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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Computer Networksarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Computer Networks
Article . 2008 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
DBLP
Article . 2008
Data sources: DBLP
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TranSim: Accelerating simulation of large-scale IP networks through preserving network invariants

Authors: Hwangnam Kim; Jennifer C. Hou; Hyuk Lim;

TranSim: Accelerating simulation of large-scale IP networks through preserving network invariants

Abstract

In this paper, we propose a fast simulation framework, TranSim, that expedites simulation by reducing the rate of generating packet-events. In the framework, we transform an IP network into an alternate network that generates a smaller number of packet-events, conduct simulation in the ''transformed'' network, and extrapolate simulation results for the original network from those obtained in the ''transformed'' network. We formally prove that, as long as the network invariant - the bandwidth-delay product - is preserved, the network dynamics, such as the queue dynamics and the packet dropping probability at each link, and TCP dynamics, such as the congestion window, RTTs, and rate dynamics, are also preserved in the course of network transformation. We implement TranSim in ns-2, and carry out a simulation study to evaluate it against packet-level simulation, with respect to the capability of capturing transient, packet-level network dynamics, the reduction in the execution time and memory usage, and the discrepancy in the network throughput. The simulation results indicate maximally two orders of magnitude improvement in the execution time, and the performance improvement becomes more prominent as the network size increases (in terms of the number of nodes, the number of flows, the complexity of topology, and link capacity) or as the degree of downsizing increases. The memory usage incurred in TranSim is comparable to that in packet-level simulation. The error discrepancy between TranSim and packet-level simulation, on the other hand, is between 1% and 10% in a wide variety of network topologies, inclusive of randomly generated topologies, traffic loads with different AQM strategies, different combination of operating systems and hardware systems.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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