Maximum Network Throughput Based on Distributed Algorithm for Rechargeable Wireless Sensor Networks
Demin Gao, Haifeng Lin, Fuquan Zhang and Yunfei Liu
As the most important features, energy can be replenished continually, and its storage capacity is limited for each sensor in rechargeable wireless sensor networks, which causes a node cannot be always beneficial to conserve energy when a network can harvest excessive energy from the environment. Therefore, surplus energy of a node can be utilized for strengthening packet delivery efficiency and improving network throughput. In this work, we propose a distributed algorithm to compute an optimal data generation rate that maximizes the network throughput, which is formulated as a linear programming problem. Considering it is NP-hard, a dual problem by introducing Lagrange multipliers is constructed, and subgradient algorithms are used to solve it in a distributed manner. The resulting algorithms have low computational complexity and are guaranteed to converge to an optimal data generation rate. The algorithms are illustrated by an example in which an optimum flow is computed for a network of randomly distributed nodes. Through extensive simulation and experiments, we demonstrate our algorithm is efficient to maximize network throughput in rechargeable wireless sensor networks.
Keywords: Wireless sensor networks; maximum throughput; optimization technique; linear programming; rechargeable-WSNs.