支持sla的任务分配,并在云环境中进行资源优化

Shrabanee Swagatika, A. Rath
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引用次数: 1

摘要

由于其不可预测的性质,云计算是多个用户的物化环境。然而,对于许多研究来说,云是一个具有挑战性的环境,因为它很难准确预测虚拟机(VM)的状态,以便为云消费者分配资源。许多研究者致力于优化和调度算法来预测虚拟机的准确状态,但他们的研究未能提供主导的结果。为了提供有效的结果,我们提出了一种新的具有资源优化的云框架。其中选择了两个特殊组件:一个是资源管理器(RM),另一个是虚拟机重新分配器(VMRA)。这个框架有几个方法,如任务集群、任务分配、VM集群和VM重新分配。针对云上可用的多个任务引入sla优先级聚类算法,并使用ETC矩阵和粒子群算法对这些任务进行分配。我们提出的云框架可以使用CloudSim仿真工具实现,该工具提供了高效的结果。因此,我们的流程在云环境下有效地分配资源,解决了VM的重新分配问题,提出了高效节能的VM重新分配算法来解决随机故障问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SLA-aware task allocation with resource optimisation on cloud environment
Cloud computing is a materialised environment for several users due to its unpredictable nature. However cloud is a challengeable environment for many researches because of its hardness on predicting the accurate status of virtual machines (VM) in order to allocate resources for cloud consumers. Many researchers focus on optimisation and scheduling algorithms for predicting accurate status about VMs and their researches fail in providing the predominant results. In order to furnish efficacious results, we propose a novel cloud framework with resource optimisation. Two special components are chosen on it: one is resource manager (RM) and the other one is virtual machine re-allocator (VMRA). This framework has several methodologies like task clustering, task allocation, VM clustering and re-allocation of VMs. Specifically we introduce SLA-priority clustering algorithm for several tasks available on cloud, and these are allocated using ETC matrix with PSO algorithm. Our proposed cloud framework can be implemented using a CloudSim simulation tool which furnishes the efficient results. Thus our process effectively allocates resources on cloud environment and we also solve the problem of re-allocation of VM, power efficient VM re-allocation algorithm is proposed to solving the random failure issues.
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