A new link weight factor in backpressure scheduling algorithm for energy-efficient design of Smart Wireless Sensor Networks

Abstract

In Smart Wireless Sensor Networks, it is imperative to utilize the most power efficient techniques to prolong the lifetime of a sensor node. Backpressure based scheduling has a remarkable performance for smart WSNs, and it has been discussed extensively in literatures. However, considering the energy efficiency of Backpressure scheduling algorithms for recourse-constrained smart WSNs is still need to be studied in order to design smart WSNs with minimum energy consumption. Unlike previous works for Backpressure scheduling algorithms, in this paper we propose a novel Multi-Factors Backpressure Scheduling (MFBS) algorithm which focuses on introducing new link-weights for energy efficient scheduling in smart WSNs. In MFBS, besides queue backlog differentials which is the common scheduling method in the classical Backpressure algorithm, nodal residual energy as well as the shortest path between neighbors (nodes) are also jointly considered into the transmission scheduling decision. Based on the results of our extensive simulation which is proven by the equivalent theoretical analysis, MFBS shows a significant improvement in the network performance of smart WSNs in terms of the network lifetime, the throughput, the queue length and the energy-efficiency in comparison with existing algorithms such as the classical backpressure algorithm and enhanced dynamic backpressure routing algorithm.