DMS-Based Energy Optimizations for Clustered WSNs

Abstract

In this article, we consider clustered wireless sensor networks where the nodes harvest energy from the environment. We target performance-sensitive applications that have to collectively send their information to a cluster head by a predefined deadline. The nodes are equipped with Dynamic Modulation Scaling (DMS)-capable wireless radios. DMS provides a tuning knob, allowing us to trade off communication latency with energy consumption. We consider two optimization objectives, maximizing total energy reserves and maximizing the minimum energy level across all nodes. For both objectives, we show that optimal solutions can be obtained by solving Mixed Integer Linear Programming problems. We also develop several fast heuristics that are shown to provide approximate solutions experimentally.