Analysis of energy-efficient, fair routing in wireless sensor networks through non-linear optimization

In the area of wireless sensor networks (WSN) there is still a significant gap between theory and practice: system designs and protocols are rapidly out-pacing analysis. We develop formal computational models of a WSN based on non-linear optimization and use them to analyze the impact of fairness constraints on network performance. The optimization framework presented is very general and can also be used to analyze the optimal performance of WSN subject to other design parameters such as the topology, number of nodes, energy levels, source rates, reception power, etc. Our results show that the maximum information that can be extracted for a fixed amount of energy increases and that the minimum energy required outputting a fixed amount of information decreases as we reduce the fairness requirement in the network. We present these functions for a fixed network topology and observe that they exhibit sharp changes in gradient due to qualitative changes in optimal routes.