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Resource discovery algorithm based on hierarchical model and Conscious search in Grid computing system

机译:网格计算系统中基于层次模型和意识搜索的资源发现算法

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The distributed system of Grid subscribes the non-homogenous sources at a vast level in a dynamic manner. The resource discovery manner is very influential on the efficiency and of quality the system functionality. The “Bitmap” model is based on the hierarchical and conscious search model that allows for less traffic and low number of messages in relation to other methods in this respect. This proposed method is based on the hierarchical and conscious search model that enhances the Bitmap method with the objective to reduce traffic, reduce the load of resource management processing, reduce the number of emerged messages due to resource discovery and increase the resource according speed. The proposed method and the Bitmap method are simulated through Arena tool. This proposed model is abbreviated as RNTL.
机译:Grid的分布式系统以动态方式广泛地订阅了非均匀源。资源发现方式对系统功能的效率和质量有很大的影响。 “位图”模型基于分层和有意识的搜索模型,相对于此方面的其他方法,该模型允许较少的通信量和较少的消息数。该方法基于分层有意识的搜索模型,该模型对Bitmap方法进行了增强,目的是减少流量,减少资源管理处理的负担,减少由于发现资源而出现的消息数量并提高资源的按需速度。通过Arena工具对提出的方法和位图方法进行了仿真。提出的模型简称为RNTL。

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