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A Computing Capability Allocation Algorithm InDelicate Granularity For Cloud Environment

机译:云环境中精细粒度的计算能力分配算法

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As several special features in the environment of cloud computing, which may be quite different from the centralized computing infrastructure currently available, the existed method of resource allocation used in the grid computing environment may not be suitable for these changes. In this paper, a new allocation algorithm based on Ant Colony Optimization (ACO) was proposed to satisfy the property of Cloud Computing. When started, this algorithm first predict the capability of the potentially available resource nodes;then, it will analyze some factors such as network qualities or response times to acquire a set of optimal compute nodes;finally, the tasks would be allocated to these suitable nodes. This algorithm met the needs of cloud computing with shorter response time and better performance than others which designed based on Grid environment. These were proved by the simulation in the Gridsim environment elaborated in the Session 3.
机译:由于云计算环境中的几个特殊功能可能与当前可用的集中式计算基础设施完全不同,因此网格计算环境中使用的现有资源分配方法可能不适合这些更改。为了满足云计算的性能,提出了一种新的基于蚁群优化算法的分配算法。在启动时,该算法首先预测潜在可用资源节点的能力;然后,它将分析一些因素,例如网络质量或响应时间,以获取一组最佳计算节点;最后,任务将分配给这些合适的节点。与基于网格环境设计的算法相比,该算法满足了云计算的需求,响应时间更短,性能更高。这些在第3课中阐述的Gridsim环境中的仿真得到了证明。

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