Enhanced job scheduling algorithm with budget constraints in computational grids

In present era, technical problems are complex enough to be resolved by a single computer. Grid Computing is a promising field that deals with exploiting the idle CPU cycles of resources connected in a network. Job scheduling is a most demanding subject in computing grids. An effective scheduling strategy is required to utilize the resources in grid and to balance the overall load on them. This paper presents an enhanced job scheduling algorithm with budget constraint which extends existing algorithm to include economy factor into account. The main contribution of our work is dual: Firstly it tries to balance load of overall grid system and secondly it assigns tasks to resources with best computing capability which lies within the budget specified by each user. The performance of proposed algorithm is assessed by conducting simulations using GridSim. Observations prove that this algorithm achieves reduced average cost of execution for jobs to great extent so that it lies in the user's stated budget.