Research On Real-time Task Scheduling Strategy For Energy Planning In Wirelessly Powered Sensing System

The wirelessly powered sensing system(WSS)get rid of the shortcomings of traditional Io T nodes relying on batteries,can convert radio frequency signals in the environment into energy for self-power supply,and greatly improve their own endurance.The wirelessly powered sensing system consists of multiple wirelessly powered sensing platforms.However,compared with traditional Io T nodes,the wirelessly powered sensing platform have many differences in energy acquisition methods and energy efficiency.Although the wirelessly powered sensing platform can obtain energy from the RF signal,the energy efficiency is not high and the problem of insufficient available energy often occurs,which affects the execution of real-time tasks and greatly reduces the performance of the real-time system in the wirelessly powered sensing platform,so the traditional real-time task scheduling algorithm cannot be used directly.Therefore,it is necessary to further understand the energy model of the wirelessly powered sensing system.At the same time,it is urgent and important to study the real-time task scheduling algorithm based on its own energy model based.In order to solve the above problems,this article fully considers the characteristics of the wirelessly powered sensing system and does the following work:(1)In order to solve the problem that the FRIIS energy propagation model is susceptible to signal attenuation and multipath effects,this paper adds loss factors and attenuation factors to optimize the FRIIS energy propagation model from the perspective of a mathematical model;At the same time,in order to obtain a more accurate communication distance,solve the problem that the RSSI(Received Signal Strength Indication)value is susceptible to environmental interference,this paper designs a WSSF(Wirelessly powered Sensing System Filtering)filtering algorithm suitable for RSSI.The algorithm combines Gaussian filtering,median filtering and Kalman filtering to process RSSI data.Experiments show that the algorithm can obtain a more accurate communication distance.Finally,a charging model suitable for the wirelessly powered sensing system is proposed.And this paper improve the energy model of the wirelessly powered sensing platform.(2)In order to the non-overloaded state,the wirelessly powered sensing platform can schedule real-time tasks more reasonably and make full use of idle time to supplement energy.Based on the EDF(Early Deadline First)algorithm and the wirelessly powered sensing platform energy model,this paper proposes dynamics task scheduling algorithm suitable for the wirelessly powered sensing system named WEDF(Wirelessly powered EDF).The algorithm combines energy model,slack time and other factors to reasonably allocate tasks so that each node of the wirelessly powered sensing system gets more charging time.Simultaneously WEDF increase the alarm function.When the data is found abnormal,the wirelessly powered sensing platform shorten the task execution cycle and speed up the collection sample rate,so as to achieve timely monitoring of the environment.It can be known through simulation experiments that the algorithm increases the idle time of the wirelessly powered sensing platform,alleviates the energy shortage of the wirelessly powered sensing system,and increases the successful execution rate of the tasks;(3)In the overload state,in order to rationally use limited system resources to schedule realtime tasks and obtain higher system benefits,this paper designs a dynamic preemption task scheduling algorithm named Wirelessly Powered Dynamic Real-time Transaction Scheduling(WDRTS)suitable for the wirelessly powered sensing system based on the proposed dynamic assignment task priority strategy and the dynamic assignment platform priority strategy.This algorithm combines the dynamic assignment task priority strategy and the dynamic assignment platform priority strategy to complete the scheduling assignment of real-time tasks,which effectively increases the scheduling capability of the wirelessly powered system.And through theoretical derivation,the algorithm sets the bump factor,which alleviates the bump problem and reduces the waste of resources in the wirelessly powered system due to repeated preemption problems.Finally,through simulation experiments,we can know that compared with DVD(Dynamic Value Density)and other algorithms,the WDRTS algorithm can effectively alleviate the repeated preemption between tasks,reduce the false intercept rate of real-time tasks,and increase the benefits obtained by the wirelessly powered sensing system in the case of heavy system load.In summary,the method designed in this paper meets the characteristics and needs of the wirelessly powered sensing system,and effectively improves the performance and success rate of real-time task scheduling.