Energy-aware Reprogramming of Sensor Networks Using Incremental Update and Compression

Reprogramming is an important issue in wireless sensor networks. It enables users to extend or correct functionality of a sensor network after deployment at a low cost. In this paper, we investigate the problem of improving energy efficiency and delay of reprogramming by using data compression and incremental updates. We analyze different algorithms for both approaches, as well as their combination, when applied to resource-constrained devices. Our results show that the classic Lempel-Ziv-77 compression algorithm with Bsdiff for delta encoding has the best overall performance compared to other compression algorithms; on average reducing energy usage by 74% and enabling 71% faster updates.