title: Self-organizing network services with evolutionary adaptation.
abstract: This paper proposes a novel framework for developing adaptive and scalable network services. In the proposed framework, a network service is implemented as a group of autonomous agents that interact in the network environment. Agents in the proposed framework are autonomous and capable of simple behaviors (e.g., replication, migration, and death). In this paper, an evolutionary adaptation mechanism is designed using genetic algorithms (GAs) for agents to evolve their behaviors and improve their fitness values (e.g., response time to a service request) to the environment. The proposed framework is evaluated through simulations, and the simulation results demonstrate the ability of autonomous agents to adapt to the network environment. The proposed framework may be suitable for disseminating network services in dynamic and large-scale networks where a large number of data and services need to be replicated, moved, and deleted in a decentralized manner.
authors.affiliation: Donald Bren School of Information and Computer Sciences, University of California, Irvine, CA 92697, USA. tnakano@ics.uci.edu
authors.forename: Tadashi
authors.initials: T
authors.lastname: Nakano
authors.forename: Tatsuya
authors.initials: T
authors.lastname: Suda
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods; D012815:Signal Processing, Computer-Assisted; D013685:Telecommunications