网格计算系统中基于层次模型和有意识搜索的资源发现算法

Nasim Nickbakhsh, M. Aghaei
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引用次数: 1

摘要

网格的分布式系统以动态的方式对海量的非同质源进行订阅。资源发现的方式直接影响到系统功能的效率和质量。“位图”模型基于分层和有意识的搜索模型,在这方面,与其他方法相比,它允许更少的流量和更少的消息数量。该方法基于层次意识搜索模型,对位图方法进行了改进,目的是减少流量,减少资源管理处理负荷,减少因资源发现而产生的消息数量,提高资源查找速度。通过Arena工具对该方法和位图方法进行了仿真。这个模型被缩写为RNTL。
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Resource discovery algorithm based on hierarchical model and Conscious search in Grid computing system
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.
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来源期刊
International Journal of Advances in Soft Computing and its Applications
International Journal of Advances in Soft Computing and its Applications Computer Science-Computer Science Applications
CiteScore
3.30
自引率
0.00%
发文量
31
期刊介绍: The aim of this journal is to provide a lively forum for the communication of original research papers and timely review articles on Advances in Soft Computing and Its Applications. IJASCA will publish only articles of the highest quality. Submissions will be evaluated on their originality and significance. IJASCA invites submissions in all areas of Soft Computing and Its Applications. The scope of the journal includes, but is not limited to: √ Soft Computing Fundamental and Optimization √ Soft Computing for Big Data Era √ GPU Computing for Machine Learning √ Soft Computing Modeling for Perception and Spiritual Intelligence √ Soft Computing and Agents Technology √ Soft Computing in Computer Graphics √ Soft Computing and Pattern Recognition √ Soft Computing in Biomimetic Pattern Recognition √ Data mining for Social Network Data √ Spatial Data Mining & Information Retrieval √ Intelligent Software Agent Systems and Architectures √ Advanced Soft Computing and Multi-Objective Evolutionary Computation √ Perception-Based Intelligent Decision Systems √ Spiritual-Based Intelligent Systems √ Soft Computing in Industry ApplicationsOther issues related to the Advances of Soft Computing in various applications.
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