云数据中心虚拟机替换的改进最大最小蚁群优化算法[j]

2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC) Pub Date : 2014-12-01 DOI:10.1109/PCCC.2014.7017047

Tiantian Ren, Xinli Huang

{"title":"云数据中心虚拟机替换的改进最大最小蚁群优化算法[j]","authors":"Tiantian Ren, Xinli Huang","doi":"10.1109/PCCC.2014.7017047","DOIUrl":null,"url":null,"abstract":"With the increasing scale of cloud datacenters, the volumes of traffic flows inside a single datacenter become larger. An effective virtual machine (VM) replacement among physical machines (PMs) can improve resource utilization rate and reduce overall network cost in cloud datacenters. In this paper, we propose a Modified Max-Min Ant Colony Optimization (M3ACO) algorithm which can be used to solve the VMs replacement problem. Furthermore, we apply the M3ACO algorithm into a new framework based on Software Defined Network (SDN), which provides an integrated solution for resource optimization problem in cloud datacenters.","PeriodicalId":105442,"journal":{"name":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A modified max-min ant colony optimization algorithm for virtual machines replacement in cloud datacenter§\",\"authors\":\"Tiantian Ren, Xinli Huang\",\"doi\":\"10.1109/PCCC.2014.7017047\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the increasing scale of cloud datacenters, the volumes of traffic flows inside a single datacenter become larger. An effective virtual machine (VM) replacement among physical machines (PMs) can improve resource utilization rate and reduce overall network cost in cloud datacenters. In this paper, we propose a Modified Max-Min Ant Colony Optimization (M3ACO) algorithm which can be used to solve the VMs replacement problem. Furthermore, we apply the M3ACO algorithm into a new framework based on Software Defined Network (SDN), which provides an integrated solution for resource optimization problem in cloud datacenters.\",\"PeriodicalId\":105442,\"journal\":{\"name\":\"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PCCC.2014.7017047\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PCCC.2014.7017047","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

随着云数据中心规模的不断扩大，单个数据中心内部的流量也越来越大。在云数据中心中，通过物理机之间有效的虚拟机替换，可以提高资源利用率，降低整体网络成本。本文提出了一种改进的最大最小蚁群优化算法(M3ACO)来解决虚拟机替换问题。此外，我们将M3ACO算法应用到基于软件定义网络(SDN)的新框架中，为云数据中心的资源优化问题提供了一个集成的解决方案。

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

A modified max-min ant colony optimization algorithm for virtual machines replacement in cloud datacenter§

With the increasing scale of cloud datacenters, the volumes of traffic flows inside a single datacenter become larger. An effective virtual machine (VM) replacement among physical machines (PMs) can improve resource utilization rate and reduce overall network cost in cloud datacenters. In this paper, we propose a Modified Max-Min Ant Colony Optimization (M3ACO) algorithm which can be used to solve the VMs replacement problem. Furthermore, we apply the M3ACO algorithm into a new framework based on Software Defined Network (SDN), which provides an integrated solution for resource optimization problem in cloud datacenters.

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

2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)

自引率

0.00%

发文量