Joint Optimization of Data Routing and Energy Cooperation for Multicastive WPT assisted Data Collection in WSNs

Abstract

In Energy Harvesting assisted Wireless Sensor Networks (EH-WSNs), Wireless Power Transfer (WPT) technology plays a vital role in extending network lifespan by enabling energy cooperation among nodes. Nevertheless, existing energy cooperation assisted data collection methods mostly focused solely on Point-to-Point (P2P) style WPT, overlooking the broadcasting nature of wireless radio signals, which offers the potential for multiple nodes to harvest energy simultaneously from a single radio signal. To best exploit the multicastive radio signals, this paper concentrates on harnessing multicastive WPT-based energy cooperation for optimizing data collection performance in WSNs, and inspects the underlying joint optimization of Data Routing and Energy Cooperation for Data Collection (DREC-DC) problem. Here the term \textit{multicastive WPT} is used to distinguish from the P2P-style WPT considered in previous works. To overcome the scalability limitations of centralized solutions, we proposed an efficient Distributed method based on Projected Subgradient Algorithm (DPSA) by formulizing and transforming the single-slot version DREC-DC problem into a strict convex form. For situations where relevant information in some upcoming time slots are available ahead through predictions, DPSA is extended to a sliding window style multi-slot version. Our DPSA is compared with a P2P style energy cooperation approach and some classic routing algorithms not involving energy cooperation for assessing its effectiveness. Simulation results demonstrate that our distributive multicastive-WPT based method leads to considerably higher data collection ability than others.