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Constella: A Complete IP Network Topology Discovery Solution

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Managing Next Generation Networks and Services (APNOMS 2007)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 4773))

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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.

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Shingo Ata Choong Seon Hong

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© 2007 Springer-Verlag Berlin Heidelberg

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Nazir, F., Tarar, T.H., Javed, F., Suguri, H., Farooq Ahmad, H., Ali, A. (2007). Constella: A Complete IP Network Topology Discovery Solution. In: Ata, S., Hong, C.S. (eds) Managing Next Generation Networks and Services. APNOMS 2007. Lecture Notes in Computer Science, vol 4773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75476-3_43

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  • DOI: https://doi.org/10.1007/978-3-540-75476-3_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75475-6

  • Online ISBN: 978-3-540-75476-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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