Luis Orozco-Barbosa

Use of a-stable self-similar stochastic processes for modeling traffic in broadband networks

Abstract In this article, we propose a new model for aggregate network traffic. This model, besides reflecting self-similarity and long-range dependence, is able to capture the appropriate level of burstiness of different types of traffic by selecting the proper parameters. Different types of self-similar traffic traces (LAN/WAN, WWW, VBR video) are analysed by estimating their self-similarity coefficient H, as well as the parameters of their marginal distributions. When comparing the real traces with our artificial traces, the agreement, which was evaluated both qualitatively (visually) and quantitatively (by means of the marginal CDF and the periodogram), is better than that achieved with previously proposed models. By analysing different types of traffic traces, the model is shown to be flexible enough to be applied to a variety of communications scenarios. A queue with our proposed traffic as input is analysed. A proof of convergence of aggregate traffic to α-stable processes is also included, as well as the conditions under which the Gaussian assumption is appropriate.

Some proposals to improve error resilience in the MPEG-2 video transmission over ATM networks

MPEG-2 video communications over ATM networks is one of the most active research areas in the field of computer communications. In this paper, we introduce a set of control mechanisms at different levels of the protocol architecture to be used in MPEG-2-based video communications systems using ATM networks as their underlying transmission mechanism. We argue that in order to be able to create video systems able to cope with some of the errors encountered in computer communications systems, a structured set of error-resilient protocol mechanisms is needed. Our results show the effectiveness of using a structured set of control mechanisms to overcome for the loss of cells carrying VBR MPEG-2 video streams.

Design and performance evaluation of intelligent multimedia services

Telecommunications networks are evolving globally to keep pace with rapid technological, regulatory and market changes. This is particularly evident in the introduction of intelligent network (IN) capabilities by network providers around the world. These IN capabilities will augment the network intelligence via the common channel signaling network and distributed service control points allowing users to gain access to advanced communications services. In this paper, we present the results of our research in the area of intelligent multimedia services. One of the main results has been the design of novel multimedia services operating over different network platforms. One of the new services being designed is an intelligent multimedia gateway, providing interconnectivity between the public service telephone network and the Internet. The design of this service has proved useful in gaining insight into the way novel intelligent multimedia services across network platforms will benefit from the use of IN technology. A performance evaluation of the service has also proved valuable to identify the major system and traffic parameters to consider when designing and deploying IN multimedia services across multiple networks.

A spread slotted random access protocol with multi-priority for personal and mobile communication networks carrying integrated traffic

This paper describes and analyzes a medium access protocol for wireless personal communication networks serving integrated traffic. A multi‐priority mechanism, which is implemented and controlled explicitly by the users and without any involvement from the network is incorporated into the protocol. We examine the proposed protocol under reservation and non‐reservation policies and evaluate its performance when handling integrated voice and data traffic. The proposed protocol is suitable to be used in Personal Communication Systems aiming to provide integrated (voice/data) services.

Fast simulation of broadband telecommunications networks carrying long-range dependent bursty traffic

A technique for the fast simulation of broadband communications systems is proposed, which is based on regenerative importance sampling techniques. Our algorithm is applicable to estimating the probability of rare events when modeling the offered traffic using fractional stable noise (FSN) processes (including fractional Brownian noise as a particular case), which have been proved to be able to capture both the long-range dependence and the burstiness of todays aggregate network traffic. An exact description of FSN processes is given, as well as an approximation that allows for the application of importance sampling techniques. The results obtained for a simple example are also included.

Use of alpha-stable self-similar stochastic processes for modeling traffic in broadband networks

A novel model for simulating aggregate network traffic is proposed. Our model, besides reflecting self-similarity and long-range dependence, it is able to capture the appropriate level of burstiness of different types of traffic by selecting the proper parameters. Different types of self- similar traffic traces are analyzed by estimating their self-similarity coefficient H, as well as the parameters of their marginal distributions. When comparing the real traces with our artificial traces, the agreement, which was evaluated both qualitatively and quantitatively, is better than the achieved with previously proposed models. By analyzing different types of traffic traces, the model is shown to be flexible enough to be applied to simulate a variety of communications scenarios. A queue with our proposed traffic as input is analyzed. A proof of convergence of aggregate traffic to alpha-stable processes is also included, as well as the conditions under which the Gaussian assumption is appropriate.

Probabilistic envelope processes for α-stable self-similar traffic models and their application to resource provisioning

Recent experimental studies have shown that @a-stable self-similar stochastic processes can accurately characterize various types of aggregate network traffic. Using this traffic modeling approach, we propose some probabilistic envelope processes that can be used to represent the resource demand of a traffic stream in performance evaluation studies. We illustrate the use of the proposed envelopes in resource allocation for data and video traffic and in the design of an admission control mechanism. From our analysis we conclude that the presence of heavy tails in the distribution of a traffic process has a severe impact on the dimensioning of network elements.

On the dynamic allocation of resources using linear prediction of aggregate network traffic

Recent works propose the use of fractional stable noise (FSN) to capture the statistical properties of an arrival process over time intervals. This process can reproduce the properties of long-range dependence and high variability exhibited by traffic in real-life networks. However, when modeling network traffic with this @a-stable long-range dependent stochastic process, some analytical difficulties arise. For instance, the value of its index of stability @a conditions the existence of some moments, which in turn limits the applicability of traditional statistical procedures. Therefore, alternative procedures and methods have to be used. In this work we claim that in spite of the increased complexity, there is much to gain by considering this modeling approach in the context of traffic control. We focus our attention in the prediction of FSN processes and we argue that it can potentially help improving currently existing resource management mechanisms. We support this claim by introducing the Dynamic Predictive Weighted Fair Queueing; a novel algorithm for the dynamic allocation of resources. Our simulation results and consequent performance comparisons with other schemes suggest that the performance of some scheduling algorithms can be highly improved in terms of packet losses and delays by incorporating prediction techniques that take into account the relevant properties of the network traffic.

Performance analysis of wireless ATM/AAL2 over a burst error channel

Recent growth in cellular networks has motivated research on broadband access technologies for the support of diverse services over wireless networks. Wireless asynchronous transfer mode (WATM) has been proposed as a transport solution for next generation wireless and personal communication networks and ATM adaptation layer 2 (AAL2) has been identified suitable for the support of low data rate and delay sensitive voice traffic generated in cellular networks. In this paper, we study the performance of AAL2 over a burst error wireless channel. Analytical expressions for performance measures of interest are derived for the Gilbert-Elliott channel and numerical results are presented to demonstrate the effect of burst errors on the AAL2 frame structure and the AAL2 performance.

Improving fairness of long VCs with dynamic weights in the ATM ABR service

The fair distribution of bandwidth to different connections is an important issue in high-speed networks. This is especially true in low-priority services where the bandwidth available for the low priority connections may be small and may vary rapidly. An example is the Available Bit Rate (ABR) service in Asynchronous Transfer Mode networks. This study uses the ABR service to explore a scheme that achieves better fairness in bandwidth allocations. Traditional schemes fail to achieve desired bandwidth allocations, which are generally based on connection weights. In this paper, a new scheme called Active Fairness is proposed which substantially improves fairness in bandwidth allocations. Contrary to one set of weights used in traditional schemes, Active Fairness maintains two sets of weights at each link.