An introduction to genetic algorithms
An introduction to genetic algorithms
Dynamically Selecting Optimal Distribution Strategies for Web Documents
IEEE Transactions on Computers
Dynamic Replica Placement for Scalable Content Delivery
IPTPS '01 Revised Papers from the First International Workshop on Peer-to-Peer Systems
A Short Tutorial on Evolutionary Multiobjective Optimization
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
SAINT '01 Proceedings of the 2001 Symposium on Applications and the Internet (SAINT 2001)
On the Placement of Web Server Replicas
On the Placement of Web Server Replicas
A Dynamic Object Replication and Migration Protocol for an Internet Hosting Service
ICDCS '99 Proceedings of the 19th IEEE International Conference on Distributed Computing Systems
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Parameter control in evolutionary algorithms
IEEE Transactions on Evolutionary Computation
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This paper proposes an evolutionary framework where a network service is created from a group of autonomous agents that interact and evolve. Agents in our framework are capable of autonomous actions such as replication, migration and death. An evolutionary mechanism isdesigned using genetic algorithms in order to evolve their behavior over generations. A simulation study is carried out to demonstrate the ability of the evolutionary mechanism to improve the network service performance (e.g., response time) in a decentralized and self-organized manner. This paper describes the evolutionary mechanism, its design and implementation, and evaluates it through simulations