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36
Gossip algorithms for distributed signal processing
 PROCEEDINGS OF THE IEEE
, 2010
"... Gossip algorithms are attractive for innetwork processing in sensor networks because they do not require any specialized routing, there is no bottleneck or single point of failure, and they are robust to unreliable wireless network conditions. Recently, there has been a surge of activity in the co ..."
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Cited by 115 (29 self)
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Gossip algorithms are attractive for innetwork processing in sensor networks because they do not require any specialized routing, there is no bottleneck or single point of failure, and they are robust to unreliable wireless network conditions. Recently, there has been a surge of activity in the computer science, control, signal processing, and information theory communities, developing faster and more robust gossip algorithms and deriving theoretical performance guarantees. This paper presents an overview of recent work in the area. We describe convergence rate results, which are related to the number of transmittedmessages and thus the amount of energy consumed in the network for gossiping. We discuss issues related to gossiping over wireless links, including the effects of quantization and noise, and we illustrate the use of gossip algorithms for canonical signal processing tasks including distributed estimation, source localization, and compression.
Distributed ImageBased 3D Localization of Camera Sensor Networks
"... Abstract — We consider the problem of distributed estimation of the poses of N cameras in a camera sensor network using image measurements only. The relative rotation and translation (up to a scale factor) between pairs of neighboring cameras can be estimated using standard computer vision technique ..."
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Cited by 26 (4 self)
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Abstract — We consider the problem of distributed estimation of the poses of N cameras in a camera sensor network using image measurements only. The relative rotation and translation (up to a scale factor) between pairs of neighboring cameras can be estimated using standard computer vision techniques. However, due to noise in the image measurements, these estimates may not be globally consistent. We address this problem by minimizing a cost function on SE(3) N in a distributed fashion using a generalization of the classical consensus algorithm for averaging Euclidean data. We also derive a condition for convergence, which relates the stepsize of the consensus algorithm and the degree of the camera network graph. While our methods are designed with the camera sensor network application in mind, our results are applicable to other localization problems in a more general setting. We also provide synthetic simulations to test the validity of our approach. I.
Network Navigation: Theory and Interpretation
"... Abstract—Realtime and reliable location information of mobile nodes is a key enabler for many emerging wireless network applications. Such information can be obtained via network navigation, a new paradigm in which nodes exploit both spatial and temporal cooperation to infer their positions. In th ..."
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Cited by 13 (6 self)
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Abstract—Realtime and reliable location information of mobile nodes is a key enabler for many emerging wireless network applications. Such information can be obtained via network navigation, a new paradigm in which nodes exploit both spatial and temporal cooperation to infer their positions. In this paper, we establish a theoretical foundation for network navigation and determine the fundamental limits of navigation accuracy using equivalent Fisher information analysis. We then introduce the notion of carryover information and provide a geometrical interpretation for the evolution of navigation information. Our framework unifies the navigation information obtained from spatial and temporal cooperation, leading to a deep understanding of information evolution and cooperation benefits in navigation networks. Index Terms—Cooperative network, localization, navigation, CramérRao bound (CRB), equivalent Fisher information (EFI). I.
Robust power allocation for energyefficient locationaware networks
 IEEE/ACM Trans. Netw
"... Abstract—In wireless locationaware networks, mobile nodes (agents) typically obtain their positions using the range measurements to the nodes with known positions. Transmit power allocation not only affects network lifetime and throughput, but also determines localization accuracy. In this paper, ..."
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Cited by 11 (4 self)
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Abstract—In wireless locationaware networks, mobile nodes (agents) typically obtain their positions using the range measurements to the nodes with known positions. Transmit power allocation not only affects network lifetime and throughput, but also determines localization accuracy. In this paper, we present an optimization framework for robust power allocation in network localization with imperfect knowledge of network parameters. In particular, we formulate power allocation problems to minimize localization errors for a given power budget and show that such formulations can be solved via conic programming. Moreover, we design a distributed power allocation algorithm that allows parallel computation among agents. The simulation results show that the proposed schemes significantly outperform uniform power allocation, and the robust schemes outperform their nonrobust counterparts when the network parameters are subject to uncertainty. Index Terms—Localization, resource allocation, robust optimization, secondorder conic programming (SOCP), semidefinite programming (SDP), wireless networks. I.
Robust Localization of Nodes and TimeRecursive Tracking in Sensor Networks Using Noisy Range Measurements
"... Simultaneous localization and tracking (SLAT) in sensor networks aims to determine the positions of sensor nodes and a moving target in a network, given incomplete and inaccurate range measurements between the target and each of the sensors. One of the established methods for achieving this is to it ..."
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Cited by 10 (3 self)
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Simultaneous localization and tracking (SLAT) in sensor networks aims to determine the positions of sensor nodes and a moving target in a network, given incomplete and inaccurate range measurements between the target and each of the sensors. One of the established methods for achieving this is to iteratively maximize a likelihood function (ML) of positions given the observed ranges, which requires initialization with an approximate solution to avoid convergence towards local extrema. This paper develops methods for handling both Gaussian and Laplacian noise, the latter modeling the presence of outliers in some practical ranging systems that adversely affect the performance of localization algorithms designed for Gaussian noise. A modified Euclidean Distance Matrix (EDM) completion problem is solved for a block of target range measurements to approximately set up initial sensor/target positions, and the likelihood function is then iteratively refined through MajorizationMinimization (MM). To avoid the computational burden of repeatedly solving increasingly large EDM problems in timerecursive operation, an incremental scheme is exploited whereby a new target/node position is estimated from previously available node/target locations to set up the iterative ML initial point for the full spatial configuration. The above methods are first derived under Gaussian noise assumptions, and modifications for Laplacian noise are then considered. Analytically, the main challenges to overcome in the Laplacian case stem from the nondifferentiability of ℓ1 norms that arise in the various cost functions. Simulation results Copyright (c) 2011 IEEE. Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from the IEEE by sending a request to pubspermissions@ieee.org.
Simultaneous Localization of Multiple Unknown and Transient Radio Sources Using a Mobile Robot
"... Abstract—We report system and algorithm developments that utilize a single mobile robot to simultaneously localize multiple unknown transient radio sources. Because of signal source anonymity, short transmission durations, and dynamic transmission patterns, the robot cannot treat the radio sources ..."
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Cited by 4 (0 self)
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Abstract—We report system and algorithm developments that utilize a single mobile robot to simultaneously localize multiple unknown transient radio sources. Because of signal source anonymity, short transmission durations, and dynamic transmission patterns, the robot cannot treat the radio sources as continuous radio beacons. To deal with this challenging localization problem, we model the radio source behaviors using a novel spatiotemporal probability occupancy grid that captures transient characteristics of radio transmissions and tracks posterior probability distributions of radio sources. As a Monte Carlo method, a ridge walking motion planning algorithm is proposed to enable the robot to efficiently traverse the highprobability regions to accelerate the convergence of the posterior probability distribution. We also formally show that the time to find a radio source is insensitive to the number of radio sources, and hence, our algorithm has great scalability. We have implemented the algorithms and extensively tested them in comparison with two heuristic methods: a random walk and a fixedroute patrol. The localization time of our algorithms is consistently shorter than that of the two heuristic methods. Index Terms—Localization, networked robots, wireless sensor network. I.
Asymmetric Information Diffusion via Gossiping on Static And Dynamic Networks
"... Abstract — In this paper we consider the problem of gossiping in a network to diffuse the average of a subset of nodes, called sources, and directing it to another subset of nodes in the network called destinations. This case generalizes the typical average consensus gossiping policy, where all no ..."
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Cited by 3 (0 self)
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Abstract — In this paper we consider the problem of gossiping in a network to diffuse the average of a subset of nodes, called sources, and directing it to another subset of nodes in the network called destinations. This case generalizes the typical average consensus gossiping policy, where all nodes are both sources and destinations of the average of the nodes data. We first describe prior results we obtained on a static network topology and gossip policy, highlighting what conditions lead to the desired information flow. We show that, through semidirected flows, this formulation allows to solve the problem with lower complexity than using plain gossiping policies. Inspired by these results, we then move on to design algorithms to solve the problem in the dynamic case. For the dynamic network scenario we derive conditions under which the network converges to the desired result in the limit. We also provide policies that tradeoff accuracy with increased mixing speed for the dynamic asymmetric diffusion problem.
Wireless Body Area Network Node Localization Using SmallScale Spatial Information
, 2012
"... Deploying wireless body area networks (WBANs) in the longterm athome monitoring of a patient’s physiological and biokinetic conditions has become increasingly prevalent. However, such WBANs do not typically incorporate mechanisms to detect and correct for the possibility of accidentally switchin ..."
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Cited by 3 (0 self)
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Deploying wireless body area networks (WBANs) in the longterm athome monitoring of a patient’s physiological and biokinetic conditions has become increasingly prevalent. However, such WBANs do not typically incorporate mechanisms to detect and correct for the possibility of accidentally switching up wearable wireless sensor nodes (W2SNs), where a node assigned to one limb is placed on another, and viceversa, leading to possible incorrect prognoses from interpreting the data. In this thesis, we present a new scheme to automatically identify and verify the locations of W2SNs in a WBAN. Using smallscale geospatial information, instantaneous atmospheric air pressures at each node are examined and compared to map and match them in physical space. By enhancing the contextawareness of WBANs, this enhancement enables unassisted sensor node placement, providing a practical solution to obtain and continuously monitor node locations at a sufficient resolution to recognize limb
Minimum cost localization problem in wireless sensor networks,” Ad Hoc Networks
 J
"... Abstract—Localization is a fundamental problem in wireless sensor networks. Current localization algorithms mainly focus on checking the localizability of a network and/or how to localize as many nodes as possible given a static set of anchor nodes and distance measurements. In this paper, we study ..."
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Cited by 2 (1 self)
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Abstract—Localization is a fundamental problem in wireless sensor networks. Current localization algorithms mainly focus on checking the localizability of a network and/or how to localize as many nodes as possible given a static set of anchor nodes and distance measurements. In this paper, we study a new optimization problem, minimum cost localization problem, which aims to localize all sensors in a network using the minimum number (or total cost) of anchor nodes given the distance measurements. We show this problem is very challenging and then present a set of greedy algorithms using both trilateration and local sweep operations to address the problem. Extensive simulations have been conducted and demonstrate the efficiency of our algorithms. I.