Novel adaptive scheduling algorithm for computational grid

Scheduling is an important issue in computational grid. In computational grid, computing resources are connected through networks. So, if we want to take advantage of computational grid, an efficient scheduling algorithm is necessary to assign jobs to the appropriate nodes. Our adaptive load sharing algorithms uses a timer to find a receiver/sender. If receiver does not find a sender it broadcasts a message to decrease threshold. Similarly if sender does not find receiver within poll limit it broadcasts a message to increase the threshold. We implemented distributed algorithms using a decentralized approach that improves average response time of jobs. The job arrival process and the CPU service times are modeled using M/M/1 queuing model. We compared the performance of our algorithms with similar algorithms in the literature. We present some results that verify the effectiveness of our scheme.