Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Computer-aided system integration for data-intensive multimedia applications (poster session)
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
IEEE/ACM Transactions on Networking (TON)
i-CAD: A Rapid Prototyping CAD Tool for Intranet Design
RSP '03 Proceedings of the 14th IEEE International Workshop on Rapid System Prototyping (RSP'03)
Content Distribution Architecture Using Network Layer Anycast
WIAPP '01 Proceedings of the Second IEEE Workshop on Internet Applications (wiapp '01)
A genetic algorithm for designing distributed computer networktopologies
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Producing content producers [computer animation]
IEEE Communications Magazine
Automated design of hierarchical intranets
Computer Communications
Constrained mirror placement on the Internet
IEEE Journal on Selected Areas in Communications
Query-based data aggregation within WSN through Monte Carlo simulation
Proceedings of the 9th International Conference on Advances in Mobile Computing and Multimedia
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This paper presents a Monte Carlo simulator (MCS), which is embedded within a computer-aided design tool called iCAD. iCAD is a design and analysis tool that concurrently synthesizes and integrates network topology, server placement and file allocation for application-specific networks. We formulated the three problems as a single optimization problem, where the objective is to minimize the design cost, and to satisfy both the design and performance constraints. iCAD used an evolutionary approach to search the design space; therefore, we embedded two performance evaluation methodologies: analytical and simulation within iCAD. During each evolution cycle, an analytical queuing model (network of M/M/1 queues) is used to evaluate the performance of the network topology, which carries both the client-to-client and client-server traffic. On the other hand, a Monte Carlo simulator (MCS) is used to evaluate the performance of the placed servers within the network. MCS is used due to some uncertainty concerning with the timing of file-transfer requests by the clients that could lead to unacceptable performance by the servers. Uncertainty is introduced by randomizing the timing of files' requests by each server, and then simulating the file-transfer within a server over time. The two heterogeneous analysis methodologies (queuing and simulation) complement each other in evaluating each candidate design as fast as possible; moreover, our experimental results have demonstrated the effectiveness of iCAD in finding good designs from a large design space (65 to 150 client nodes) in a reasonable amount of time.