基于分数 PID 控制的多目标网络资源分配方法

IF 3.4 2区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Signal Processing Pub Date : 2024-09-25 DOI:10.1016/j.sigpro.2024.109717

Xintong Ni, Yiheng Wei, Shuaiyu Zhou, Meng Tao

{"title":"基于分数 PID 控制的多目标网络资源分配方法","authors":"Xintong Ni, Yiheng Wei, Shuaiyu Zhou, Meng Tao","doi":"10.1016/j.sigpro.2024.109717","DOIUrl":null,"url":null,"abstract":"<div><div>In this paper, a fractional proportional–integral–derivative (PID) distributed optimization algorithm is proposed to solve the network resource allocation problem. The algorithm combines fractional calculus and the concept of PID control, which improves the convergence rate and increases the freedom, flexibility and potential with multiple parameters compared with the existing algorithms. Meanwhile, the results of simulation study verified the efficiency and superiority of the algorithm.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"227 ","pages":"Article 109717"},"PeriodicalIF":3.4000,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-objective network resource allocation method based on fractional PID control\",\"authors\":\"Xintong Ni, Yiheng Wei, Shuaiyu Zhou, Meng Tao\",\"doi\":\"10.1016/j.sigpro.2024.109717\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In this paper, a fractional proportional–integral–derivative (PID) distributed optimization algorithm is proposed to solve the network resource allocation problem. The algorithm combines fractional calculus and the concept of PID control, which improves the convergence rate and increases the freedom, flexibility and potential with multiple parameters compared with the existing algorithms. Meanwhile, the results of simulation study verified the efficiency and superiority of the algorithm.</div></div>\",\"PeriodicalId\":49523,\"journal\":{\"name\":\"Signal Processing\",\"volume\":\"227 \",\"pages\":\"Article 109717\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Signal Processing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0165168424003372\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165168424003372","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}

引用次数: 0

摘要

本文提出了一种分数比例积分派生（PID）分布式优化算法来解决网络资源分配问题。该算法结合了分数微积分和 PID 控制的概念，与现有算法相比，提高了收敛速度，增加了多参数的自由度、灵活性和潜力。同时，仿真研究结果验证了该算法的高效性和优越性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Multi-objective network resource allocation method based on fractional PID control

In this paper, a fractional proportional–integral–derivative (PID) distributed optimization algorithm is proposed to solve the network resource allocation problem. The algorithm combines fractional calculus and the concept of PID control, which improves the convergence rate and increases the freedom, flexibility and potential with multiple parameters compared with the existing algorithms. Meanwhile, the results of simulation study verified the efficiency and superiority of the algorithm.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Signal Processing 工程技术-工程：电子与电气

CiteScore

9.20

自引率

9.10%

发文量

309

审稿时长

41 days

期刊介绍： Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing. Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.