利用makespan对云环境进行有效的节点选择

Kunjal Garala, Hemanshi Dobariya
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引用次数: 2

摘要

今天,云计算作为一种新技术和新的商业模式正在崛起。不断增加的云计算服务为客户提供了以最优惠的价格找到最大服务的巨大机会,然而,这也提出了如何从庞大的群体中选择最佳服务的新挑战。在云计算环境中,各种计算资源为任务的执行提供了便利。因此,选择合适的节点执行任务是提高大规模云计算环境性能的必要条件。消费者收集必要的信息并分析所有服务提供商以做出决定是很耗时的。从计算的角度来看,这也是一项要求很高的任务,因为具有相似需求的多个消费者可能会重复执行相同的计算。负载均衡是在分布式系统的各个节点之间分配负载以提高资源利用率和作业响应时间的过程。负载平衡确保系统中的所有处理器在任何时刻都完成大约等量的工作。CloudAnalyst是一个工具,它可以帮助开发人员模拟大规模的云应用程序,从而了解这些应用程序在各种部署配置下的性能。本文给出了基于调度算法的仿真结果,并对三层负载均衡策略与不同算法的响应时间估计进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effective selection of node for cloud environment using makespan
Today, Cloud computing has been rising as new technology as well as new business model. The increasing cloud computing services offer great opportunities for clients to find the maximum service at finest pricing, which however raises new challenges on how to select the best service out of the huge group. A variety of computing resources facilitate the execution of tasks in Cloud computing environment. Therefore, it becomes necessary to select appropriate node for executing a task which enhances the performance of large-scale cloud computing environment. It is time-consuming for consumers to collect the necessary information and analyze all service providers to make the decision. This is also a highly demanding task from a computational perspective, because the same computations may be conducted repeatedly by multiple consumers who have similar requirements. Load balancing is the process of distributing the load among various nodes of a distributed system to improve both resource utilization and job response time. Load balancing ensures that all the processor in the system does approximately an equal amount of work at any instant of time. CloudAnalyst is a tool that helps developers to simulate large-scale Cloud applications with the purpose of understanding performance of such applications under various deployment configurations. The simulated results provided in this paper based on the scheduling algorithm Three level hierarchical load balancing policy is being compared with different algorithm to estimate response time.
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