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We consider the approximate sparse recovery problem in multi-hop Wireless Sensor Networks (WSNs) using Compressed Sensing/Compressive Sampling (CS). The goal is to recover the n-dimensional data values by querying only mnsensors based on some linear projection of sensor readings. To solve this problem, a distributed compressive sparse sampling(DCSS) algorithm is proposed based on sparse binary CSmeasurement...
Identifying codes have been proposed as an abstraction for implementing monitoring tasks such as indoor localization using wireless sensor networks. In this approach, sensors' radio coverage overlaps in unique ways over each identifiable region, according to the codewords of an identifying code. While connectivity of the underlying identifying code is necessary for routing data to a sink, existing...
In this paper, we propose a new multiple-sink positioning problem in wireless sensor networks to best support real-time applications. We formally define this problem as the -Sink Placement Problem ( -SPP) and prove that it is APX-complete. We show that an existing approximation algorithm for the well-known -center problem is a constant factor approximation of -SPP. Furthermore, we introduce...
We consider an optimization problem in wireless sensor networks (WSNs) that is to find a multicast tree with maximum lifetime. While a recently proposed distributed algorithm for this problem guarantees to obtain optimal solutions, its high message complexity may prevent such contribution from being practically used in resource-constrained WSNs. In this paper, we proposed a new distributed algorithm...
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