Summary of some traffic engineering studies carried out within RACE project R1044

Abstract

The paper summarizes some results obtained within RACE Project R10044 in the period 1988–1992. Traffic Engineering Studies have been carried out by R1044 with the objective and within the scope of supporting identification, selection and evaluation of network evolution strategies towards IBC; in particular, to establish which kind of traffic assumptions should be considered within Reference Demand Scenarios and how these traffic assumptions can be obtained. In its first part, the paper summarizes discussions on the main challenges to be faced by Traffic Engineering to contribute to the definition of evolution strategies towards IBC (to which requirements should Traffic Engineering respond?; which traffic considerations are required?; which “weight” they “should” have?; which problems should Traffic Engineering experts solve to allow strategic planning considerations?; more details, and discussion on other strategic planning challenges, can be found in the so called R1044 book, published by North Holland [1, 2, 3]). In particular the first part summarizes discussions on: the need of simple conservative engineering rules based upon ergodic approximations; their use to conceive a network architecture which can accommodate decoupling among Service and Network Evolutions; their role in establishing Reference Demand Scenarios, namely real differences in the “nature” of the demand requiring different strategical decisions. In the second part the paper provides information on the results obtained in order to solve some problems introduced in the first part; in particular this part introduces the conservative ergodic approximations developed to support an engineering of the first statistical multiplexer stage over time, robust against unexpected traffic evolutions. Finally, in the third part, the paper describes a simple computer tool developed (intentionally no more than an “electronic sheet”) and applied in RACE Project R1044 to produce simple reference demand scenarios.