Resource Allocation Technique for Distributed System using Prioritized Class-Based Algorithm
Roshan Kavuri1, Niraj Upadhayaya2, A. Govardhan3

1Roshan Kavuri, Department of Computer Science and Engineering form JNT University, Kukatpally, Hyderabad, India.
2Niraj Upadhayaya, Department of Electronics Engineering and M.S. in Software Systems.
3A Govardhan, Department of Computer Science and Engineering from Osmania University College of Engineering, Hyderabad, India.

Manuscript received on 02 July 2019 | Revised Manuscript received on 09 July 2019 | Manuscript published on 30 July 2019 | PP: 3287-3291 | Volume-8 Issue-9, July 2019 | Retrieval Number: I8183078919/19©BEIESP | DOI: 10.35940/ijitee.I8183.078919

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Abstract: Distributed Systems (DS) are the systems in which the components are distributed at different locations in a network and these components interact with each other by passing messages. In DS each system has a memory and a processor pair. DS is cost-effective, more reliable and faster when compared to the conventional computer systems. But there are some issues in the allocation of resources in such systems as the resources are shared over a number of systems apart from its own individual tasks. The current literature developed various techniques to allocate the resources efficiently by using basic algorithms based on local and global messages and tradeoffs. However, these methods may not be effective as they require special storage and maintenance and constraints the resource availability. In this paper, an efficient resource allocation technique is developed using prioritization and class-based algorithm. The tasks are first given priority and then resources are allocated by fixing a certain percentage of bandwidth for each priority group per execution cycle. The simulation results show that the proposed algorithm is efficient in resource allocation when compared to the conventional techniques.
Keywords: Distributed System, Resource Allocation, Priority, Class-Based Algorithm, Aging.

Scope of the Article: Distributed Computing