Jeremy Elson and Deborah Estrin
Department of Computer Science, University of California, Los Angeles; and
USC/Information Sciences Institute
We show how this randomized scheme can significantly improve the system's energy efficiency in contexts where that efficiency is paramount, such as energy-constrained wireless sensor networks. Benefits are realized if the typical data size is small compared to the size of an identifier, and the number of transactions seen by an individual node is small compared to the number of nodes that exist in the entire system. Our scheme is designed to scale well: identifier sizes grow with a system's density, not its overall size. We quantify these benefits using an analytic model that predicts our scheme's efficiency. We also describe an implementation as applied to packet fragmentation and an experiment that validates our model.