Simulation has become the evaluation method of choice for many areas of computer networking research. However, most existing network simulation packages have severe limitations on the size and complexity of the network being modeled. Simulated networks of just a few thousand network elements and a few thousand data
ows will quickly exhaust the computing resources in any reasonably sized computer workstation. Thus the researcher is faced with the dilemma of proving concepts designed to work eciently on networks of tens of millions of elements, using a simulation of only a few thousand elements. The grand challenge we discuss in this paper is that of using simulation to reach credible conclusions about Internet{scale network performance. We present data that demonstrates that simulation of Internet{scale networks is not presently feasible, nor is it likely to be feasible in the near future. We present a summary of current research in the eld of large scale network simulations. These recent advances, while not enabling Internet{scale simulations, do oer the tools with which one can begin to tackle the problem. We sketch one possible approach and describe the issues that need to be resolved in order to realize it.
|
1752
|
Random Early Detection gateways for Congestion Avoidance
– Floyd, Jacobson
- 1993
|
|
331
|
Glomosim: A library for parallel simulation of large-scale wireless networks
– Zeng, Bagrodia, et al.
- 1998
|
|
205
|
An Empirical Model of http Network Traffic
– Mah
- 1997
|
|
182
|
Why we don’t know how to simulate the Internet
– Paxson, Floyd
- 1997
|
|
169
|
PARSEC: A Parallel Simulation Environment for Complex Systems
– Bagrodia, Meyer, et al.
- 1998
|
|
129
|
Tuning RED for web traffic
– Christiansen, Jaffey, et al.
- 2001
|
|
97
|
Time warp on a shared memory multiprocessor
– Fujimoto
- 1989
|
|
81
|
Modeling the global internet
– Cowie, Nicol, et al.
- 1999
|
|
72
|
A Generic Framework for Parallelization of Network Simulations
– Riley, Fujimoto, et al.
- 1999
|
|
65
|
Enabling Large-Scale Simulations: Selective Abstraction Approach to the Study of Multicast Protocols
– Huang, Estrin, et al.
- 1998
|
|
56
|
Towards realistic million-node internet simulations
– Cowie, Liu, et al.
- 1999
|
|
34
|
An Object-Oriented Time Warp Simulation Kernel
– Radhakrishnan, Martin, et al.
- 1998
|
|
33
|
TeD — A Language for Modeling Telecommunication Networks
– Perumalla, Ogielski, et al.
- 1998
|
|
28
|
Opnet 2.4: an environment for communication network modeling and simulation
– Bertolotti, Dunand
- 1993
|
|
23
|
Stateless routing in network simulations
– Riley, Ammar, et al.
- 2000
|
|
17
|
Simulation of ultralarge communication networks
– Rao, Wilsey
- 1999
|
|
15
|
FWNS: A Framework for Webbased Network Simulation
– Rao, Radhakrishnan, et al.
- 1999
|
|
14
|
An Empirical Model of HTTP Network Trac
– Mah
- 1997
|
|
12
|
Efficient large-scale process-oriented parallel simulations
– Perumalla, Fujimoto
- 1998
|
|
12
|
Tuning RED for Web Trac
– Christiansen, Jeay, et al.
- 2000
|
|
8
|
The Telecom framework: A simulation environment for telecommunications
– Unger, Lomow
- 1993
|
|
7
|
The LBNL network simulator." Software on-line: http://www.isi.edu/nsnam
– McCanne, Floyd
- 1997
|
|
7
|
A parallel simulation environment based on timewarp
– Baezner, Lomow, et al.
- 1994
|
|
4
|
Virtual time," in
– Jefferson
- 1985
|
|
2
|
Parallel/Distributed ns." Software online: www.cc.gatech.edu/ computing/ compass / pdns/ index.html
– Riley, Fujimoto, et al.
- 2000
|
|
2
|
Ted models for ATM internetworks
– Perumalla, Andrews, et al.
- 1998
|
|
2
|
An object{ oriented time warp simulation kernel
– Radhakrishnan, Martin, et al.
- 1998
|
|
1
|
jimoto, "Stateless routing in network simulations
– Riley, Aremar, et al.
- 2000
|
|
1
|
Fujimoro, "Efficient large-scale process-oriented parallel simulations
– Perumalla, M
- 1998
|
|
1
|
Time warp on a shared memory multiprocessor
– Fujimoro
- 1989
|
|
1
|
Virtual time," in
– Jeerson
- 1985
|