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Resource availability prediction using semi-Markov model in mobile grid environment

机译:移动网格环境中使用半马尔可夫模型的资源可用性预测

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摘要

Integration of mobile resources in grid environment increases the complexity of resource prediction owing to heterogeneity, dynamic nature of resources, mobility pattern and uncertainty in the availability. The mobile grid has geographically distributed autonomous resources and is composed of hardware and software resources that need to be located. The existing resource prediction approaches in mobile grid treat resources equally. These approaches face problems in terms of resource prediction times. This can be reduced by predicting the availability of resources based on its characteristics. The dynamic characteristics of mobile resources increase complexities in resource prediction and filtering process, which in turn increases resource prediction time. In this paper, a semi-Markov model based availability prediction mechanism is proposed for the mobile grid environment. This mechanism uses a semi-Markov model to predict the resources availability and a mapper to filter the resources based on task requirement, which reduces resource prediction time.
机译:网格环境中的移动资源集成由于异构性,资源的动态特性,移动性模式和可用性的不确定性而增加了资源预测的复杂性。移动网格具有地理上分散的自治资源,并且由需要定位的硬件和软件资源组成。移动网格中现有的资源预测方法均等地对待资源。这些方法在资源预测时间方面面临问题。可以通过根据其特性预测资源的可用性来减少这种情况。移动资源的动态特性增加了资源预测和过滤过程的复杂性,进而增加了资源预测时间。本文针对移动网格环境,提出了一种基于半马尔可夫模型的可用性预测机制。该机制使用半马尔可夫模型预测资源可用性,并使用映射器根据任务要求过滤资源,从而减少了资源预测时间。

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