Catálogo de publicaciones - libros

This paper present an analytical model for the DCF function in 802.11 Mesh Networks where nodes are not all able to hear each other. The aim is to obtain insight into behavior rather than numerical accuracy. The model is quite general and accounts for the fundamental parameters that affect performance, namely network and flow topologies, channel reservation, exponential backoff and hidden nodes. Performances of the most elementary mesh networks (linear, tree, star,...) are analysed using this model. NS simulations are also provided to compare with the analytic results.

This paper presents a self-tuning optimal PI (Proportional-Integral) rate controller for end-to-end congestion in the IP-based Internet. We employ LQR (Linear Quadratic Regulator) approach from modern control theory in the optimal controller design that would allow the user to achieve good transient performance of IP networks by selecting proper positive definite matrices Q and R. Self-tuning PI rate controller self-tunes only when the changes in network traffic have drifted the network monitoring parameter outside its specified interval. The PI rate controller is located in each router and can calculate a desirable advertised source window size (i.e. source sending rate) based on the instantaneous queue length of the buffer. Our OPNET simulations demonstrate that our network traffic control algorithm can provide the network with a good transient behavior in AQM and flow throughput.

Multi-service mesh networks allow existence of guaranteed delay Quality-of-Service (QoS) traffic streams such as Voice over IP and best effort QoS traffic streams such as file transfer. We present an optimization that performs a linear search for the minimum number of TDMA slots required to support the guaranteed QoS flows. At each stage of the search a linear integer program is solved to find if there is a feasible schedule supporting the required end-to-end bandwidth and delay. Our optimization results in a relative order of transmissions in the frame that guarantees a maximum end-to-end delay in the network. The ordering of the transmissions can be used later to find feasible schedules with the Bellman-Ford algorithm on the conflict graph for the network. We use the optimization in numerical simulations showing the efficiency of 802.16 mesh networks with VoIP traffic.

In IP QoS () networks, classes of service for different kinds of data traffic have been proposed, analyzed and currently implemented. On the contrary, signaling traffic has been mostly considered as negligible. However in the last time, it has become more critical due to the necessity of controlling setup latencies. As a consequence, a new class of service () dedicated to carry the user signaling traffic was proposed by IETF. This paper deeps into the signaling CoS and proposes a model for its provisioning. It also considers the impact of timers (for reliable data transfer) on the network load and the setup latencies. It concludes aspects about the transport protocols used for the signaling class of service.

In this paper, we present a comprehensive algorithmic framework for discrete-time flow-level simulation of data networks. We first provide a simple algorithm based upon iterative equations useful for the simulation of networks with static traffic demands, and we show how to determine packet loss and throughput rates using a simple example network. We then extend these basic equations to a simulation method capable of handling queue and link delays in dynamic traffic scenarios and compare results from flow-level simulation to those obtained by packet-level simulation. Finally, we illustrate the tradeoff between computational complexity and simulation accuracy which is controlled by the duration of a single iteration interval .

The paper proposes a new method to calculate the occupancy distribution and the blocking probability in the full-availability group with multi-rate traffic and bandwidth reservation. In the presented method, the occupancy distribution in a group is calculated with the application of the proposed asymmetric convolution operation that takes into consideration the influence of the reservation mechanism upon the probability of passing between the states. The results of the analytical calculations of the blocking probability in the system with bandwidth reservation obtained on the basis of the proposed analytical method are compared to the data obtained on the basis of other known analytical methods and to the results of the simulation.

We consider a single circuit-switched communication link, depicted by a Erlang multi-class loss queue, where a customer may vary its required bandwidth during its service. We obtain approximately the steady-state blocking probability of each class of customer. Comparisons with simulation results show that the approximation solution has a good accuracy. For the proposed model, we also provide an efficient capacity provisioning algorithm.

This paper presents an approximation method — Multiservice Overflow Approximation (MOA), to compute traffic loss in multi-tier hierarchical networks with multiservice overflows. With the MOA method, we first obtain the variances of multiservice non-Poisson overflows in each tier by a blocking probability matching approach, and then compute the call blocking probability of multiservice overflow traffic by a modified Fredericks & Hayward’s approximation. The results obtained by the MOA method are verified by simulations. Compared with an existing approximation method based on multi-dimensional Markov-Modulated Poisson Process analysis, the MOA method achieves an accurate estimation of overflow traffic loss at a much lower computational cost, particularly for high-load multi-tier hierarchical networks

In this paper we use a multivariate Markov Modulated Fluid Flow model to study the loss process for a bufferless transmission link. We propose a method for the analysis of moments and correlations of congestion periods and cumulative amount of lost bits and lost packets from different sources. Such knowledge is useful for the encoding of voice and video. Then we demonstrate how the proposed method can be used for the analysis of capacity sharing policies.

We propose a novel adaptive reservation scheme that handles, in an integrated way, streaming and elastic traffic. The scheme continuously adjusts the quality of service perceived by users, adapting to any mix of traffic and enforcing a differentiated treatment among services, both in fixed and variable capacity systems. The performance evaluation carried out verifies that the QoS objective is met with an excellent precision and that it converges rapidly to new operating conditions. Other key features of our scheme are its simplicity and its oscillation-free behavior.