Solving Grid Scheduling Problems Using Selective Breeding Algorithm

Grid scheduling is characterized as the way toward settling on planning choices including resources over multiple administrative domains. This procedure can search through different administrative areas to utilize a particular machine or scheduling one job for exhausting various resources at a particular node or multiple nodes. From a grid point of view, a job is anything that needs a resource. The primary objective of grid is to give service with high dependability and minimal effort for substantial volumes of clients and support teamwork. In this paper, we consider a directed acyclic graph (DAG) with nodes and edges where the nodes are considered the task and the edges specify the order of execution of the tasks as a grid. This kind of problem is called the precedence-constrained problem. The selective breeding algorithm is an efficient algorithm to solve NP-hard problems. One such example of NP-hard problem is the precedence-constrained problem. So we consider SBA algorithm to solve precedence-constrained problems and found optimal solution of 13 units when compared with the traditional methods of 23 units. And it is also proved that the amount of waiting time is reduced greatly when compared to the traditional methods. So by implementing SBA for the grid scheduling problem more time is saved and is proved to be efficient.