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Volume & Issue no: Volume 11, Issue 5, May 2022


Author Name:
R.Ananthi Lakshmi, Dr.S.Vidhya
ABSTRACT Grid computing is hailed the futuristic computing revolution for business applications and big scale grids are complicated systems, which contains many thousands of elements that belong to different fields. It is a massive challenging task to plan the facilities so that quality of service (QoS) can be ensured in these environments. It is a distributed high performance computing principle, which provides different kinds of resources (such as computing, storage, communication) to resourceoriented user functions. The scheduling of these jobs are performed for the allocation of the Grid resources available with efficiency to attain improved system throughput and to fulfill the user needs. The problem of task scheduling has emerged to become complicated with the exponential increase in the Grid systemsize. In the available system, there is no guarantee ofload balancing and in some scenarios, there is a reduction in the process speed owing to convergence problems. Therefore, there is a considerable degradation in the overall grid computing performance. In order to get over the above stated problems, in this research work, Max-Min Heuristic (MMH) and Improved Ant Colony Optimization (IACO) algorithm is introduced to bring an improvement in the load balancing besides optimally allocating the resources on grid. The proposed system encompasses important stages referred as system model, load balancing, resource allocation and path and node-level fault resistance. At first, the number of resources, number of tasks, Virtual Machine (VM) and number of grid users over the grid computing are taken into consideration. In this research work, load balancing is performed with the help of MMH algorithm which is helpful inbalancing the entire workload over grid. Load balancing is attained by reassigning tasks from over-loaded nodes to under-loaded nodes. Next, the resources are allocated with the help of IACO algorithm and it is utilized for choosing increasingly optimal resources with efficiency. It also highlights on limiting the cost complexity and improving the VM performance in grid. The fault resistance is achieved with the help of Fit First (FF) heuristic algorithmthat decreases the failure periods and improves the data transfer time. Grid performance is also improved through the idle time reduction of the resources and equal distribution of the unmapped tasks among the existing resources. It can be concluded from the simulation result that the proposed IACO+FF algorithm yields improved performance in terms of improved accuracy, reduced error rate, cost and time overhead compared to the available algorithms Keywords: Grid computing, Max-Min Heuristic (MMH), Improved Ant Colony Optimization (IACO) algorithm, load balancing, resource allocation, fault tolerance, Fit First (FF) heuristic algorithm
Cite this article:
R.Ananthi Lakshmi, Dr.S.Vidhya , " EFFICINET LOAD BALANCING AND OPTIMAL RESOURCE ALLOCATION USING MAX-MIN HEURISTIC APPROACH AND HYBRID OPTIMIZATION ALGORITHM OVER GRID COMPUTING" , International Journal of Application or Innovation in Engineering & Management (IJAIEM) , Volume 11, Issue 5, May 2022 , pp. 160-177 , ISSN 2319 - 4847.
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