{"title":"Towards a novel service broker policy for choosing the appropriate data center in cloud environments","authors":"Lin Shan , Li Sun , Amin Rezaeipanah","doi":"10.1016/j.comcom.2024.107939","DOIUrl":null,"url":null,"abstract":"<div><p>Providing cloud computing services leads to quick access of users to dynamic and distributed resources. Increasing demand has created challenges such as resource availability, privacy, and security to provide efficient services in cloud computing. Cloud environments contain various computing resources, and allocating a suitable node to process a request can improve the quality of service on a large scale. Load balancing is one of the strategies to improve service quality and resource utilization, which refers to the distribution of load among different nodes in a distributed system. The cloud application service broker is responsible for load balancing by choosing the appropriate geo-distributed datacenter to process the requests of each end user. Parameters such as transmission delay, network delay, processing time, number of servers, workload, and service cost can be considered to select a suitable datacenter in close proximity. To reduce the adverse effects of choosing a datacenter by a service broker, this paper presents Rank-based Load Balancing in Geo-Distributed datacenters (RLBGD) as an effective service broker strategy in cloud environments. RLBGD uses a weighted combination of several criteria such as processing time, number of servers, workload, processing speed, service cost, and response time for dynamic ranking and determining the appropriate datacenter. CloudAnalyst tool is used to simulate and analyze the performance of the proposed method. The results of experiments show the effectiveness of RLBGD in terms of metrics such as service cost and processing time in different scenarios.</p></div>","PeriodicalId":55224,"journal":{"name":"Computer Communications","volume":"228 ","pages":"Article 107939"},"PeriodicalIF":4.5000,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Communications","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S014036642400286X","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Providing cloud computing services leads to quick access of users to dynamic and distributed resources. Increasing demand has created challenges such as resource availability, privacy, and security to provide efficient services in cloud computing. Cloud environments contain various computing resources, and allocating a suitable node to process a request can improve the quality of service on a large scale. Load balancing is one of the strategies to improve service quality and resource utilization, which refers to the distribution of load among different nodes in a distributed system. The cloud application service broker is responsible for load balancing by choosing the appropriate geo-distributed datacenter to process the requests of each end user. Parameters such as transmission delay, network delay, processing time, number of servers, workload, and service cost can be considered to select a suitable datacenter in close proximity. To reduce the adverse effects of choosing a datacenter by a service broker, this paper presents Rank-based Load Balancing in Geo-Distributed datacenters (RLBGD) as an effective service broker strategy in cloud environments. RLBGD uses a weighted combination of several criteria such as processing time, number of servers, workload, processing speed, service cost, and response time for dynamic ranking and determining the appropriate datacenter. CloudAnalyst tool is used to simulate and analyze the performance of the proposed method. The results of experiments show the effectiveness of RLBGD in terms of metrics such as service cost and processing time in different scenarios.
期刊介绍：
Computer and Communications networks are key infrastructures of the information society with high socio-economic value as they contribute to the correct operations of many critical services (from healthcare to finance and transportation). Internet is the core of today''s computer-communication infrastructures. This has transformed the Internet, from a robust network for data transfer between computers, to a global, content-rich, communication and information system where contents are increasingly generated by the users, and distributed according to human social relations. Next-generation network technologies, architectures and protocols are therefore required to overcome the limitations of the legacy Internet and add new capabilities and services. The future Internet should be ubiquitous, secure, resilient, and closer to human communication paradigms.
Computer Communications is a peer-reviewed international journal that publishes high-quality scientific articles (both theory and practice) and survey papers covering all aspects of future computer communication networks (on all layers, except the physical layer), with a special attention to the evolution of the Internet architecture, protocols, services, and applications.
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