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Mạng và viễn thông P31

Trafic Monitoring and Forecasting Having explained the underlying principles of electrical communication and the statistical ‘laws’ oftelecommunicationstraffic, we cannowconsiderthepracticaldesignandoperationof networks. A prime concern is to ensure that there are adequate resources to meet the traffic demand, or to prioritize the use of resources when shortfalls are unavoidable. Two things have to be done to keep abreast of demand. | Networks and Telecommunications Design and Operation Second Edition. Martin P. Clark Copyright 1991 1997 John Wiley Sons Ltd ISBNs 0-471-97346-7 Hardback 0-470-84158-3 Electronic 31 Traffic Monitoring and Forecasting Having explained the underlying principles of electrical communication and the statistical laws of telecommunications traffic we can now consider the practical design and operation of networks. A prime concern is to ensure that there are adequate resources to meet the traffic demand or to prioritize the use of resources when shortfalls are unavoidable. Two things have to be done to keep abreast of demand. These activities are the monitoring and future forecasting of network use. In this chapter we shall review the parameters to be applied in measuring traffic activity and go on to provide an overview of some forecasting models for the prediction of future demand. Used as an input to the teletraffic engineering formulae of Chapter 30 the forecast values of future traffic can be used to predict the future network equipment requirements on which the overall planning process will be based. 31.1 MEASURING NETWORK USAGE We discussed different methods of defining the volume of network usage in Chapter 30. These methods in various ways served to measure over a predetermined period of time any of the following parameters the total number of calls or messages the total conversation time the total holding time holding time includes both conversation time and call set-up time the total number of data characters e.g. packets frames or cells conveyed We have covered the concept of traffic intensity which is a measure of the average call demand. We have shown how traffic intensity measured in Erlangs determines the number of circuits needed on a route in a circuit-switched network to maintain a given grade of service. For this reason it is usual practice to monitor the magnitude of the 555 556 TRAFFIC MONITORING AND FORECASTING traffic intensity and to predict its .