Performance Analysis of Average Consensus Algorithm without Reconfiguration of Edge Weights in Hybrid Wireless Sensor Networks

The integration of mobile sensor nodes with existing static nodes poses a significant technological shift to overcome the well-studied limitations of wireless sensor technologies. Over the recent years, it has been identified by many scientists that the application of data aggregation mechanisms can effectively compensate for negative factors affecting the operation of wireless sensor nodes. In this paper, we address the average consensus algorithm with a weight matrix guaranteeing the convergence without any reconfiguration of the edge weights in dynamically changing topologies whereby the data aggregation in mobile wireless sensor networks is significantly optimized in many aspects. Specifically, we examine the performance of the mentioned algorithm with bounded execution for distributed averaging over hybrid wireless sensor networks under various scenarios. Besides, we compare the performance of the algorithm over hybrid networks with its performance over mobile networks.