Nature-Inspired Informatics for Telecommunication Network Design

Abstract

The speedy pace of change in telecommunications and its ubiquitous presence have drastically altered the way people interact, impacting production, government, and social life. The infrastructure for providing telecommunication services must be continuously renewed, as innovative technologies emerge and drive changes by offering to bring new services to the end users. In this context, the problem of efficiently designing the underlying networks in order to satisfy different requirements while at the same time keeping the capital and operative expenditures bounded is of ever growing importance and actuality. Network design problems have many variations, depending on the characteristics of the technologies to be employed, as well as on the simplifying hypothesis that can be applied on each particular context, and on the planning horizon. Nevertheless, in most cases they are extremely complex problems, for which exact solutions can not be found in practice. Nature-inspired optimization techniques (belonging to the metaheuristic family of computational methods) are important tools in these cases, as their application allows obtaining good quality solutions in reasonable computational times. The objective of this work is to present a systematic review of the application of natureinspired techniques to solve optimization problems related to telecommunication network design. The review is aimed at providing an insight of different approaches in the area, in particular covering four main classes of applications: minimum spanning trees, reliable networks, local access network design and backbone location, and cellular and wireless network design. A large proportion of the papers deal with single objective models, but a growing number of works study multi-objective problems, where it is necessary to find solutions which perform well in a number of different criteria. While genetic algorithms and other evolutionary algorithms appear most frequently, there is also significant research on the application of other methods, such as ant colony optimization, particle swarm optimization, immune systems, and other nature-inspired agent-based techniques.