Search

Multiservice networks are discussed. Reliability of access network topologies is investigated with the aim of ensuring a level of quality of service (QoS) at the lowest cost to end users.

One of the main characteristics of telelearning is the spatial and temporal distance between the instructors and their learners. The latter - many of which are adults are subject to […]

This paper presents a machine learning approach to the topological optimization of computer networks. Traditionally formulated as an integer program, this problem is well known to be a very difficult one, only solvable by means of heuristic methods. This paper addresses the specific problem of inferring new design rules that can reduce the cost of the network, or reduce the message delay below some acceptable threshold. More specifically, it extends a recent approach using a rule-based system in order to prevent the risk of combinatorial explosion and to reduce the search space of feasible network topologies. This extension essentially implements an efficient inductive learning algorithm leading to the refinement of existing rules and to the discovery of new rules from examples, defined as network topologies satisfying a given reliability constraint. The contribution of this paper is the integration of learning capabilities into topological optimization of computer networks. Computational results confirm the efficiency of the discovered rules. Index Terms - Computer networks, inductive learning, intelligent system, knowledge acquisition, topological design.

The topological design of distributed packet switched networks consists of finding a topology that minimizes the communication costs by taking into account a certain number of constraints such as the delay and the reliability. This paper proposes a genetic algorithm (GA) for generating low-cost feasible computer network topologies subject to these constraints. The implementation of this algorithm has been subjected to extensive tests in order to measure the quality of solutions. Computational results confirm the efficiency of the GA to provide good solutions for medium-sized computer networks, in comparison with well-tried conventional methods. Index Terms - Computer networks, distributed systems, genetic algorithms, heuristic method, topological design.

A tabu-search method is presented that solves topological design problems associated with packet switched networks which integrate unreliable components. The performance of the method depends on several factors such as the choice of the neighborhood structure, length of the tabu list and parameters that affect the quality of results. Compared with other heuristic methods, the tabu-search approach may provide a major contribution for solving topological design problems related to packet switched networks.