{"title":"云计算环境下的云调度:基于优先级的云调度算法(PBCSA)","authors":"D. Gritto, P. Muthulakshmi","doi":"10.1109/SMART55829.2022.10047622","DOIUrl":null,"url":null,"abstract":"Cloud computing is a service model that has evolved in its stature beyond its traditional bounds of infrastructure, platform and software as a service. As the surge in resource demand may hit the cloud service provider at any time, a ceaseless monitoring system is vital. The allocation of an appropriate virtual machine for the cloudlet i.e., the user workload and maintaining the work load equilibrium among the resources is the most challenging operation in the cloud environment. The proper utilization of the cloud resources can be ensured by selecting the right cloudlet scheduling and load balancing algorithm(s). The cloudlet scheduling algorithm selection is based on the combination of two or more Quality of Service (QoS) and performance metrics like makespan, throughput, cost, power consumption, virtual machine or resource utilization and load balancing etc. The load balancer module takes the responsibility of dispersing the cloudlets evenly among the virtual machines by considering various features like CPU utilization, number of processing elements, bandwidth, memory and the load limit of the virtual machines. In this paper, an effort has been made to comprehend the most persisting cloudlet scheduling and load balancing algorithms that have been proposed by the researchers. Compiling the load balancing technologies that are integrated with the contemporary cloud platforms such as Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP) has also been prioritized. This study suggests a Priority Based Cloudlet Scheduling Algorithm (PBCSA) that schedules the cloudlet according to the user priority. The Min-Min scheduler is used to schedule the high priority cloudlets and the Max-Min scheduler is used to schedule the low priority cloudlets. The experimental findings reveals that, in the majority of scenarios, the proposed algorithm outperforms the Min-Min and Max-Min scheduling in terms of makespan and virtual machine utilization ratio.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Scheduling Cloudlets in a Cloud Computing Environment: A Priority-based Cloudlet Scheduling Algorithm (PBCSA)\",\"authors\":\"D. Gritto, P. 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引用次数: 1
摘要
云计算是一种服务模式,其地位已经超越了基础设施、平台和软件即服务的传统界限。由于资源需求的激增可能随时冲击云服务提供商,因此一个不间断的监控系统至关重要。为cloudlet分配适当的虚拟机(即用户工作负载和维护资源之间的工作负载平衡)是云环境中最具挑战性的操作。通过选择合适的云调度和负载均衡算法,可以保证云资源的合理利用。cloudlet调度算法的选择是基于两个或多个服务质量(QoS)和性能指标的组合,如makespan、吞吐量、成本、功耗、虚拟机或资源利用率和负载平衡等。负载平衡器模块通过考虑各种特性,如CPU利用率、处理元素的数量、带宽、内存和虚拟机的负载限制,负责在虚拟机中均匀地分散cloudlet。本文对研究人员提出的最持久的云调度和负载平衡算法进行了理解。编译与Amazon Web Services (AWS)、Microsoft Azure和谷歌cloud Platform (GCP)等当代云平台集成的负载平衡技术也已被优先考虑。本研究提出一种基于优先级的云调度算法(PBCSA),根据用户优先级对云调度进行调度。Min-Min调度器用于调度高优先级的cloudlets, Max-Min调度器用于调度低优先级的cloudlets。实验结果表明,在大多数场景下,该算法在makespan和虚拟机利用率方面优于Min-Min和Max-Min调度。
Scheduling Cloudlets in a Cloud Computing Environment: A Priority-based Cloudlet Scheduling Algorithm (PBCSA)
Cloud computing is a service model that has evolved in its stature beyond its traditional bounds of infrastructure, platform and software as a service. As the surge in resource demand may hit the cloud service provider at any time, a ceaseless monitoring system is vital. The allocation of an appropriate virtual machine for the cloudlet i.e., the user workload and maintaining the work load equilibrium among the resources is the most challenging operation in the cloud environment. The proper utilization of the cloud resources can be ensured by selecting the right cloudlet scheduling and load balancing algorithm(s). The cloudlet scheduling algorithm selection is based on the combination of two or more Quality of Service (QoS) and performance metrics like makespan, throughput, cost, power consumption, virtual machine or resource utilization and load balancing etc. The load balancer module takes the responsibility of dispersing the cloudlets evenly among the virtual machines by considering various features like CPU utilization, number of processing elements, bandwidth, memory and the load limit of the virtual machines. In this paper, an effort has been made to comprehend the most persisting cloudlet scheduling and load balancing algorithms that have been proposed by the researchers. Compiling the load balancing technologies that are integrated with the contemporary cloud platforms such as Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP) has also been prioritized. This study suggests a Priority Based Cloudlet Scheduling Algorithm (PBCSA) that schedules the cloudlet according to the user priority. The Min-Min scheduler is used to schedule the high priority cloudlets and the Max-Min scheduler is used to schedule the low priority cloudlets. The experimental findings reveals that, in the majority of scenarios, the proposed algorithm outperforms the Min-Min and Max-Min scheduling in terms of makespan and virtual machine utilization ratio.