Comparative analysis of algorithms for tree structure restoration in sensor networks

Sensor networks would be usually used for the collection of measured data. In many cases, a tree structure is formed for data query, data dissemination and other operations. As sensor nodes fail, this underlying tree structure is impacted or, at the worst case, disabled. In this paper, we propose and compare three algorithms to restore the tree structure for sensor network under network dynamics. Two of the algorithms use global information at the base station (or sink), while the third uses only local information. Through simulations, we observe that the localized algorithm outperforms the two global algorithms in terms of communication cost, corresponding energy and latency. In addition, we also gain a deeper insight into the performance tradeoff for algorithms in sensor network. We clearly identify energy-latency tradeoff for the global algorithms, as well as energy-accuracy (optimality) tradeoff for the localized algorithm.