Task scheduling and optimization for integrated observation network with maximum energy utilization efficiency

被引：0

作者：

Du X. ^{[1
]}

Wang X. ^{[2
,3
,4
]}

Han S. ^{[2
,3
]}

Wang F. ^{[2
,5
]}

机构：

[1] School of Economics and Management, University of Chinese Academy of Sciences, Beijing

[2] The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing

[3] Qingdao Academy of Intelligent Industries, Qingdao

[4] Vehicle Intelligence Pioneers Inc., Qingdao

[5] Research Center of Military Computational Experiments and Parallel Systems Technology, National University of Defense Technology, Changsha

来源：

Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice | 2021年 / 41卷 / 06期

关键词：

Integrated observation networks; Maximum energy efficiency; Parallel intelligence methods; Resource allocation; Task scheduling;

D O I：

10.12011/SETP2020-2064

中图分类号：

学科分类号：

摘要：

This paper studied how to allocate resources reasonably to ensure efficient task scheduling, which is important for energy efficiency optimization in integrated observation networks. The core concepts, methods and technologies of parallel intelligence are introduced to integrated observation networks. An artificial integrated observation network is constructed, in which the connection probability among sensing nodes and local central nodes are considered, for better task management and scheduling. In order to delay the life of the network, we design computational experiments to obtain the energy efficiency maximization plan, and utilize the optimization of resource allocation parameters to improve the efficiency of network resource scheduling and allocation, thereby improving the information transmission rate in the network, reducing delay, and improving the resource utilization efficiency of task scheduling. © 2021, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.

引用

页码：1547 / 1555

页数：8

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