Bandwidth constraint models: a performance study

Paper presented at IEEE GLOBECOM 2006 - 2006 Global Telecommunications Conference. San Francisco, CA: pp. 4150664.Bandwidth constraint models have been a topic of intense discussions at the IETF meetings. Three conventional methods have been described in informational IETF RFCs and their performance on a single link has been analyzed and discussed in the literature. In this article, we take a further step into analyzing their performance and optimal bandwidth constraint setting for a real network scenario. A new model is proposed and compared to existing ones when failure events may cause preemption of traffic trunks in a network. Our simulations results provide great insight on the benefits of the methods

Queueing models for capacity changes in cellular networks

With the rapid development of cellular communication techniques, many recent studies have focused on improving the quality of service (QoS) in cellular networks. One characteristic of the systems in cellular networks, which can have direct impact on the system QoS, is the fluctuation of the system capacity. In this thesis, the QoS of systems with capacity fluctuations is studied from two perspectives: (1) priority queueing systems with preemption, and (2) the M/M/~C/~C system. In the first part, we propose two models with controlled preemption and analyze their performance in the context of a single reference cell that supports two kinds of traffic (new calls and handoff calls). The formulae for calculating the performance measures of interest (i.e., handoff call blocking probability, new call blocking and dropping probabilities) are developed, and the procedures for solving optimization problems for the optimal number of channels required for each proposed model are established. The proposed controlled preemption models are then compared to existing non-preemption and full preemption models from the following three perspectives: (i) channel utilization, (ii) low priority call (i.e., new calls) performance, and (iii) flexibility to meet various constraints. The results showed that the proposed controlled preemption models are the best models overall. In the second part, the loss system with stochastic capacity, denoted by M/M/~C/~C, is analyzed using the Markov regenerative process (MRGP) method. Three different distributions of capacity interchange times (exponential, gamma, and Pareto) and three different capacity variation patterns (skip-free, distance-based, and uniform-based) are considered. Analytic expressions are derived to calculate call blocking and dropping probabilities and are verified by call level simulations. Finally, numerical examples are provided to determine the impact of different distributions of capacity interchange times and different capacity variation patterns on system performance