电子学报2025，Vol.53Issue(1)：221-237,17.DOI:10.12263/DZXB.20240401
基于动态势博弈的边缘算力网络任务调度算法
Task Scheduling Algorithm Based on Dynamic Potential Game for Edge Compute First Networking
摘要
Abstract
With the continuous development and maturity of personalized and diversified new network applications and services,the amount of data and computing demands are experiencing an exponential growth trend.Cloud computing,edge computing and intelligent terminal devices have been developed rapidly,and computing resources have shown a trend of ubiquitous and decentralized deployment.How to use these ubiquitous computing resources efficiently and collaborative-ly to meet the increasing computational demands has become an important new topic in the current network field.Edge com-pute first network focus on the edge of the network,near the location of the data source,combining heterogeneous comput-ing resources and network resources to improve resource utilization and task execution efficiency through resource aware-ness,service positioning,task scheduling,maintaining low latency and low cost and realizing the optimal configuration of distributed computing resources at the same time.Edge compute first network usually adopts the distributed task scheduling mode.In distributed task scheduling,each node makes local decision based on local information,which has the advantages of short decision time and effective relief of calculation and communication pressure of central controller.However,the lo-cal and asymmetric nature of information limits the global optimization performance of distributed scheduling,resulting in an inadequate task coverage.This paper focuses on distributed task scheduling in edge compute first network.With the sup-port of game theory and multi-objective optimization methods,a distributed task scheduling algorithm based on optimal dy-namic response is designed,which introduces communication and consensus elimination mechanisms within a two-hop range.Under the conditions of minimizing interaction costs and scheduling delays,it maximizes the task coverage of distrib-uted scheduling and achieves convergence to the Nash equilibrium point.A dynamic game model based on the optimization and consistency of distributed decision-making,with consensus elimination within a two-hop range as one of the optimiza-tion objectives,is established.The theoretical derivation demonstrates the asymptotic equivalence between local decisions and global decisions,providing an effective theoretical basis for the existence of Nash equilibria and the convergence of dis-tributed scheduling.Finally,the effectiveness and optimization benefits of the proposed algorithm are validated through sim-ulations and comparisons with a classical distributed decision-making algorithm and global optimal solutions.关键词
边缘算力网络/任务调度/拍卖算法/动态势博弈/分布式决策Key words
edge compute first networking/task scheduling/auction algorithm/dynamic potential game/distributed decision making分类
计算机与自动化引用本文复制引用
张晶,关建峰,刘科显,申奥..基于动态势博弈的边缘算力网络任务调度算法[J].电子学报,2025,53(1):221-237,17.基金项目
国家自然科学基金(No.62394323) National Natural Science Foundation of China(No.62394323) （No.62394323）
