Title: A prediction model of death probability for guiding wireless recharging in sensor networks

Authors: Ping Zhong; Aikun Xu; Shu Lin; Xiaoyan Kui

Addresses: School of Computer Science and Engineering, Central South University, Changsha, 410073, China ' School of Computer Science and Engineering, Central South University, Changsha, 410073, China ' School of Computer Science and Engineering, Central South University, Changsha, 410073, China ' School of Computer Science and Engineering, Central South University, Changsha, 410073, China

Abstract: Wireless power transmission (WPT) technology is usually used to maintain the continuous operation of sensor nodes. However, when large amounts of data need to be processed, the node may enter an abnormal death state because it cannot be charged in time. Therefore, a prediction of node death probability is crucial to guide the charging path planning for charging vehicles. In this paper, we build an analysis model based on a Markov fluid queue (MFQ) model with the aim of creating harvest-store-use (HSU) and harvest-then-use (HTU) models of the node. Specifically, the proposed models involve a Markov process, a queuing model, and a successive fluid process. The result shows that the abnormal death probability calculated by the model is approximately 0.1% different from the probability of death obtained by simulation. Meanwhile, by comparing the two modes of energy usage, we find that HTU is better than HSU.

Keywords: abnormal death; MFQ; Markov fluid queue; WSN; wireless sensor network; WRSN; wireless rechargeable sensor network; WPT; wireless power transmission; WET; wireless energy transmission.

DOI: 10.1504/IJSNET.2021.118489

International Journal of Sensor Networks, 2021 Vol.37 No.2, pp.125 - 139

Received: 03 Oct 2020
Accepted: 05 Feb 2021
Published online: 27 Oct 2021 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article