A hybrid simulator for an ATM network

*Correspondence to: David J. Parish, High Speed Networks Research Group, Department of Electronic and ElectricalEngineering, Loughborough University, Ashby Road, Loughborough LE11 3TU, U.K. E-mail: [email protected]

Contract/grant sponsor: EPSRC

Received March 1998Copyright ( 2000 John Wiley & Sons, Ltd. Accepted April 1999

INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMSInt. J. Commun. Syst. 2000; 13:179}184

A hybrid simulator for an ATM network

Martin J. Tunnicli!e1 and David J. Parish2,*

1 School of Computer Science and Electronic Systems, Kingston University, Penrhyn Road, Kingston upon Thames,Surrey KT1 2EE, U.K.

2 High Speed Networks Research Group, Department of Electronic and Electrical Engineering, Loughborough University,Ashby Road, Loughborough LE11 3TU, U.K.

SUMMARY

The e$cient management of large interlinked broadband networks requires an e$cient means of networksimulation. Throughout the range of algorithms currently available, a trade-o! exists between accuracy andrun-time: Commercial cell-level simulators successfully mimic speci"c network scenarios to a high degree ofaccuracy, but often require many hours of run-time to produce statistically signi"cant results. Conversely,analytical and probabilistic models yield rapid results for more general scenarios, but these usually lack theexactitude needed for network management purposes. This paper proposes a hybrid simulation structurewithin which an amalgam of di!erent techniques may combine optimum accuracy within economicalrun-time. The software suite applies a detailed cell-level simulation to those regions of the network which areof speci"c interest, whilst using a faster but less accurate &#uid-#ow' approximation to represent the networkin general. This approach is shown to be both accurate and also economical in terms of computation time.Copyright ( 2000 John Wiley & Sons, Ltd.

1. INTRODUCTION

Numerous commercial network simulation packages are available e.g. Reference 1, which operateby emulating a network in precise detail. Extremely long run-times are then needed to producestatistically signi"cant results. Conversely, the use of analytical techniques with associatedsimplifying assumptions e.g. References 2 and 3 signi"cantly reduces these run-times, but withreduced accuracy.

In view of these di$culties, a number of &speed-up' techniques have been developed such asLINK}SIM, devised by Pitts et al.4 Whilst run-time is signi"cantly improved by this approxima-tion, results are generally only accurate for &bursty' (i.e. rapidly changing bit-rate) tra$c.

The work reported in this paper investigates the interaction of two di!erent simulationalgorithms which are combined within a generic hybrid simulator to produce accurate ande$cient ATM-type network simulations.

Figure 1. Schematic representation of cell-level network simulation scheme

2. HYB}SIM NETWORK SIMULATION SUITE

The software (called HYB}SIM) contains two separate simulator cores, both of which are nowdescribed.

2.1. Cell-level simulator

Figure 1 shows a schematic representation of the cell-level portion of HYB}SIM. The network iscomposed of an arbitrary number of interconnected queuing nodes, through which C virtual-channels (VCs) are independently routed. Each node consists of a single-server, "nite-capacity"rst-in}"rst-out (FIFO) bu!er and each cell is identi"ed by its virtual-channel identi"er (VCI),and time-stamp (the time at which it entered the network).

Each bu!er (node) receives cells from a series of &source' bu!ers, and sends them on to a secondseries of &sink' bu!ers. The source and sink bu!ers associated with each bu!er and channel arespeci"ed by an input descriptor structure, which also contains information such as the bu!erservice parameters and the tra$c characteristics. The output structure produced by the programincludes cell losses on a per-channel and/or per-node basis, and the queuing delay distributionsfor each channel.

2.2. Fluid yow simulation

The second simulator core is a cell-rate or #uid-#ow program, based loosely upon an algorithmdevised by Pitts et al.4 This simulator operates upon the same input descriptor structure as itscell-level counterpart, and produces results in an identical format.

Figure 2 shows a schematic representation of the #uid-#ow concept. Discrete cell-streams arerepresented as continuous #uids #owing into and out of a series of reservoirs which represent thequeuing bu!ers. If the arrival-rate for cells in virtual channel i is A

iand the bu!er service rate is

k then the rate of change of queued cells n is given by

dn(t)

dt"A(t)!k, 0(n(t)(N (1)

where

A(t)"C+k/1

Ak(t) (2)

180 M. J. TUNNICLIFFE AND D. J. PARISH

Copyright ( 2000 John Wiley & Sons, Ltd. Int. J. Commun. Syst. 2000; 13:179}184

Figure 2. Schematic representation of #uid-#ow approximation technique

Figure 3. Comparison of cell-level and #uid-#ow performance

and t is the time in time-slots. Similarly the rate at which cell losses liaccumulate is given by

dli

dt"A

i(t)C1!

kA(t)D , n(t)"N (3)

When simulating a network it is necessary to model the output rates from each bu!er, whichsubsequently become the input rates for the various &sink' bu!ers. Since cells joining a queue ofsize n are on average delayed by n/k time-slots, input-rate variations take this length of time topropagate through to the output. The queue output rates D

imay therefore be modelled by the

following equations which must be solved self-consistently for all nodes.

Di(t#n(t)/k)"k

Ai(t)

A(t), n(t)'0 (4)

Di(t)"A

i(t), n(t)"0 (5)

The relative performance of the two approaches can be seen in Figure 3. The #uid-#ow model isseen to produce &smooth' changes in queue occupancy in response to an increase in input cell rate,whilst the cell level simulation accurately models actual changes on a per time-slot basis. The celllevel simulator is therefore the more accurate, but requires a longer processing time.

181A HYBRID SIMULATOR FOR AN ATM NETWORK


Figure 4. Illustration of hybrid mode operation

Figure 5. Simulated network topology and bulk-tra$c statistics



Figure 6. Results obtained using HYB}SIM in cell-level and hybrid modes of operation

3. HYBRIDIZATION OF THE CELL-LEVEL AND FLUID-FLOW ALGORITHMS

HYB}SIM allows the two algorithms to be combined in a hybrid simulation environment. Fig-ure 4 shows the basic philosophy applied to a very simple 2-node network. The area of thenetwork of particular interest (bu!er 1) is partitioned o! and subjected to a complete cell-levelsimulation, whilst the remainder (bu!er 2) is given the #uid-#ow treatment only. At the points ofinteraction between the two simulations, the incoming cell-level cross-tra$c is generated prob-abilistically, using the incoming #uid-rate to generate the appropriate Bernoulli probabilities.

Initially, the global network descriptor is fed directly into the cell-rate core, in order todetermine the approximate cross-tra$c characteristics required for the local descriptor. Oncethese have been established, the local descriptor is fed into the cell-level core in order to acquiredetailed statistics for the channel of interest.

As an example, consider the network shown in Figure 5(i). At the cell-level, the cell-generationfor each virtual channel is considered to be governed by a Bernoulli process, the generationprobability being modulated by a &bulk tra$c pro"le' as shown in Figure 5(ii) for this example.

Let us assume that VC 1 is of direct interest to us. The path of this de"nes a &local network'which passes through only a sub-set of the total network nodes (1, 5 and 9 in this case). Byrunning the simulator in both cell-level and hybrid modes, the cell delay distributions shown inFigure 6(i) are obtained for VC 1. It is seen that a similar distribution is obtained in each case, yetFigure 6(ii) shows a signi"cant reduction in run-time for the hybrid mode of operation.

4. CONCLUSIONS

The HYBRID mode of operation produces a tolerable approximation of the global cell-levelqueuing-delay distribution, but does so in approximately one-third of the run-time. This saving isachieved by the fact that only one third of the nodes in the example global network need to beprocessed. It is possible that for larger networks, a smaller proportion of the total nodes will need

183A HYBRID SIMULATOR FOR AN ATM NETWORK


to be included in the local descriptor, and greater savings in run-times may therefore beachievable. It is also possible that prediction accuracy may be proportional to the percentage ofnodes given cell level analysis. This is an area for future investigation.

ACKNOWLEDGEMENTS

The support of the EPSRC is acknowledged in respect of the material presented in this paper.

REFERENCES

1. Alta Group of Cadence Design Systems, BONeS DESIGNER V 3.0.2. D. D. Kouvatsos, &Entropy maximisation and queuing network models', Ann. Oper. Res., 48, 63}126 (1994).3. K. R. S. Rodrego and M. Woodward, &A slot based modelling study of the Orwell protocol for slotted rings', in

Computer and ¹elecommunication Systems Performance Engineering, M. E. Woodward, S. Datta, S. Szumko, eds,Pentech Press, London, pp. 78}93, 1994.

4. J. M. Pitts, &Cell-rate modelling for accelerated simulation of ATM at the burst level', IEE Proc. Commun., 142(6),379}385 (1995).

AUTHORS' BIOGRAPHIES

Martin J. Tunnicli4e received the BEng Degree in 1987 and the PhD in 1993, fromthe Universities of Bradford and Loughborough, respectively. He has worked inthe International Electronics Reliability Institute (IERI), and later the High SpeedNetworks Group at Loughborough University, and has published 15 conferenceand journal articles. He is currently teaching at the School of Computer Scienceand Electronic Systems, Kingston University.

David J. Parish holds BSc and PhD degrees from the University of Liverpool. Hehas worked as a Scienti"c O$cer at the UKAEA Culham Laboratory and asa Demonstrator in the Electrical Engineering Department at Liverpool University.From 1983 he has held the position of Lecturer and later Senior Lecturer andReader in the Department of Electronic and Electrical Engineering at Lough-borough University. His research interests concern the management, operation,monitoring and application of High Performance Networks. He leads the HighSpeed Networks Group at Loughborough.



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A hybrid simulator for an ATM network