NDLI: A New Network Topology Evolution Generator Based on Traffic Increase and Distribution Model

Content Provider	IEEE Xplore Digital Library
Author	Xiangqian Chen Makki, K. Kang Yen Pissinou, N.
Copyright Year	2007
Description	Author affiliation: Florida Int. Univ., Miami (Xiangqian Chen; Makki, K.; Kang Yen; Pissinou, N.)
Abstract	Following traffic increase near to network backbone capacity in a domain network, the evolution of backbone topology takes place. In this paper, three main types of evolution methods: link upgrading only method (upgrade link capacity only), node upgrading method (add nodes and links with the same link capacity), and the combinations of previous two are explored. To shunt the saturated traffic efficiently, we propose several node upgrading generators - Adapting Traffic Evolution Topology gEnerators (ATETEs). ATETEs consider traffic distribution and node burden conditions and select the congested link as the main shunting object. The difference among ATETEs lies that they have diverse strategies to choose a node in the congested link as the second shunting aim. Simulation shows that: the type of ATETEs which picks the burdened node in the saturated link as another shunting object has the most effective shunting result. Compare with most of current topology generators such as [BRITE] in [1] which consider little about traffic increase distribution, ATETEs are more efficient to satisfy traffic increase.
Starting Page	56
Ending Page	56
File Size	237517
Page Count	1
File Format	PDF
ISBN	0769528058
DOI	10.1109/ICN.2007.5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-04-22
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Network topology Telecommunication traffic Traffic control Telecommunication network topology Spine Routing Costs Eigenvalues and eigenfunctions Web and internet services IP networks traffic shunting Topology evolution link upgrading node upgrading saturate link traffic increase model burdened node
Content Type	Text
Resource Type	Article

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