IRMM: An Integrated Resource Management Model for Grid Computing
Makhan Singh

1Makhan Singh, Computer Science & Engineering, UIET, Panjab University, Chandigarh, India. 
Manuscript received on 01 August 2019. | Revised Manuscript received on 08 August 2019. | Manuscript published on 30 September 2019. | PP: 6691-6696 | Volume-8 Issue-3 September 2019 | Retrieval Number: C5804098319/2019©BEIESP | DOI: 10.35940/ijrte.C5804.098319
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Grid computing is a collection of heterogeneous systems or heterogeneous objects that are geographically distributed over a network. Resource management is a process in which various activities like allocation of resources and scheduling are performed for handling issues like load balancing, reliability, scalability, maximum, throughput, minimum expectation time and security. There are several factors that make resource management difficult as different system may have different requirements, properties, conditions and different access and cost models. Resource management in Grid is the method of identifying requirements, finding corresponding resources to the applications, allocating those matching resources, scheduling and monitoring. In Grid resource management resource broker plays the very important role. Users communicate with a resource broker to access the grid information. Resource broker discover the resource that are available and negotiates with their owners or their agents to get the reservation of resources. Number of approaches exists through which one can develop grid resource management systems. In this paper a new architectural model has been implemented for grid resource management which is based on the characteristics of both the Economical model and Hierarchical model.
Keywords: Grid Computing, Resource Management, Scheduler, Economical model and Hierarchical Model.

Scope of the Article:
Cloud Computing