Resource Discovery Algorithm Based on Small-World Cluster in Hierarchical Grid Computing Environment

Ma, Yan; Gong, Bin; Zou, Lida

doi:10.1109/gcc.2008.83

Cited by 13 publications

(9 citation statements)

References 11 publications

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“…The purpose of a resource discovery system is to allow available resources to be located using a user-defined search criterion. To improve the efficiency of grid resource management numerous works have been done by researchers in this area [1][2][3]5,6]. Several methods have been proposed to solve the resource discovery problem in Grid systems.…”

Section: Existing Systemmentioning

confidence: 99%

Prioritized Least Cost Method for Better Resource Allocation in Hypercube Based Cluster Environment

Shanthi¹,

Irudhayaraj²,

Maruthi³

2014

2014 International Conference on Intelligent Computing Applications

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The processes are allocated to the suitable resource node according to the resource availability in hypercube based clusters using a least cost allocation algorithm. In the clusters, nodes are arranged in hypercube structure, using a small world theory. The main goal is to find the appropriate resource with minimum search cost and maximum search efficiency. The frame work, which is proposed, follows a linear programming model for grid resource allocation. It organizes resource elements into a set of hyper cubed overlay networks. Within this frame work, an algorithm is defined with request forwarding strategy. This strategy decides to which node a request to be forwarded. The resource availability in hypercube based clusters are discovered and allocated the request to the appropriate alive node using Prioritized Least Cost Method Algorithm (PLCM). The proposed PLCM Algorithm aims at minimum cost. The result shows that the proposed PLCM Algorithm, when compared with Least Cost Method (LCM) reduces the processing cost, satisfies the user demand, improves the resource utilization and balances the load across the grid environment.

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Section: Existing Systemmentioning

confidence: 99%

Prioritized Least Cost Method for Better Resource Allocation in Hypercube Based Cluster Environment

Shanthi¹,

Irudhayaraj²,

Maruthi³

2014

2014 International Conference on Intelligent Computing Applications

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“…[6] analyzes the small world phenomenon of the Internet and its impact on the multicast performance; from an engineering point of view, [7] gives a detail analysis of how small world occurs in network communication; [8] uses the comparative test to observe the small world and other several technologies impact on the average path length. [9][10][11] apply small world to P2P network overlay design; [12] applies the small world to wireless P2P network. But all these method above construct the small world network based on the physical connection distance or geographical distance.…”

Section: (/$7(' :25mentioning

confidence: 99%

ISW: Interest-based Small World network of P2P

Zeng

Zheng

2012

2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing

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Content location in unstructured peer-to-peer (P2P) networks is a challenging problem. In this paper, we present a novel Interest-based Small World (ISW) network to address the problem, by constructing a cluster overlay in the unstructured P2P network based on the small world paradigm and user interest. There are many attractive properties of a small world network, such as low average hop distance and high clustering coefficient. Interest locality can improve the awareness of user's indeed intentions. Our scheme combines their advantage to create a better solution. The simulation results show that our scheme outperforms other schemes significantly.

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“…After grouping all the jobs sends to the corresponding resources whose connection can be finished earlier which implies that the smallest request issued through the fastest connection giving best transmission rate or bandwidth. Hierarchical architecture based on small-world cluster and Small World Resource Discovery (SWRD) algorithm used in education resource grid have high search success rate and low query cost [5]. Grouping based fire grained job scheduling algorithm [6] light weight jobs are grouped as coarse grained jobs.…”

Section: Related Workmentioning

confidence: 99%

“…Architecture of hierarchical grid [9] is represented by graph formalized as G= (V, E), where V is the vertex set, E is Edge set. V (G) = {V R , V I , V L } and E (G) = {E 1 , E 2 , E 3 …..E n } V L is the leaf node, mainly made up of group of jobs, are the bottom of hierarchical grid.…”

Section: Architecture Of Hierarchical Gridmentioning

confidence: 99%

Hierarchical Structure based Job Group Resource Allocation Scheduling Model

Suri¹,

Rani²

2015

IJCA

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In grid environment, the resource management system schedules the jobs to specific resources with trying to minimize some objective functions. This paper considers the hierarchical structure of grid with multiple level resource schedule model which divides the tasks into group according to minimum execution time assigns and these groups to the resources. This grouping based algorithm is compared with non-grouped jobs and obtained better results in terms of completion time, expected performance and expected execution time than the non-grouped jobs.

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Resource Discovery Algorithm Based on Small-World Cluster in Hierarchical Grid Computing Environment

Cited by 13 publications

References 11 publications

Prioritized Least Cost Method for Better Resource Allocation in Hypercube Based Cluster Environment

Prioritized Least Cost Method for Better Resource Allocation in Hypercube Based Cluster Environment

ISW: Interest-based Small World network of P2P

Hierarchical Structure based Job Group Resource Allocation Scheduling Model

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