Minimum Transmission Power Configuration in Real-Time Wireless Sensor Networks

Multi-channel communications can effectively reduce channel competition and interferences in a wireless sensor network, and thus achieve increased throughput and improved end-to-end delay guarantees with reduced power consumption. However, existing work relies only on a small number of orthogonal channels, resulting in degraded performance when a large number of data flows need to be transmitted on different channels. In this thesis, empirical studies are conducted to investigate the interferences among overlapping channels. The results show that overlapping channels can also be utilized for improved real-time performance if the node transmission power is carefully configured. In order to minimize the overall power consumption of a network with multiple data flows under end-to-end delay constraints, a constrained optimization problem is formulated to configure the transmission power level for every node and assign overlapping channels to different data flows. Since the optimization problem has an exponential computational complexity, a heuristic algorithm designed based on Simulated Annealing is then presented to find a suboptimal solution. The extensive empirical results on a 25-mote testbed demonstrate that the proposed algorithm achieves better real-time performance and less power consumption than two baselines including a scheme using only orthogonal channels.