Approximate Monitoring in Wireless Sensor Networks

In this paper, we develop an energy efficient approach to processing continuous aggregate queries in sensor networks with bounded quality constraints. Specifically, we exploit quality-aware in-network aggregation of query information to reduce communication costs. Given cluster structures over sensor nodes, we develop an adaptive approximate data processing protocol to aggregate data and process queries given error tolerance on user queries. The protocol enforces group quality constraints on clusters and adjusts error bounds to balance workload of clusters and reduce communication cost. It also tries to initiate local communication instead of global communication in the effort of minimizing overall communication overhead. Our experimental results indicate that significant benefits can be achieved by using our adaptive