Constella: a complete IP network topology discovery solution

  • Authors:
  • Fawad Nazir;Tallat Hussain Tarar;Faran Javed;Hiroki Suguri;Hafiz Farooq Ahmad;Arshad Ali

  • Affiliations:
  • National ICT Australia, Australia and University of New South Wales, Australia and NUST Institute of Information Technology, Pakistan;European Oeganization For Nuclear Research, Switzerland and NUST Institute of Information Technology, Pakistan;NUST Institute of Information Technology, Pakistan;Communication Technologies, Japan;NUST Institute of Information Technology, Pakistan and Communication Technologies, Japan;NUST Institute of Information Technology, Pakistan

  • Venue:
  • APNOMS'07 Proceedings of the 10th Asia-Pacific conference on Network Operations and Management Symposium: managing next generation networks and services
  • Year:
  • 2007

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Abstract

Network topology discovery for the large IP networks is a very well studied area of research. Most of the previous work focus on improving the efficiency in terms of time and completeness of network topology discovery algorithms and less attention has been given to the deployment scenarios and user centric view of network topology discovery. In this paper we propose a novel network topology discovery algorithm and a flexible architecture. The silent features of our work are loosely coupled architecture, network boundary aware architecture, discovering the transparency of dumb/incorporative elements, flexible network Visualization, and intelligent algorithm for quick response to user discovery request. To the best of our knowledge no existing solution has focused on the above mentioned requirements. After several years of research experience in developing a complete, flexible and scalable solution for network topology discovery we propose to divide it into three loosely coupled components: topology discovery algorithm, topology object generation and persistence, and topology visualization. In this paper we will present our proposed integrated complete network topology discovery solution, discuss the motivation of our proposed architecture, the efficiency and user-friendliness of our work. Our results show that the average accuracy of our algorithm is 92.4% and takes one second to discover 100 network elements.