Optimizing server placement in hierarchical grid environments

In this paper, we address some problems related to server placement in Grid environments. Given a hierarchical network with requests from clients and constraints on server capability, the minimum server placement problem attempts to place the minimum number of servers that satisfy requests from clients. Instead of using a heuristic approach, we propose an optimal algorithm based on dynamic programming to solve the problem. We also consider the balanced server placement problem, which tries to place a given number of servers appropriately so that their workloads are as balanced as possible. We prove that an optimal server placement can be achieved by combining the above algorithm with a binary search on workloads. This approach can be further extended to deal with constrains on network capability. The simulation results clearly show the improvement in the number of servers and the maximum workload. Furthermore, as the maximum workload is reduced, the waiting time is reduced accordingly.