Distributed Monitoring and Aggregation in Wireless Sensor Networks

Self-monitoring the sensor statuses such as liveness, node density and residue energy is critical for maintaining the normal operation of the sensor network. When building the monitoring architecture, most existing work focuses on minimizing the number of monitoring nodes. However, with less monitoring points, the false alarm rate may increase as a consequence. In this paper, we study the fundamental tradeoff between the number of monitoring nodes and the false alarm rate in the wireless sensor networks. Specifically, we propose fully distributed monitoring algorithms, to build up a poller-pollee based architecture with the objective to minimize the number of overall pollers while bounding the false alarm rate. Based on the established monitoring architecture, we further explore the hop-by-hop aggregation opportunity along the multihop path from the polee to the poller, with the objective to minimize the monitoring overhead. We show that the optimal aggregation path problem is NP-hard and propose an opportunistic greedy algorithm, which achieves an approximation ratio of 5/4. As far as we know, this is the first proved constant approximation ratio applied to the aggregation path selection schemes over the wireless sensor networks.