5 research outputs found

    A Dependable Slepian-Wolf Coding Based Clustering Algorithm for Data Aggregation in Wireless Sensor Networks

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    International audienceThis paper considers the Slepian-Wolf coding based data aggregation problem and the corresponding dependable clustering problem in wireless sensor networks (WSNs). A dependable Slepian-Wolf coding based clustering (DSWC) algorithm is proposed to provide dependable clustering against cluster-head failures. The proposed D-SWC algorithm attempts to elect a primary cluster head and a backup cluster head for each cluster member during clustering so that once a failure occurs to the primary cluster head the cluster members within the failed cluster can promptly switchover to the backup cluster head and thus recover the connectivity of the failed cluster to the data sink without waiting for the next-round clustering to be performed. Simulation results show that the DSWC algorithm can effectively increase the amount of data transmitted to the data sink as compared with an existing nondependable clustering algorithm for Slepian-Wolf coding based data aggregation in WSNs

    A dependable Slepian-Wolf coding based clustering algorithm for data aggregation in wireless sensor networks

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    An Architecture for Robust Sensor Network Communications

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    Node clustering in sensor networks increases scalability, robustness, and energy-efficiency. In hostile environments, unexpected failures or attacks on cluster heads (through which communication takes place) may partition the network or degrade application performance. We propose REED (Robust Energy-Efficient Distributed clustering), for clustering sensors deployed in hostile environments in an interleaved manner with low complexity. Our primary objective is to construct a k-faulttolerant (i.e., k-connected) clustered network, where k is a constant determined by the application. Fault tolerance is achieved by selecting k independent sets of cluster heads (i.e., cluster head overlays) on top of the physical network, so that each node can quickly switch to other cluster heads in case of failures. The independent cluster head overlays also give multiple vertex-disjoint routing paths for load balancing and security. Network lifetime is prolonged by selecting cluster heads with high residual energy and low communication cost, and periodically re-clustering the network. We prove that REED asymptotically achieves k-connectivity if certain conditions on node density are met. We also discuss inter-cluster routing and MAC layer considerations, and investigate REED clustering properties via extensive simulations
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