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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI)
Ali Asghar Pourhaji Kazem
Islamic Azad University of Tabriz
Computer Science & IT Electrical & Electronics Engineering Engineering

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AC-RDVT: Acyclic Resource Distance Vector Routing Tables for Dynamic Grid Resource Discovery Nafiseh Bahrami; Ahmad Habibizad Navin; Mina Alavighi; Ali Asghar Pourhaji Kazem
International Journal of Electrical and Computer Engineering (IJECE) Vol 3, No 1: February 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (316.746 KB)

Abstract

Since the objective of grid is sharing the numerous and heterogeneous resources, resource discovery is a challenging issue. Recently appeared, Ontosum, is a resource discovery method based on semantically linked organizations and a routing algorithm Resource Distance Vector (RDV), has been presented to forward resource discovery queries into the clusters. Although this framework is efficient for large-scale grids and nodes are clustered automatically based on semantic attributes to constitute a semantically linked overlay network, but the dynamic behavior of grid isn’t considered. In this method, deceptive information is stored in RDV tables (RDVT) which cause some problems in routing process. In this paper, a method is proposed to improve the dynamism of RDV routing algorithm, so the consistency with grid environments is increased. The developed algorithm is assessed by investigating the success probability, number of hops and routing time of resource discovery.DOI:http://dx.doi.org/10.11591/ijece.v3i1.1837
RDVBT: Resource Distance Vector Binary Tree Algorithm for Resource Discovery in Grid SeyedElyar Hashemseresht; Ali Asghar Pourhaji Kazem
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 1, No 2: June 2012
Publisher : Institute of Advanced Engineering and Science

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Abstract

Nowadays, with the increasing variety of computer systems, resource discovery in the Grid environment has been very important due to their applications; thus, offering optimal and dynamic algorithms for discovering resources in which users need a short period is an important task in grid environments.One of the methods used in resource discovery in grid is to use routing tables RDV (resource distance vector) in which the resources are based on certain criteria clustering and the clusters form a graph. In this way, some information about the resources is stored in RDV tables. Due to the environmental cycle in the graph, there are some problems; for example there are multiple paths to resources, most of which are repeated. Also, in large environments, due to the existence of many neighbors, updating the graph is time-consuming. In this paper, the structure of RDV was presented as a binary tree and these two methods (RDV graph-algorithm and RDVBT) were compared. Simulation results showed that, as a result of converting the structure to a binary tree, much better results were obtained for routing time, table updating time and number of successful requests; also the number of unsuccessful requests was reduced.DOI: http://dx.doi.org/10.11591/ij-ai.v1i2.442 
Co-Authors Ahmad Habibizad Navin Mina Alavighi Nafiseh Bahrami SeyedElyar Hashemseresht