Distributed Clustering Algorithms for Lossy Wireless Sensor Networks

Recent experimental studies have revealed that a large percentage of wireless links are lossy and unreliable for data delivery in wireless sensor networks (WSNs). Such findings raise new challenges for the design of clustering algorithms in WSNs in terms of data reliability and energy efficiency. In this paper, we propose distributed clustering algorithms for WSNs by taking into account of the lossy nature of wireless links. We first formulate the one-hop clustering problem that maintains reliability as well as saves energy into an integer program and prove its NP-hardness. We then propose a metric-based distributed clustering algorithm to solve the problem. We adopt a metric called selection weight for each sensor node that can indicate both link qualities around the node and its capability of being a cluster head. We further extend the algorithm to multi-hop clustering to achieve better scalability. Extensive simulations have been conducted under a realistic link model and the results demonstrate that the proposed clustering algorithm can reduce the total energy consumption in the network and prolong network lifetime significantly compared to a typical distributed clustering algorithm, HEED, that does not consider lossy links.