A Framework for Self-Management of Hybrid Wireless Networks Using Autonomic Computing Principles

Abstract

The dramatic increase in the number of mobile subscribers has put a significant resource and service provisioning strain on current cellular networks in particular in terms of multimedia and high-data rate service provision. Hybrid wireless networks, which is a novel scalable and adaptive wireless network architecture utilizing a mixture of cellular and ad hoc multi-hop routing, facilitates cellular network design with small cell systems without having to wire a large number of base stations into a core network. However, this new network design has drawbacks in terms of routing complexity, radio resource heterogeneity and network infrastructure design growth. Traditional centralised system administration methods become too inflexible to result in a manageable cellular system. A recently introduced concept-autonomic computing, based on stimulation from biological systems, may provide a remedy to the state of unmanageability. The Autonomic computing paradigm, recently coined autonomic communications, when applied to communication systems and networks, enables self-management, which is composed of self-protecting, self-healing, self-configuring and self-optimizing components. This self-management is not necessarily novel as technologies such as neural networks, fuzzy logic, genetic algorithms and evolutional methods have already been proposed to facilitate limited self-configuration and self-optimization when embedded with cellular and ad hoc networks. However, a structure or framework has been lacking so far. In this paper we propose an architecture for a framework of autonomic computing based on policies for a hybrid wireless network and investigate the merits of each of its functions.