An Account Of Multi-Neutral Workflow Procedure For Cloud Situation

Yogesh Kothyari, Ajit Singh
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引用次数: 1

Abstract

The workflow preparation complications contain quality of service. The task-reserve mapping sustaining workflow solicitations necessitate extraordinary computational power and often involve a large amount of data transmission from one place to another. Furthermore, due to dependency exist on among tasks schedulers must be brought forth according to given preference constraints. Cloud computing is a new business-oriented platform service that facilitates an infinite number of services by providing heterogeneous and virtualized resources to users based on a pay-as-you-go model. The distinctive quality of service (QoS) is market-oriented and conventional approach for facing new challenges like autonomy, on-demand payment and unprecedented openness. This paper presents multi-objective workflow scheduling algorithm (MWSA) which optimally run the workflow execution process for minimization of total cost and makespan. This algorithm uses the concept of an adaptive elite-based particle-swarm-optimization (PSO) for implementing task-resource mapping. A comparative study of presented algorithm is also made with some existing algorithms.
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云环境下多中性工作流过程的描述
工作流准备的复杂性包含服务质量。维持工作流请求的任务储备映射需要非凡的计算能力,并且通常涉及从一个地方到另一个地方的大量数据传输。此外,由于任务之间存在依赖关系,必须根据给定的首选项约束提出调度器。云计算是一种新的面向业务的平台服务,它基于现收现付模式向用户提供异构和虚拟化资源,从而促进了无限数量的服务。独特的服务质量(QoS)是以市场为导向的传统方式来面对自主性、按需支付和前所未有的开放性等新挑战。提出了一种多目标工作流调度算法(MWSA),该算法以最小化总成本和最大完工时间为目标,对工作流执行过程进行优化调度。该算法采用基于自适应精英的粒子群优化(PSO)思想实现任务-资源映射。并与现有算法进行了比较研究。
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