Delay and Energy Consumption Oriented UAV Inspection Business Collaboration Computing Mechanism in Edge Computing Based Electric Power IoT  

作　　者：SHAO Sujie LI Yi GUO Shaoyong WANG Chenhui CHEN Xingyu QIU Xuesong 

机构地区：[1]State Key Laboratory of Networking and Switching Technology,Beijing University of Posts and Telecommunications,Beijing 100876,China [2]Blockchain Research Department,China Electronics Standardization Institute,Beijing 100007,China

出　　处：《Chinese Journal of Electronics》2023年第1期13-25,共13页电子学报（英文版）

基　　金：supported by the National Natural Science Foundation of China (62071070);Test Bed Construction of Industrial Internet Platform in Specific Scenes (New Mode)。

摘　　要：With the development of Internet of things(IoT) technology and smart grid infrastructure,edge computing has become an effective solution to meet the delay requirements of the electric power IoT.Due to the limitation of battery capacity and data transmission mode of IoT terminals,the business collaboration computing must consider the energy consumption of the terminals.Since delay and energy consumption are the optimization goals of two co-directional changes,it is difficult to find a business collaboration computing mechanism that simultaneously minimizes delay and energy consumption.This paper takes the unmanned aerial vehicle(UAV) inspection business scenario in the electric power IoT based on edge computing as the representative,and proposes a two-stage business collaboration computing mechanism including resources allocation and task allocation to optimize the business delay and energy consumption of UAV by decoupling the complex correlation between resource allocation and task allocation.A steepest descent resource allocation algorithm is proposed.On the basis of resource allocation,an improved multiobjective evolutionary algorithm based on decomposition by dynamically adjusting the size of neighborhood and the cross distribution index is proposed as a task allocation algorithm to minimize energy consumption and business delay.Simulation results show that our algorithms can respectively reduce the business delay and energy consumption by more than6.4% and 9.5% compared with other algorithms.

关 键 词：Business collaboration computing Task allocation Resource allocation Electric power IoT 

分 类 号：TP391.44-2[自动化与计算机技术—计算机应用技术] TN929.5-2[自动化与计算机技术—计算机科学与技术]