Data aggregation in wireless sensor networks - exact and approximate algorithms

Abstract

A fundamental challenge in the design of wireless sensor networks (WSNs) is to maximize their lifetimes. Data aggregation has emerged as a basic approach in WSNs in order to reduce the number of transmissions of sensor nodes, and hence minimizing the overall power consumption in the network. We study optimal data aggregation in WSNs. Data aggregation is affected by several factors, such as the placement of aggregation points, the aggregation function, and the density of sensors in the network. The determination of an optimal selection of aggregation points is thus extremely important. We present exact and approximate algorithms to find the minimum number of aggregation points in order to maximize the network lifetime. Our algorithms use a fixed virtual wireless backbone that is built on top of the physical topology. We also study the tradeoffs between energy savings and the potential delay involved in the data aggregation process. Numerical results show that our approach provides substantial energy savings.