An adaptive data replication algorithm
ACM Transactions on Database Systems (TODS)
Generating representative Web workloads for network and server performance evaluation
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Optimal Placement of Replicas in Trees with Read, Write, and Storage Costs
IEEE Transactions on Parallel and Distributed Systems
The case for geographical push-caching
HOTOS '95 Proceedings of the Fifth Workshop on Hot Topics in Operating Systems (HotOS-V)
SPDP '95 Proceedings of the 7th IEEE Symposium on Parallel and Distributeed Processing
WebWave: Globally Load Balanced Fully Distributed Caching of Hot Published Documents
ICDCS '97 Proceedings of the 17th International Conference on Distributed Computing Systems (ICDCS '97)
Choosing Replica Placement Heuristics for Wide-Area Systems
ICDCS '04 Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS'04)
Replication algorithms for the World-Wide Web
Journal of Systems Architecture: the EUROMICRO Journal
Static and adaptive distributed data replication using genetic algorithms
Journal of Parallel and Distributed Computing
On Optimal Replication of Data Object at Hierarchical and Transparent Web Proxies
IEEE Transactions on Parallel and Distributed Systems
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We consider the problem of placing copies of objects in a distributed web server system to minimize the cost of serving read and write requests when the web servers have limited storage capacities. We formulate the problem as a 0-1 optimization problem and present a hybrid particle swarm optimization algorithm to solve it. The proposed hybrid algorithm makes use of the strong global search ability of particle swarm optimization (PSO) and the strong local search ability of tabu search to obtain high quality solutions. The effectiveness of the proposed algorithm is demonstrated by comparing it with the genetic algorithm (GA), simple PSO, tabu search, and random placement algorithm on a variety of test cases. The simulation results indicate that the proposed hybrid approach outperforms the GA, simple PSO, and tabu search.