed in this paper. The proposed protocol targets WSN's applications having different types of data traffic. It is based on differentiating QoS requirements according to the data type, which enables to provide several and customized QoS metrics for each traffic category. With each packet, the protocol attempts to fulfill the required data-related QoS metric(s) while considering power efficiency. It is modular and uses geographical information, which eliminates the need of propagating routing information. For link quality estimation, the protocol employs distributed, memory and computation efficient mechanisms. It uses a multisink single-path approach to increase reliability. To our knowledge, this protocol is the first that makes use of the diversity in data traffic while considering latency, reliability, residual energy in sensor nodes, and transmission power between nodes to cast QoS metrics as a multiobjective problem. The proposed protocol can operate with any medium access control (MAC) protocol, provided that it employs an acknowledgment (ACK) mechanism. Extensive simulation study with scenarios of 900 nodes shows the proposed protocol outperforms all comparable state-of-the-art QoS and localized routing protocols. Moreover, the protocol has been implemented on sensor motes and tested in a sensor network testbed.

Security Games for Vehicular Networks

Abstract: Vehicular networks (VANETs) can be used to improve transportation security, reliability, and management. This paper investigates security aspects of VANETs within a game-theoretic framework where defensive measures are optimized with respect to threats posed by malicious attackers. The formulations are chosen to be abstract on purpose in order to maximize applicability of the models and solutions to future systems. The security games proposed for vehicular networks take as an input centrality measures computed by mapping the centrality values of the car networks to the underlying road topology. The resulting strategies help locating most valuable or vulnerable points (e.g., against jamming) in vehicular networks. Thus, optimal deployment of traffic control and security infrastructure is investigated both in the static (e.g., fixed roadside units) and dynamic cases (e.g., mobile law enforcement units). Multiple types of security games are studied under varying information availability assumptions for the players, leading to fuzzy game and fictitious play formulations in addition to classical zero-sum games. The effectiveness of the security game solutions is evaluated numerically using realistic simulation data obtained from traffic engineering systems.

A Privacy-Preserving Location Monitoring System for Wireless Sensor Networks

Abstract: Monitoring personal locations with a potentially untrusted server poses privacy threats to the monitored individuals. To this end, we propose a privacy-preserving location monitoring system for wireless sensor networks. In our system, we design two in-network location anonymization algorithms, namely, resource and quality-aware algorithms, that aim to enable the system to provide high-quality location monitoring services for system users, while preserving personal location privacy. Both algorithms rely on the well-established k-anonymity privacy concept, that is, a person is indistinguishable among k persons, to enable trusted sensor nodes to provide the aggregate location information of monitored persons for our system. Each aggregate location is in a form of a monitored area A along with the number of monitored persons residing in A, where A contains at least k persons. The resource-aware algorithm aims to minimize communication and computational cost, while the quality-aware algorithm aims to maximize the accuracy of the aggregate locations by minimizing their monitored areas. To utilize the aggregate location information to provide location monitoring services, we use a spatial histogram approach that estimates the distribution of the monitored persons based on the gathered aggregate location information. Then, the estimated distribution is used to provide location monitoring services through answering range queries. We evaluate our system through simulated experiments. The results show that our system provides high-quality location monitoring services for system users and guarantees the location privacy of the monitored persons.