A Fuzzy Rule-Based Optimisation Model for Efficient Resource Utilisation in a Grid Environment Using Proximity Awareness and Semantic Technology

Abdul Khalique Shaikh (), Saadat M. Alhashmi (), Rajendran Parthiban () and Amril Nazir ()
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Abdul Khalique Shaikh: Information Systems Department, Sultan Qaboos University, Muscat, Oman
Saadat M. Alhashmi: College of Business, University of Sharjah Sharjah, UAE
Rajendran Parthiban: School of Engineering, Monash University Malaysia, Bandar Sunway, Malaysia
Amril Nazir: Department of Computer Science, Taif University, Saudi Arabia

Journal of Information & Knowledge Management (JIKM), 2018, vol. 17, issue 02, 1-21

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.

Keywords: Grid computing; high-performance computing; cloud computing; resource allocation; resource utilisation; proximity; semantic (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1142/S0219649218500235

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