Minimizing Communication Costs In Hierarchically Clustered Networks Of Wireless Sensors

This paper develops a technique for quantifying and minimizing the energy required to gather data from all sensors in a multi-hop wireless sensor network. The technique combines analytical results from stochastic geometry with a distributed, randomized algorithm for generating clusters. The minimum communication energy achieved by this approach is significantly lower than the energy costs incurred in non-clustered networks and in clustered networks produced by such algorithms as the Max-Min d-cluster Algorithm.