A self-adaptive structuring for large-scale P2P Grid environment: design and simulation analysis. (2017)

• Record Type: Journal Article
• Authors: Gueye, Bassirou; Flauzac, Olivier; Rabat, Cyril; Niang, Ibrahima
• Is Part Of: International journal of grid and utility computing. Volume 8:Number 3(2017)
• Page Start: 254
• Page End: 267
• Publication Date: 2017
• Subjects: peer-to-peer systems -- grid services -- resources management -- modelling -- distributed algorithms -- clustering -- spanning tree -- OverSim simulator; Electronic data processing -- Distributed processing -- Periodicals; Electronic commerce -- Management -- Computer programs -- Periodicals; 004.605
• Languages: English
• ISSNs: 1741-847X

Abstract

Resource management is a key issue for large-scale grid environments. In particular, the resource discovery mechanism used highly impacts on the efficiency of resource sharing and cooperative computing. Meanwhile, the increasing size of resources and users in large-scale distributed systems has lead to a scalability problem. The self-organising, fault tolerance and decentralised nature of P2P technology, which helps to reduce the management cost of grid infrastructure, is a good basis for resolving both aforementioned problems. In this context, we propose a self-adaptive structuring model for large-scale P2P grid environments. The proposed specification, called P2P4GS, is generic, i.e. not linked to a particular P2P architecture. Our structuring approach is completely distributed, and requires only local knowledge about neighbouring nodes to implement node virtual community. Indeed, given a node's connection and based on its neighbours, we dynamically create virtual communities or clusters. A particular node called ISP (Information System Proxy) acts as service directory within each cluster. In addition, to provide an efficient lookup mechanism in our system, we proposed to build a spanning tree constituted by the set of ISPs. An experimental validation, through simulation, shows that our approach ensures a high scalability in terms of clusters distribution and communication cost.