期刊名称：International Journal of Future Generation Communication and Networking
印刷版ISSN：2233-7857
出版年度：2016
卷号：9
期号：9
页码：215-230
出版社：SERSC
摘要：In order to implement big data access and process with high efficiency, an algorithm of nodes location was proposed according to the state of computable resources. In this paper, we first describe and map the computational resource with javascript object notation(JSON) in P2P network system. Regarding the computational nodes as spatial points, then we present a generalized euclid distance(GED) model using the method of spatial points clustering. Through this model, the computational nodes can partition into multiple sub-group upon the characteristic attributes. After that, we calculate the spatial distance and attribute distance by spatial geometric model of global network positioning(GNP), ultimately implement the computable nodes location with efficiency, to provide the basis of load balance, especially in cloud computing. Experimental resultsshow that our method not only can significantly improve system performance, also in accuracy of nodes location
