IEEE/ACM Transactions on Networking (TON)
Computational and data Grids in large-scale science and engineering
Future Generation Computer Systems - Grid computing: Towards a new computing infrastructure
Simulation of Dynamic Data Replication Strategies in Data Grids
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
QoS-Aware Replica Placement for Content Distribution
IEEE Transactions on Parallel and Distributed Systems
An efficient replicated data access approach for large-scale distributed systems
CCGRID '04 Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid
Efficient Multi-Source Data Transfer in Data Grids
CCGRID '06 Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid
A QoS-Aware Heuristic Algorithm for Replica Placement
GRID '06 Proceedings of the 7th IEEE/ACM International Conference on Grid Computing
Optimizing server placement in hierarchical grid environments
GPC'06 Proceedings of the First international conference on Advances in Grid and Pervasive Computing
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This paper focuses on two problems related to QoS-aware I/O server placement in hierarchical Grid environments. Given a hierarchical network with requests from clients, the network latencies of links, constraints on servers' capabilities and the service quality requirement, the solution to the minimum server placement problem attempts to place the minimum number of servers that meet both the constrains on servers' capabilities and the service quality requirement. As our model considers both the different capabilities of servers and the network latencies, it is more general than similar works in the literatures. Instead of using a heuristic approach, we propose an optimal algorithm based on dynamic programming to solve the problem. We also consider the optimal service quality problem, which tries to place a given number of servers appropriately so that the maximum expected response time is minimized. We prove that an optimal server placement can be achieved by combining the dynamic programming algorithm with a binary search on the service quality requirement. The simulation results clearly show the improvement in the number of servers and the maximum expected response time.