Multi-agent brokering approach and firefly algorithm for job scheduling in grid environment

With the advancements in Science and Technology, capabilities for handling complex problems increase through optimal usage and management of computing power. Resources being distributed are reality, identifying and accumulating required resources for solving problem is a difficult task. In order to overcome this burden the recent trend is to effectively use grid computing, supporting resource sharing. The goal is to aggregate idle network, processing resources such as CPU cycles, and storage spaces to facilitate optimal utilization and computing. For the above, we need an effective method for identifying service providers based on all needs of any job for successful execution. The assignments and scheduling of the jobs should result in efficient way to solve the problem and promote optimal use of resource .This project proposes to address the above problem using Multi Agent Brokering Approach for the identification of service providers in a grid environment. The Multi Agent Approach can ensure that the agents can specialize in identification of service provider for scheduling jobs. Firefly algorithm used for reducing the make span time by its status table, records the behavior in detail as well. Also the proposed algorithm makes weak ones to jump to new positions to attain high probability. This leads to increase the performance better in finding the optimal solution. The experimental result shows that the Firefly mechanism is more efficient than standard firefly algorithm and other heuristic methods.