Cloudlet Scheduling with Particle Swarm Optimization

Hussein S. Al-Olimat, Mansoor Alam, R. Green, Jong Kwan Lee
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引用次数: 42

Abstract

Cloud computing is a particularly interesting and truly complex concept of providing services over networks on demand. Many tools have previously been created to simulate the work of the clouds, such as CloudSim. The main use of these tools is evaluation and testing of architectures and services before deployment on network centers and hosts in order to avoid any potential failures or inconveniences. The benefits of using the pay-per-use clouds may be affected by underutilization of the already reserved resources, so the maximization of system utilization while simultaneously minimizing makespan is of great interest to cloud providers wishing to reduce costs. To minimize makespan and increase resource utilization, a hybrid of particle swarm optimization and simulated annealing is implemented inside of CloudSim to advance the work of the already implemented simple broker. The new method maximizes the resource utilization and minimizes the makespan.
基于粒子群优化的云调度
云计算是一个特别有趣且真正复杂的概念,它通过网络按需提供服务。以前已经创建了许多工具来模拟云的工作,例如CloudSim。这些工具的主要用途是在网络中心和主机上部署之前对架构和服务进行评估和测试,以避免任何潜在的故障或不便。使用按使用付费的云的好处可能会受到已预留资源利用率不足的影响,因此,希望降低成本的云提供商非常关心如何在最大化系统利用率的同时最小化完工时间。为了最小化makespan并提高资源利用率,在CloudSim内部实现了粒子群优化和模拟退火的混合,以推进已经实现的简单代理的工作。新方法使资源利用率最大化,最大完工时间最小化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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