Qualities of Grid Computing that can last for Ages

Asagba, P. O.; Ogheneovo, Edward E.

doi:10.4314/jasem.v12i4.55218

Cited by 2 publications

(1 citation statement)

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“…But, it becomes difficult when the resources are geographically distributed, different in nature, possessed by diverse user or organizations with their own policies, have diverse access models, and have dynamically changing loads and availability (Nandagopal & Uthariaraj, 2010). By offering scalable, secure, high-performance techniques for discovering and allowing access to remote resources, the Grid assures the possibility for scientific collaborations to share resources on an exceptional scale, and for geographically dispersed groups to work together in ways that were formerly not possible (Oghenekaro & Edward, 2008).…”

Section: Introductionmentioning

confidence: 99%

Resource Allocation Mechanism with New Models for Grid Environment

Sathish

Reddy

2013

International Journal of Grid and High Performance Computing

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Resource allocation is playing a vital role in grid environment because of the dynamic and heterogeneous nature of grid resources. Literature offers numerous studies and techniques to solve the grid resource allocation problem. Some of the drawbacks occur during grid resource allocation are low utilization, less economic reliability and increased waiting time of the jobs. These problems were occurred because of the inconsiderable level in the code of allocating right resources to right jobs, poor economic model and lack of provision to minimize the waiting time of jobs to get their resources. So, all these drawbacks need to be solved in any upcoming resource allocation technique. Hence in this paper, the efficiency of the resource allocation mechanism is improved by proposing two allocation models. Both the allocation models have used the Genetic Algorithm to overcome all the aforesaid drawbacks. However, one of the allocation models includes penalty function and the other does not consider the economic reliability. Both the models are implemented and experimented with different number of jobs and resources. The proposed models are compared with the conventional resource allocation models in terms of utilization, cost factor, failure rate and make span.

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Section: Introductionmentioning

confidence: 99%