Resource Dimensioning in WDM Networks under State-Based Routing Schemes

Network dimensioning for wavelength-routed WDM networks has been extensively studied to maximize connection acceptance rate while minimizing the total cost. However, Internet services are increasingly generating more demands that have high-bandwidth requirements with relatively short holding times. As globalization of companies or organizations becomes a new trend, the variety of Internet service demands, in space and time, creates a more variable and unpredictable traffic model for long term network provisioning. At the same time, upgrading backbone networks remains expensive and infrequent. It is important to be able to efficiently utilize precious network resources so that low call blocking is achieved while requiring fewer upgrades when the traffic model changes. There are two kinds of dimensioning problems. First, basic dimensioning allocates network resources for a newly built network. Second, incremental dimensioning allocates extra resources for an already built network without affecting currently available resources. Historically, routing and dimensioning problems are studied together as an optimization problem. However, as integrating multiple network layers into one control platform becomes a common trend, and as higher-layer traffic that currently utilize dynamic routing imposed on logical layers increases, it is essential to plan the underlying network based on dynamic routing schemes, such as open shortest path routing (SPF). In this paper, we study basic and incremental dimensioning for dynamic routed traffic. We propose a simulation based basic dimensioning approach and introduce two new incremental dimensioning techniques: MEAN and SD. We also introduce an evolutionary traffic model and traffic load computation criteria. Simulation results show that basic dimensioning effectively reduces the topological bottlenecks, rendering 7% less blocking compared to uniform allocation. With the evolutionary traffic model, SD incremental dimensioning shows advantages over the MEAN method on most practical networks. We also compare our results with fixed routing and dimensioning approaches, showing that dynamic approaches provide better network balance and utilization.