GEMM, a Genetic Engineering-Based Mutual Model for Resource Allocation of Grid Computing

Resource selection, sharing, and aggregation are the key functions of grid computing. However, managing the resources in a grid-based environment is a stimulating task. It is necessary to update the topographical dispersal of the resources possessed by the various organisations with proper load distribution, and availability patterns. Different types of Users and servers have specific objectives and needs that could be achieved using a grid environment. This article suggests a cost-effective efficient framework for resource management in grid computing to look at and address the resource management difficulties. The proposed framework has three main functions, which help in grid construction, load balancing, and resource allocation. A Genetic engineering approach has been implemented to establish a relationship between the resource pool and the jobs of the nodes that improve resource utilization. The proposed methodology also optimizes the overall cost by minimizing turnaround time. The results of the proposed research are compared with commonly used algorithms and claim 1.5 to 10% better results.