Approach for resource management in grid environments using genetic algorithm

The use of ‘proper energy computation system’ is the best method to investigate the problem of energy deficiency, since energy consumption in computational resources is proportional with the work load in the applied program. Also, the best method to improve the use of resources and decrease in energy consumption is dynamic integration of virtual machines which can be a base for the integration of resources in independent systems through virtualization technology, so that it is possible to use resources and equipment for long time and consequently assuring quicker return of investment. Today, grid computation is a new technology connecting heterogeneous computational resources to each other; thus, this structure operates as an individual and integrated virtual machine. Then, it is possible to implement very complex applied programs requiring high processing capacity and huge amount of input data on this virtual machine. In this regard, the purpose of this study is to present an approach for resource management in grid environments using PSO and Genetic algorithms, and also ants colony to find the location of virtual machines.