Bio-Inspired Models of Network, Information, and Computing Systems. 5th International ICST Conference, BIONETICS 2010, Boston, USA, December 1-3, 2010, Revised Selected Papers

Research Article

An Evolutionary Game Theoretic Framework for Adaptive, Cooperative and Stable Network Applications

Download
383 downloads
  • @INPROCEEDINGS{10.1007/978-3-642-32615-8_21,
        author={Chonho Lee and Junichi Suzuki and Athanasios Vasilakos},
        title={An Evolutionary Game Theoretic Framework for Adaptive, Cooperative and Stable Network Applications},
        proceedings={Bio-Inspired Models of Network, Information, and Computing Systems. 5th International ICST Conference, BIONETICS 2010, Boston, USA, December 1-3, 2010, Revised Selected Papers},
        proceedings_a={BIONETICS},
        year={2012},
        month={10},
        keywords={Evolutionary game theory Adaptive and cooperative network applications Stability in adaptive networking},
        doi={10.1007/978-3-642-32615-8_21}
    }
    
  • Chonho Lee
    Junichi Suzuki
    Athanasios Vasilakos
    Year: 2012
    An Evolutionary Game Theoretic Framework for Adaptive, Cooperative and Stable Network Applications
    BIONETICS
    Springer
    DOI: 10.1007/978-3-642-32615-8_21
Chonho Lee1,*, Junichi Suzuki1,*, Athanasios Vasilakos2,*
  • 1: University of Massachusetts
  • 2: University of Western Macedonia
*Contact email: chonho@cs.umb.edu, jxs@cs.umb.edu, vasilako@ath.forthnet.gr

Abstract

This paper investigates a bio-inspired framework, iNet- EGT/C, to build adaptive, cooperative and stable network applications. In this framework, each application is designed as a decentralized set of agents, each of which provides a functional service and possesses biological behaviors such as migration, replication and death. iNet-EGT/C implements an adaptive behavior selection mechanism for agents. Its selection process is modeled as a series of evolutionary games among behaviors. iNet-EGT/C allows agents to seek to operate at evolutionarily stable equilibria and adapt to dynamic networks by invoking evolutionarily stable behaviors. It is theoretically proved that each behavior selection process retains stability (i.e., reachability to at least one evolutionarily stable equilibrium). iNet-EGT/C leverages the notion of coalitions for agents to select behaviors as coalitional decisions in a cooperative manner rather than individual decisions in a selfish manner. This cooperative behavior selection accelerates agents’ adaptation speed by up to 78%.