J4 ›› 2009, Vol. 36 ›› Issue (3): 547-552.

• Original Articles • Previous Articles     Next Articles

Self adaptive network topology inference algorithm in tomography

ZHAO Hong-hua;CHEN Ming;WEI Zhen-han   

  1. (Institute of Command Automation, PLA Univ. of Sci. & Tech., Nanjing  210007, China)
  • Received:2008-03-10 Revised:2008-07-17 Online:2009-06-20 Published:2009-07-04
  • Contact: ZHAO Hong-hua E-mail:zhhahuatian@163.com

Abstract:

There are a few network topology inference techniques based on network tomography, but all of them use only one network performance characteristics, which leads to many limits when the network load is different. In order to reduce the limits of the inference based on one network performance characteristics, a self adaptive network topology inference method is proposed which joines multiple network performance parameters self-adaptively in inference. In applying the self adaptive network topology inference, no additional traffic is needed except for some calculation, and the inference method could be applied in complex networks with different loads. The self adaptive method is analyzed theoretically and validated through simulations by NS2, and the results of simulation illustrate that the self-adaptive inference method could infer network topology correctly when faced with networks whose load changes greatly.

Key words: network tomography, topology inference, self adaptive

CLC Number: 

  • TP393