Earticle

초록

영어

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 results show that our method not only can significantly improve system performance, also in accuracy of nodes location.

목차

Abstract
 1. Introduction
 2. Description for Computable Resources by JSON
 3. Querying Algorithm for Computable Resource in P2P System
  3.1. Bitmap index & Spanning-Tree Generation
  3.2. Querying Algorithm for Computable Resource
 4. Algorithm of Spatial Points Clustering on Computational node Location
  4.1. Generalized Euclid Distance
  4.2. Algorithm of Computable Nodes Location
 5. Simulation and Experiments
 6. Related Work
 7. Conclusion and Future Work
 Acknowledgements
 References

키워드

저자

• Zhi Zeng [ Department of Computer Science, Huizhou University, Huizhou 516007, China ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Future Generation Communication and Networking

• 간기

  격월간

• pISSN

  2233-7857

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605