Athanasios V. Vasilakos

The use of learning algorithms in ATM networks call admission control problem: a methodology

Abstract Call Admission Control (CAC) is one of the most fundamental preventive congestion control mechanisms in Asynchronous Transfer Mode (ATM) networks. Several mathematical approaches that have been proposed in the literature, which usually estimate the equivalent bandwidth that is required, achieve conservative approximations that result in reduced statistical gain and thus, in under-utilisation of the network resources. In this study, a new methodology is proposed which uses a Learning Automaton (LA) in combination with equivalent bandwidth approximations to reduce the percentage of overestimation. The learning algorithm that is used attempts to predict in real-time if a call-request should be accepted or not receiving as feedback a function of an estimate of the equivalent bandwidth. As will be shown, the proposed mechanism, whose hardware implementation is feasible, exhibits remarkable statistical gain compared with some classical CAC schemes of the literature and distinct improvement of the equivalent bandwidth approximations. Finally, some issues for extending this work are also discussed.

Research: On the use of a stochastic estimator learning algorithm to the ATM routing problem: a methodology

This paper presents a dynamic solution to the Routing problem in (ATM) networks suitable for real-time applications. The proposed methodology employs a Stochastic Estimator Learning Algorithm (SELA) specially designed for the Routing problem. The feedback of the SELA Routing algorithm is computed from the utilisation of the links that comprise a route which is a possible solution to a specific Routing problem. The algorithm promotes the load balancing in light loading conditions, whereas as the load of the network increases it tends to behave as a shortest path algorithm trying to minimise the cell loss probability and the call dropping rate. Simulation results show the effectiveness of the proposed scheme in comparison with some of the most known Routing algorithms of the literature. Some interesting directions for future work are also discussed.

Modularization of fuzzy relational equations

Abstract In this study, we are concerned with a modularization of fuzzy relational equations that is converting a highly dimensional (multivariable) relational equation into a series of single input fuzzy relational equations. The problem originates from a need of handling (estimating) highly dimensional relational structures and is inherently associated with the curse of dimensionality present in relational fuzzy models. We propose a two-layer architecture and discuss a detailed optimization scheme leading to the determination of the fuzzy relations occurring there. Illustrative numerical studies are also included.

Information granulation for concept formation

In this study, we elaborate on the important issue of membership function determination. The main point is that any estimation procedure should reconcile the semantics of a fuzzy set (regarded as an information granule of some level of abstraction) with the experimental evidence conveyed by numeric data. This, in the sequel, calls for the development of the hybrid two-phase approach that starts from a rough specification of the support of the fuzzy sets that is followed by detailed computations involving a specific type of membership function and an estimation of its parameters. The role of robust statistics in this setting is also raised. Finally, experimental results are presented.

Computational intelligence in management of ATM networks: a survey of the current state of research

Designing effective control strategies for Asynchronous Transfer Mode (ATM) networks is known to be difficult because of the complexity of the structure of networks, nature of the services supported, and variety of dynamic parameters involved. Additionally, the uncertainties involved identification of the network parameters cause analytical modeling of ATM networks to be almost impossible. This renders the application of classical control system design methods (which rely on the availability of these models) to the problem even harder. Consequently, a number of researchers are looking at alternative non-analytical control system design and modeling techniques that have the ability to cope with these difficulties to devise effective, robust ATM network management schemes. Those schemes employ artificial neural networks, fuzzy systems and design methods based on evolutionary computation. In this survey, the current state of ATM network management research employing these techniques as reported in the technical literature is summarized. The salient features of the methods employed are reviewed.

Application of computational intelligence techniques in active networks

Computational intelligence techniques have been successfully applied for solving control problems in modern networking architectures such as ATM and the Internet. The introduction of active networks offers a high level of flexibility in customizing the network infrastructure and introducing new functionality. There is a clear need for revisiting both the applicability of computational intelligence techniques in this new networking environment, as well as the provisions of active networking technology that computational intelligence techniques can exploit for improved operation. We elaborate on the characteristics of these technologies, their synergy and report on our study with applying computational intelligence techniques for improved routing on a novel active network resource management architecture.

A roadmap of fuzzy logic in ATM, mobile and active networks: challenges of the new century

Abstract ATM networking technology was conceived 20 years ago, and installations will reach their peak the next 10 years. Active networks will be the technology which will follow the ATM. In this article, we address the most important issues regarding recent advances and future perspectives in ATM, including IP/ATM integration, Active Networks, MobileActive Networks and the impact of fuzzy technology in solving the important problems of the above future networking technologies. In the new century it is imperative that we shift from a technology to an application (needs of consumers) focus, where ubiquitous and invisible (context-aware) computing will be a reality.

Book Review: Intelligent Information Agents

In this book the author tries to cover a wide thematic range of intelligent information agents. The papers of the book are put in four parts. The ®rst part provides an introduction to non-cooperative or cooperative information agents, depending on their ability to cooperate with each other for the execution of their tasks. The second part presents rational information agents which are utilitarian for automated trading and electronic commerce in the internet. The third part introduces adaptive information agents that adapt themselves to changes in networks and information environments. The ®nal part describes mobile information agents that travel autonomously through the internet enabling network management and security. Agent technology is drawing a lot of attention from both academia and industry. The information agents paradigm is a promising technology to integrate the network of computers to meet the need of new services and easier access applications. The book is a quality contribution to the ®eld of intelligent information agents. The good breadth of topics allows the reader to keep particular technologies in perspective. I recommend it to researchers, professionals, lecturers and interested students. A.V. Vasilakos Institute of Computer Science, Foundation for Research and TechnologyÐHellas, P.O. Box 1385, Heraklion, Crete, Greece Computer Communications 23 (2000) 1790 www.elsevier.com/locate/comcom

Intelligent Information Agents: M. Klusch; Springer, Berlin, ISBN 3-540-65112-8

In this book the author tries to cover a wide thematic range of intelligent information agents. The papers of the book are put in four parts. The ®rst part provides an introduction to non-cooperative or cooperative information agents, depending on their ability to cooperate with each other for the execution of their tasks. The second part presents rational information agents which are utilitarian for automated trading and electronic commerce in the internet. The third part introduces adaptive information agents that adapt themselves to changes in networks and information environments. The ®nal part describes mobile information agents that travel autonomously through the internet enabling network management and security. Agent technology is drawing a lot of attention from both academia and industry. The information agents paradigm is a promising technology to integrate the network of computers to meet the need of new services and easier access applications. The book is a quality contribution to the ®eld of intelligent information agents. The good breadth of topics allows the reader to keep particular technologies in perspective. I recommend it to researchers, professionals, lecturers and interested students. A.V. Vasilakos Institute of Computer Science, Foundation for Research and TechnologyÐHellas, P.O. Box 1385, Heraklion, Crete, Greece Computer Communications 23 (2000) 1790 www.elsevier.com/locate/comcom