Proactive Power Optimization of Sensor Networks

We propose a reduced-complexity genetic algorithm for dynamic deployment of resource constrained multi-hop mobile sensor networks. The goal of this paper is to achieve optimal coverage and improved battery life using dynamic power scaling (DPS) and improved fitness function. DPS exploits idle times, packet delay guarantees, performance and workload data using additional controls related to sensor power states and transmission power. The dynamic power scaling in conjunction with genetic algorithm jointly optimizes power states and topologies by dynamically monitoring workloads, packet arrivals, utilization data and quality-of-service compliance. This results in minimization of the power consumption of the sensor system while maximizing the sensor objectives.