**4. Summary**

348 Telecommunications Networks – Current Status and Future Trends

Integration of individual modules in the global aggregate traffic intensity model is schematically illustrated in Fig. 7. Instead of simulating individual sources and destinations, a geographic distribution of relative traffic source intensity is calculated for any location on the surface of the Earth. The cumulative traffic intensity of sources within its coverage area are mapped to the currently serving satellite. Satellite footprint coverage areas on the Earth, overlaid over geographic distribution of traffic sources and destinations, are identified from

With the normalized cumulative traffic on each satellite, which is proportional to the intensity of traffic sources in the satellite's coverage area, it is possible to modulate the selected traffic source generator (not shown in Fig. 7). Thus data packets are actually generated considering the relative traffic intensity experienced by a particular satellite.

The destination satellite is selected for each packet in accordance with the traffic flow pattern. The probability of selecting a given satellite as a destination node is proportional to its coverage share in the destination region divided by the sum of all coverage shares in that region. Thus, although in a simplified manner, the model is taking into consideration also multiple coverage. In the case of using different traffic source models to generate distinct types of traffic by global aggregate traffic intensity model, one should also consider

traffic flows between geographical regions from Europe to Europe

mapping of traffic sources and destinations

geographical distribution of traffic sources and destinations

temporal variation of traffic load

on satellites

**3.5 Global aggregate traffic intensity model** 

the satellite positions in a given moment.

Fig. 7. Global aggregate traffic intensity model.

different, service specific traffic flow patterns.

Traffic engineering involves adapting the routing of traffic to the network conditions with two main goals: (i) providing sufficient quality of service, which is important from user's point of view, and (ii) efficient use of network resources, which is important for operators of telecommunication's network. The presented routing and traffic engineering issues addressed both goals that are explained using the ISL network as a concrete example of highly dynamic telecommunication network with several useful properties, which can be exploited by developing of routing procedures. However, the presented work is not limited to ISL networks, but can be used also in other networks as described in (Liu et al., 2011; Long et al., 2010; Rao & Wang, 2010, 2011). Routing and traffic engineering functions are presented in modular manner for easier reuse of particular procedures.

Adaptation of routing requires, in addition to good understanding of the fundamental network operating conditions, also good knowledge of the characteristics of different types of traffic in the network. In order to support better modelling of traffic characteristics a modular methodology is described for developing a global aggregate traffic intensity model suitable for supporting the dimensioning and computer simulations of various procedures in the global networks. It is based on the integration of modules describing traffic characteristics on four different levels of modelling, i.e. geographical distribution of traffic sources and destinations, temporal variations of traffic sources' intensity, traffic flows patterns and statistical behaviour of aggregated traffic sources.
