Research On Degeneracy In Wireless Communication Networks

As the complexity of the Global Internet and other attached and overlay networks increases, the ability for humans to understand, configure, and manage these networks is becoming increasingly difficult and expensive. In recent years, people have turned to nature for the solution to these problems. Methods learnt from ant colonies and swarms of bees are used to accomplish cooperative tasks in computer networking. Basic biological processes such as diffusion, replication, chemotaxis and stigmergy are used to build large scale computer networks with desirable properties including adaptivity and robustness [1,2]. Artificial immune system, genetic algorithms and cellular and molecular based methods are some other well known examples of bio-inspired mechanisms to build adaptive and autonomous communication networks [3-5].In this paper, we introduce another biological term, degeneracy, into network engineering and explore how degeneracy can be used to improve network performance in terms of connectivity and robustness.Degeneracy is defined as the ability of elements that are structurally different to perform the same function or yield the same output depending on the context in which they are expressed [6,7]. It is a prominent property of many biological systems ranging from genes to neural networks to evolution itself. Even in biological system, it is just in the beginning of this century that degeneracy was proposed and acknowledged as the fundamental property to achieve highly improved robustness. Considering the great importance of robustness in wireless communication, degeneracy will be the key technology to build the next generation wireless networks. In this paper, we first give the formal definition of degeneracy and then classify the network into two categories, infrastructure-based networks and ad-hoc networks. In these two different network models, we make some abstraction of network nodes and define their degenerate behaviours. Based on the information theory proposed by Tononi, we calculate each node's value of degeneracy, examine its relation with some network parameters and finally discovery the potential of degeneracy to enhance network performance.