PSO-based Hybrid Algorithm for Multi-objective TDMA Scheduling in Wireless Sensor Networks
Wireless microsensors are being used to form large, dense networks for the purposes of long-term environmental sensing and data collection. Unfortunately, these networks are typically deployed in remote environments where energy sources are limited. Thus, designing fault-tolerant wireless microsensor networks with long system lifetimes can be challenging. By applying energy-efficient techniques at all levels of the system hierarchy, system lifetime can be extended. In this paper, energy-efficient techniques that adapt underlying communication parameters will be presented in the context of wireless microsensor networks. In particular, the effect of adapting link and physical layer parameters, such as output transmit power and error control coding, on system energy consumption will be examined.