A prediction model of death probability for guiding wireless recharging in sensor networks. (23rd October 2021)

• Record Type: Journal Article
• Authors: Zhong, Ping; Xu, Aikun; Lin, Shu; Kui, Xiaoyan
• Is Part Of: International journal of sensor networks. Volume 37:Number 2(2021)
• Page Start: 125
• Page End: 139
• Publication Date: 2021-10-23
• Subjects: abnormal death -- MFQ -- Markov fluid queue -- WSN -- wireless sensor network -- WRSN -- wireless rechargeable sensor network -- WPT -- wireless power transmission -- WET -- wireless energy transmission; Sensor networks -- Periodicals; 681.2
• Languages: English
• ISSNs: 1748-1279

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.