The impact of spatial correlation on routing with compression in wireless sensor networks

Abstract

The efficacy of data aggregation in sensor networks is a function of the degree of spatial correlation in the sensed phenomenon. The recent literature has examined a variety of schemes that achieve greater data aggregation by routing data with regard to the underlying spatial correlation. A well known conclusion from these papers is that the nature of optimal routing with compression depends on the correlation level. In this article we show the existence of a simple, practical, and static correlation-unaware clustering scheme that satisfies a min-max near-optimality condition. The implication for system design is that a static correlation-unaware scheme can perform as well as sophisticated adaptive schemes for joint routing and compression.