4th International IEEE Conference on Broadband Communications, Networks, Systems

Research Article

A Biologically Inspired Policy Based Management System for Survivability in Autonomic Networks

  • @INPROCEEDINGS{10.1109/BROADNETS.2007.4550420,
        author={Sasitharan Balasubramaniam and Dmitri Botvich and William Donnelly and John Strassner},
        title={A Biologically Inspired Policy Based Management System for Survivability in Autonomic Networks},
        proceedings={4th International IEEE Conference on Broadband Communications, Networks, Systems},
        proceedings_a={BROADNETS},
        year={2008},
        month={6},
        keywords={Biochemistry  Biological system modeling  Blood  Quality of service  Robustness  Sugar  Technology management  Telecommunication network management  Telecommunication traffic  Web and internet services},
        doi={10.1109/BROADNETS.2007.4550420}
    }
    
  • Sasitharan Balasubramaniam
    Dmitri Botvich
    William Donnelly
    John Strassner
    Year: 2008
    A Biologically Inspired Policy Based Management System for Survivability in Autonomic Networks
    BROADNETS
    IEEE
    DOI: 10.1109/BROADNETS.2007.4550420
Sasitharan Balasubramaniam1,*, Dmitri Botvich1,*, William Donnelly1,*, John Strassner2,*
  • 1: Telecommunication Software and Systems Group Waterford Institute of Technology, Carriganore Waterford, Ireland
  • 2: Motorola Labs, Schaumburg, IL USA
*Contact email: sasib@tssg.org, dbotvich@tssg.org, wdonnelly@tssg.org, john.strassner@motorola.com

Abstract

The vision of Autonomic Network Management seeks self-governance (e.g. self-organisation, self-management) capabilities amongst network devices and system to minimise complexities found in current network management. Policy based management system provides a mechanism to counter these complexities, where the system provides a consistent model for decision making process. In this paper we propose bio-inspired mechanisms to support network survivability that is integrated with policy based management. Our solution is based on adaptation and integration of various biological principles such as Blood Glucose Homeostasis, Chemotaxis, Reaction-Diffusion and Hormone Signaling. The bio-inspired principles support a high degree of robustness, which is a key feature towards adapting in fluctuating network environment. Simulations results have also been presented to illustrate our proposed solution.