{"title":"基于CSOA-VM模型的云数据中心节能虚拟机选择","authors":"Mandeep Singh Devgan, Tajinder Kumar, Purushottam Sharma, Xiaochun Cheng, Shashi Bhushan, Vishal Garg","doi":"10.1049/cit2.70018","DOIUrl":null,"url":null,"abstract":"<p>The cloud data centres evolved with an issue of energy management due to the constant increase in size, complexity and enormous consumption of energy. Energy management is a challenging issue that is critical in cloud data centres and an important concern of research for many researchers. In this paper, we proposed a cuckoo search (CS)-based optimisation technique for the virtual machine (VM) selection and a novel placement algorithm considering the different constraints. The energy consumption model and the simulation model have been implemented for the efficient selection of VM. The proposed model CSOA-VM not only lessens the violations at the service level agreement (SLA) level but also minimises the VM migrations. The proposed model also saves energy and the performance analysis shows that energy consumption obtained is 1.35 kWh, SLA violation is 9.2 and VM migration is about 268. Thus, there is an improvement in energy consumption of about 1.8% and a 2.1% improvement (reduction) in violations of SLA in comparison to existing techniques.</p>","PeriodicalId":46211,"journal":{"name":"CAAI Transactions on Intelligence Technology","volume":"10 4","pages":"1217-1234"},"PeriodicalIF":7.3000,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/cit2.70018","citationCount":"0","resultStr":"{\"title\":\"Energy Efficient VM Selection Using CSOA-VM Model in Cloud Data Centers\",\"authors\":\"Mandeep Singh Devgan, Tajinder Kumar, Purushottam Sharma, Xiaochun Cheng, Shashi Bhushan, Vishal Garg\",\"doi\":\"10.1049/cit2.70018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The cloud data centres evolved with an issue of energy management due to the constant increase in size, complexity and enormous consumption of energy. Energy management is a challenging issue that is critical in cloud data centres and an important concern of research for many researchers. In this paper, we proposed a cuckoo search (CS)-based optimisation technique for the virtual machine (VM) selection and a novel placement algorithm considering the different constraints. The energy consumption model and the simulation model have been implemented for the efficient selection of VM. The proposed model CSOA-VM not only lessens the violations at the service level agreement (SLA) level but also minimises the VM migrations. The proposed model also saves energy and the performance analysis shows that energy consumption obtained is 1.35 kWh, SLA violation is 9.2 and VM migration is about 268. Thus, there is an improvement in energy consumption of about 1.8% and a 2.1% improvement (reduction) in violations of SLA in comparison to existing techniques.</p>\",\"PeriodicalId\":46211,\"journal\":{\"name\":\"CAAI Transactions on Intelligence Technology\",\"volume\":\"10 4\",\"pages\":\"1217-1234\"},\"PeriodicalIF\":7.3000,\"publicationDate\":\"2025-04-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/cit2.70018\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CAAI Transactions on Intelligence Technology\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/cit2.70018\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CAAI Transactions on Intelligence Technology","FirstCategoryId":"94","ListUrlMain":"https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/cit2.70018","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Energy Efficient VM Selection Using CSOA-VM Model in Cloud Data Centers
The cloud data centres evolved with an issue of energy management due to the constant increase in size, complexity and enormous consumption of energy. Energy management is a challenging issue that is critical in cloud data centres and an important concern of research for many researchers. In this paper, we proposed a cuckoo search (CS)-based optimisation technique for the virtual machine (VM) selection and a novel placement algorithm considering the different constraints. The energy consumption model and the simulation model have been implemented for the efficient selection of VM. The proposed model CSOA-VM not only lessens the violations at the service level agreement (SLA) level but also minimises the VM migrations. The proposed model also saves energy and the performance analysis shows that energy consumption obtained is 1.35 kWh, SLA violation is 9.2 and VM migration is about 268. Thus, there is an improvement in energy consumption of about 1.8% and a 2.1% improvement (reduction) in violations of SLA in comparison to existing techniques.
期刊介绍:
CAAI Transactions on Intelligence Technology is a leading venue for original research on the theoretical and experimental aspects of artificial intelligence technology. We are a fully open access journal co-published by the Institution of Engineering and Technology (IET) and the Chinese Association for Artificial Intelligence (CAAI) providing research which is openly accessible to read and share worldwide.