A scalable correlation aware aggregation strategy for wireless sensor networks

Yujie Zhu, Ramanuja Vedantham, Seung-Jong Park, Raghupathy Sivakumar

Abstract: Sensors-to-sink data in wireless sensor networks (WSNs) are typically correlated with each other. Exploiting such correlation when performing data aggregation can result in considerable improvements in the bandwidth and energy performance of WSNs. In order to exploit such correlation, we present a scalable and distributed correlation-aware aggregation structure that addresses the practical challenges in the context of aggregation in WSNs. Through simulations and analysis, we evaluate the performance of the proposed approach with centralized and distributed correlation aware and unaware structures.