ORCID Profile
0000-0003-4044-9315
Current Organisation
University of Sharjah
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Publisher: Springer Science and Business Media LLC
Date: 17-01-2014
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: IEEE
Date: 12-2011
Publisher: IEEE
Date: 08-2010
Publisher: World Scientific Pub Co Pte Lt
Date: 06-2018
DOI: 10.1142/S0219649218500235
Abstract: The performance of computational grids mainly depends on the resource allocation service of a resource management system. Efficient resource allocation is essential for better resource utilisation which could be for both providers and grid users. Resource allocation includes the scheduling of gridlets to the available resources. However, the biggest challenges for grid users are to select the best resources from the available grid resources and to allocate these resources for scheduling of the gridlets. To address these issues and enhance the resource utilisation process, we propose a semantic and proximity-aware fuzzy rule-based model that improves the resource utilisation in a grid environment. The model uses fuzzy techniques with four parameters such as semantic similarity, proximity, number of total machines and number of total processors of each machine. The experimental results provide promising results. Overall, the proposed semantic and proximity-aware fuzzy rule-based decentralised resource discovery model improves the resource utilisation by 23% as compared to non-fuzzy first come first serve (FCFS) technique in a computational grid environment.
Publisher: World Scientific Pub Co Pte Lt
Date: 20-05-2016
DOI: 10.1142/S0219649216500209
Abstract: One of the fundamental issues in Grid decentralised resource discovery services is high communication overheads that affect the Grid system’s performance significantly. The rationale is that Grid resources are geographically distributed across the world through a wide area network under various virtual organisations. To address the issue, a significant amount of effort has been made by proposing various decentralised overlay algorithms with semantic solutions. Current Grid literature reveals that when semantic features are added into discovery services, the probability of finding resources is enhanced and communication overheads could be better. However, most of the existing decentralised resource discovery models utilise a domain-based semantic ontology with First Come First Serve (FCFS) basis scheduling for allocating Grid resources that can cause job rejection at run time and can pick resources that are far from the user nodes. As a result, communication overheads of the models are affected as the proximity criterion is not being considered in the selection process. To overcome these issues and enhance the application performance, we propose a Unification of Proximity and Semantic similarity for Appropriate Resource Selection (UPSARS) algorithm in a decentralised resource discovery model by using a sub-domain ontology structure for Grid computing environments. The purpose of this unification is to get optimised resources for user jobs (Gridlets) so that Grid brokers could select optimum resources in terms of proximity with high semantic relevancy. The algorithm considers both semantic and proximity criteria and selects the nearby nodes resources and reduces the communication overheads in terms of proximity and latency. We design and implement the model using the GridSim and the FreePastry simulation and modelling toolkits. The experimental results provide promising outcomes to reduce communication overheads and enhance resource allocation performance.
Publisher: IEEE
Date: 04-2010
Publisher: Elsevier BV
Date: 10-2011
Publisher: Elsevier BV
Date: 06-2015
Publisher: Emerald
Date: 29-09-2023
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Saadat M. Alhashmi.