Rebalancing Distributed Data Storage in Sensor Networks
Sensor networks are an emerging class of systems with significant potential. Recent paper has proposed a distributed data structure called DIM for efficient support of multi-dimensional range queries in sensor networks. The original DIM design works well with uniform data distributions. However, real world data distributions are often skewed. Skewed data distributions can result in storage and traffic hotspots in the original DIM design. In this paper, the authors present a novel distributed algorithm that alleviates hotspots in DIM caused by skewed data distributions.