Node degree-aware link cost for traffic load-distribution in large-scale networks

Hitomi Tamura*, Mario Köppen, Masato Uchida, Masato Tsuru, Yuji Oie

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Traffic Engineering (TE) is required for reducing highly-loaded links / nodes in parts of a network, thereby distributing the traffic load in the network. For efficient use of network resources, it is important to efficiently map traffic demands to network resources. Therefore, we should consider an appropriate definition of "distance" in networks with the topological features of the network instead of traffic demands. Recent studies have demonstrated a scale-free property of network topology, and node outbound degree distribution is an important factor in the scale-free networks. This paper proposes a new definition of "distance" between two arbitrary communication nodes in the Internet by using node degree information for avoiding congestion in the network. Some simulation results show that the proposed scheme can distribute traffic load from high degree nodes to other nodes, and thus provides robustness of networks.

Original languageEnglish
Title of host publicationProceedings - 3rd IEEE International Conference on Intelligent Networking and Collaborative Systems, INCoS 2011
Pages299-304
Number of pages6
DOIs
Publication statusPublished - 2011 Dec 1
Externally publishedYes
Event3rd IEEE International Conference on Intelligent Networking and CollaborativeSystems, INCoS 2011 - Fukuoka, Japan
Duration: 2011 Nov 302011 Dec 2

Publication series

NameProceedings - 3rd IEEE International Conference on Intelligent Networking and Collaborative Systems, INCoS 2011

Other

Other3rd IEEE International Conference on Intelligent Networking and CollaborativeSystems, INCoS 2011
Country/TerritoryJapan
CityFukuoka
Period11/11/3011/12/2

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications

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