面向5G的云邊端協(xié)同計(jì)算資源優(yōu)化與任務(wù)調(diào)度研究

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摘要：該文針對(duì)“云-邊-端”場(chǎng)景下資源分配與任務(wù)調(diào)度效果不佳的問(wèn)題，提出基于權(quán)重綜合成本模型的模擬退火算法優(yōu)化策略。仿真實(shí)驗(yàn)表明，該策略能顯著提升資源利用率、降低任務(wù)延遲和系統(tǒng)成本，對(duì)5G網(wǎng)絡(luò)的資源分配與任務(wù)調(diào)度優(yōu)化具有重要實(shí)用價(jià)值。

關(guān)鍵詞：多接入邊緣計(jì)算；云邊端協(xié)同；資源優(yōu)化；任務(wù)調(diào)度；模擬退火算法

doi：10.3969/J.ISSN.1672-7274.2024.12.025

中圖分類(lèi)號(hào)：TN 929.53；TP 393            文獻(xiàn)標(biāo)志碼：A            文章編碼：1672-7274（2024）12-00-04

Research on Cloud-Edge-End Collaborative Computing Resource Optimization and Task Scheduling for 5G

QU Dingchun

（Gongcheng Management Consulting Co.， Ltd.， Guangzhou 516030， China）

Abstract： This study addresses the issue of inefficient resource allocation and task scheduling in the "cloud-edge-end" scenario， proposing an optimization strategy based on a weighted comprehensive cost model and simulated annealing algorithm. Simulation experiments demonstrate that this strategy significantly improves resource utilization， reduces task latency， and lowers system costs， thus holding substantial practical value for resource allocation and task scheduling optimization in 5G networks.

Keywords： multi-access edge computing; cloud-edge-end collaboration; resource optimization; task scheduling; simulated annealing algorithm

0   引言

隨著互聯(lián)網(wǎng)及5G技術(shù)的迅猛發(fā)展，全球接入互聯(lián)網(wǎng)的終端設(shè)備數(shù)量于2023年激增至300億個(gè)，伴隨而來(lái)的是對(duì)計(jì)算需求高、時(shí)延敏感的應(yīng)用的激增。（剩余3343字）