A fully distributed algorithm for estimating the center and coverage region of a wireless sensor network (WSN) is proposed. The proposed algorithm is useful in many applications, such as finding the required power for a certain level of connectivity in WSNs and localizing a service center in a network. The network coverage region is defined to be the smallest sphere that covers all the sensor nodes. The center and radius of the smallest covering sphere are estimated. The center estimation is formulated as a convex optimization problem using soft-max approximation. Then, diffusion adaptation is used for distributed optimization to estimate the center. After all the sensors obtain the center estimates, max consensus is used to calculate the radius distributively. The performance analysis of the proposed algorithm is provided, as a function of a design parameter controls the trade-off between the center estimation error and the convergence speed of the algorithm. Simulation results are provided.

Last. Andreas Spanias(ASU: Arizona State University)H-Index: 32

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A distributed consensus algorithm for estimating the maximum value of the initial measurements in a sensor network with communication noise is proposed. In the absence of communication noise, max estimation can be done by updating the state value with the largest received measurements in every iteration at each sensor. In the presence of communication noise, however, the maximum estimate will incorrectly drift and the estimate at each sensor will diverge. As a result, a soft-max approximation to...

Last. Dong Xuan(OSU: Ohio State University)H-Index: 47

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In this paper, we study the problem of wireless coverage in bounded areas. Coverage is one of the fundamental requirements of wireless networks. There has been considerable research on optimal coverage of infinitely large areas. However, in the real world, the deployment areas of wireless networks are always geographically bounded. It is a much more challenging and significant problem to find optimal deployment patterns to cover bounded areas. In this paper, we approach this problem starting fro...

Dec 1, 2012 in GLOBECOM (Global Communications Conference)

#1Srabani Kundu(Guru Nanak Institute of Technology)H-Index: 2

#2Nabanita Das(ISI: Indian Statistical Institute)H-Index: 12

In many applications of Wireless Sensor Networks (WSN), a large number of sensor nodes are distributed over an area under investigation. The sensors collect ground data at definite time interval and forward it to the sink. In case of an event, it is often required to estimate the affected area and to identify the location of the event. Since, in WSN, communication is costlier than in-network computation in terms of energy, it is better if the area can be estimated in a distributed fashion on the...

In this paper, we address the problem of estimating the maximal value over a sensor network using wireless links between them. We introduce two heuristic algorithms and analyze their theoretical performance. More precisely, i) we prove that their convergence time is finite with probability one, ii) we derive an upper-bound on their mean convergence time, and iii) we exhibit a bound on their convergence time dispersion.

#1Jianshu Chen(UCLA: University of California, Los Angeles)H-Index: 28

#2Ali H. Sayed(UCLA: University of California, Los Angeles)H-Index: 86

We propose an adaptive diffusion mechanism to optimize global cost functions in a distributed manner over a network of nodes. The cost function is assumed to consist of a collection of individual components. Diffusion adaptation allows the nodes to cooperate and diffuse information in real-time; it also helps alleviate the effects of stochastic gradient noise and measurement noise through a continuous learning process. We analyze the mean-square-error performance of the algorithm in some detail,...

Last. Yuli Wang(CUHK: The Chinese University of Hong Kong)H-Index: 2

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Finding one of the smallest non-standard ellipse containing a given point set, is very useful in image and picture labeling. The paper presents an approach to seek the ellipse. The paper was not going to seek the equation of the ellipse, it solved the 5 elliptical parameters (the long axis a, the short axis b, the elliptical center and the rotation k) for determining the ellipse, instead. In order to reduce the problem complexity, the search of non-standard ellipse was turned into the standard e...

#1Chinh T. Vu(GSU: Georgia State University)H-Index: 8

#1C.T. Vu(GSU: Georgia State University)H-Index: 1

Last. Yingshu Li(GSU: Georgia State University)H-Index: 41

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In sensor networks, it is desired to conserve energy so that the network lifetime can be maximized. An efficient approach to prolong the network lifetime is to identify a schedule for all the sensors, indicating which subset of the sensors can be active during the current time slot. Furthermore, to ensure the quality of surveillance, some applications require k-coverage of the monitored area. In this paper, we first define the Sensor Energy-efficient Scheduling for k-coverage (SESK) problem. We ...

We study four distributed techniques for computing the area of a region in a sensor network. Area calculation is a fundamental sensor network primitive, and distributed, in-network approaches prove more scalable than centralized collection in terms of energy consumption. The four techniques—Delaunay triangulations, Voronoi diagrams, and two new, simpler algorithms, inverse neighborhood and inverse neighborhood with location—vary in computational complexity, communication cost, and information re...

#2Ramesh Govindan(SC: University of Southern California)H-Index: 102

A wireless sensor network that studies relatively widespread phenomena (such as a contaminant flow or a seismic disturbance) may be called upon to provide a description of the boundary of the phenomenon (either a contour or some bounding box). In such cases, it may be necessary for each node to locally determine whether it lies at (or near) the edge of the phenomenon. In this paper, we show that such localized edge detection techniques are non-trivial to design in an arbitrarily deployed sensor ...