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138 - The external LAN traffic is extremely bursty during high load situations, and peaks, of 10 seconds duration, were up to 7 times the available, theoretical WAN link capacity. These observations yield requirements on the future and existing WAN services that shall carry the LAN interconnection traffic. The client-server traffic has proven asymmetrical, therefore, WAN links must supply bandwidth per direction. Also, the public network must be capable of handling bursty LAN traffic without severe delays or lost frames. Finally, services must be flexible, in order to offer required capacity according to instantaneous LAN interconnection traffic demands. 7 Suggestions for further work A study of cost versus performance for the WAN services used for LAN interconnections is an appropriate next step for utilizing the results from measurements of the type presented in this report. The obtained external traffic measurement data for a particular LAN site can be applied to a suitable WAN service, and issues like tariff, throughput, delay and buffer sizes should be looked into. In this work, the whole LAN has been regarded as a source and sink for external traffic, only recognized by its applications, configuration and number of users. In order to understand the applications generating the traffic on the LAN interconnection, a study per application should be performed. One station running a certain application, e.g. FTP, can be defined as a source and sink, and this specific traffic can be analysed with respect to traffic intensity and MAC frame characteristics. Then, a large number of stations running the same application could be employed, and the results compared to the one station example would give an indication of the traffic load per station for different number of stations. Measurements with shorter integration times than 10 seconds for predefined periods of the day should be conducted for better reconstruction of extreme traffic peaks. As WAN protocol analysers become more advanced, the measurements can be carried out on the WAN side, which would give an exact picture of the LAN interconnection traffic flowing in the public network. The integration time introduced in these measurements hides information about the exact traffic patterns for data frames, packets or cells. For modelling of LANs as ATM sources, measurements at the cell level are required. For higher level queue models, obtained distributions of mean values for frame interarrival times and frame sizes can be used. In this case, the interarrival time distribution of means will represent the arrival or departure rate, and the frame size distribution of means will represent the service rate. 8 References 1 Gaaren, S. LAN interconnection traffic measurements : the results. Kjeller, <strong>Telenor</strong> Research, 1994. (TF R 52/94.) 2 Gaaren, S. LAN interconnection traffic measurements : the methodology. Kjeller, <strong>Telenor</strong> Research, 1994. (TF R 51/94.) 3 Leland, W E et al. On the self-similar nature of ethernet traffic. I: SIG- COMM ’93, New York, ACM, 1993. 4 Jain, R. The art of computer systems performance analysis. New York, Wiley, 1991. ISBN 0-471-50336-3. 5 Acharya, M K et al. A flow model for computer network traffic using real-time measurements. I: 2nd conference on telecommunication systems, modelling and analysis, Nashville, Tennessee, 1994, 141–149. 6 Heegaard, P E, Helvik, B E. ATM traffic experiments : source type models and traffic scenarios. Trondheim, SINTEF DELAB, 1994. 7 Falk, G, Michel, T (eds.). Interop 93 : LAN interconnection architectures : solutions, trade-offs, and trends. San Francisco, CA, 1993. 8 Miller, M A. Internetworking : a guide to network communications LAN to LAN : LAN to WAN. Hemel Hempstead, Prentice Hall, 1991. ISBN 0-13-365974-7. 9 Caceres, R et al. Characteristics of wide-area TCP/IP conversations. I: SIGCOMM ‘91, New York, ACM 1991.
Aspects of dimensioning transmission resources in B-ISDN networks BY INGE SVINNSET 1 Introduction The complexity of current telecommunication networks makes it very important to have good network planning routines to meet the demands of the customers with the necessary investments. One important part of this is the dimensioning of the needed transmission resources, and a subtask is the dimensioning of the number of channels needed between each pair of network switching nodes. This is what we understand by dimensioning of trunk groups. Input to this task is the forecast traffic demands and the mapping of these demands onto the network routes where the various calls can be placed. This is then again mapped onto the trunk groups taking part in the route. In telephony a channel is a dedicated physical resource that must be reserved for a single call for the whole lifetime of the call. In today’s digital networks these physical resources are divided in timeslots (Time Division Multiplexing, TDM). Every Nth slot is reserved for a single call, i.e. every Nth slot belongs to one channel where N depends on the rate of the physical medium, e.g. 2 Mb/s or 34 Mb/s. In ATM a channel has a more complex definition and the amount of resources needed for one channel is not static but depends on the needed data rate and the needed quality of service. The data rate of a channel may also vary in time. This complexity gives an increased flexibility and a possibility for saving capacity (statistical multiplexing gain) and these are also two of the reasons for the attractiveness of ATM. But it also creates new problems and new challenges for the network planning task. In this paper we will present some methods for dimensioning of the required capacity of trunk groups in an ATM network. The task is to provide enough capacity for the forecast traffic needs and at the same time satisfy the given quality of service constraints. A subtask of this is to look for ways of dividing capacity between different traffic types to obtain a more effective utilisation of the network resources. The intention of such a division is to give a lower dimensioned capacity than we would have obtained without using such methods. This division will have implications for the connection admission procedure. An ATM link (= transmission path in [5]) is in this context a physical transmission channel, characterised by a constant bit rate (for example 150 Mb/s or 600 Mb/s) and extending between a pair of transmission path connection end-points. A virtual channel connection (VCC) is an end-to-end virtual connection, set up between two users and characterised by traffic parameters (for example peak bit rate and mean bit rate). A virtual path connection (VPC) is set up between two ATM switching nodes, between a user and a switching node or between two users. It can be characterised in the same manner as a VCC. An ATM link can contain one or many VPCs and a VPC can contain one or many VCCs. For more exact definitions and more information about these concepts we refer to [5]. This paper considers only VPCs or VCCs, i.e. we do not treat the problems related to bundling VCCs into VPCs. Except for the first part of this paper where we treat the multi-dimensional Erlang loss formula, we only treat linear Connection Admission Control (CAC) functions. The connection admission is then based on the calculation of an equivalent bandwidth for each connection. Ignoring the Cell Delay Variation (CDV) tolerance this equivalent bandwidth may equal the peak bit rate or may be less than the peak bit rate but higher than the mean bit rate. Taking CDV tolerance into account the equivalent bandwidth may become higher than the declared peak bit rate if the CDV tolerance is allowed to take a high value. 2 Performance parameters that impact dimensioning Performance parameters are divided into direct and derived performance parameters. Derived parameters such as availability will not be considered here. Direct performance parameters can be divided into - call/connection processing performance parameters - information transfer performance parameters. The connection processing performance parameters concern the establishment, release and parameter change of connections. These are - connection rejection probability - connection set-up delay - connection release delay - in-call connection parameter change delay. The information transfer performance parameters to be considered are - cell error ratio - cell loss ratio - cell misinsertion rate - severely errored cell block ratio - cell transfer delay - cell delay variation. Of these performance parameters the two parameters that have most impact on trunk dimensioning are: - connection rejection (blocking) probability, and - maximum cell loss ratio. The connection blocking probability is the probability that the network is not able to deliver a connection between two users due to lack of network resources or due to errors in the network. A network dimensioned for every possible circumstance will be a very expensive network, if possible to realise at all. For this reason we need to set a positive value for this parameter, a connection blocking objective, taking both cost and user satisfaction into account. The connection blocking objective may differ between the services. If no service protection is used the high capacity services will certainly experience a higher probability of connection blocking than the low capacity services. This can be very unsatisfactory. Although it is not necessary to offer the same maximum connection blocking probability for all services, it is necessary to use some kind of service protection method to control the quality of service. Service protection methods should be used to dimension the network with specified connection blocking objectives for the different services. Dimensioning should be made for busy hour in the same manner as for traditional circuit switched networks, but the busy hour may be different for the different services. When it comes to the information transfer performance, different services will have different requirements with regard to cell delay, cell delay variation and cell loss ratio. For the exact definitions of the information transfer performance parameters, see [6]. Some services like telephony are not so sensitive to cell losses, but cell delay and delay variation must be small. For data services the requirement 139
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Contents Feature Guest editorial, A
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BPS 800.000 8 700.000 600.000 500.0
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16 0 Local calls mean: 27 sec. Std.
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20 j k λ ij µji λ ik µ ki λ ir
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30 Frame 6 Basic queuing model From
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34 Since Gw (t) is the survivor fun
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40 3 Gaaren, S. LAN interconnection
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48 Telephone Systems” (published
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advantage is that it is generally v
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