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Business value-aware task scheduling for hybrid IaaS cloud

机译:混合IaaS云的业务价值感知任务调度

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Since an Infrastructure as a Service (IaaS) provider has limited resources, it faces the challenge of scheduling tasks to meet the peak demand. For this issue, the task scheduling problem for hybrid cloud from an IaaS provider's perspective should be properly addressed. However, existing research does not consider either process tasks with slack temporal constraints or the business value from an IaaS provider's perspective, or it has to specify the type of Virtual Machine (VM) for each task prior. In this paper, we first formalize the problem in which both process tasks with slack temporal constraints and VM type selection optimization are considered, and business value is taken as the objective to comprehensively measure the earned value of an IaaS provider. Second, a novel Evolutionary Algorithm for Task Scheduling in a Hybrid IaaS Cloud (EATSHC) is proposed to solve the problem. Finally, several experiments show our approach performs more effectively and efficiently than existing research.
机译:由于基础架构即服务(IaaS)提供商的资源有限,因此面临计划任务以满足峰值需求的挑战。对于此问题,应从IaaS提供商的角度正确解决混合云的任务调度问题。但是,现有研究并未从IaaS提供商的角度考虑具有宽松时间限制的处理任务或业务价值,或者必须事先为每个任务指定虚拟机(VM)的类型。在本文中,我们首先将同时考虑松弛时间约束和VM类型选择优化的处理任务并以业务价值为目标来全面衡量IaaS提供商的收入价值的问题形式化。其次,提出了一种新的用于混合IaaS云中任务调度的进化算法(EATSHC)以解决该问题。最后,一些实验表明我们的方法比现有的研究更有效。

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