Biological Approach to Autonomic Communication Systems

Among the most important research topics in computer sciences, a primary role is played by design and control of next-generation communication networks (NGCNs). Such networks will be characterized by heterogeneity at all levels, encompassing a large variety of users, media, processes and channels. Another important feature of NGCNs will be the ability to interact with the environment. Various agents will collect information from the surroundings, and, then take appropriate actions in response, either in a centralized or in a distributed fashion. These features will characterize a pervasive computing and communication environment, a challenging scenario for scientists in all comp-uter sciences-related research fields. Users will be highly mobile, and will need to access services without relying on a end-to-end connection. These factors will reflect into an increasing network management complexity, that will be approaching the limits of human capability. Consequently, necessary features of NGCNs will be the ability to self-manage, self-adapt and self-organize. These features may be summarized into one single paradigm: autonomic communication (AC). AC is an example where biological systems are considered as models of self-management and self-organization. This suggests that an appealing approach for governing the complexity of NGCNs is to draw inspiration from biology, as in autonomic computing, in order to achieve an efficient and robust communication system. This requires a multi-disciplinary approach to ICT-related research, which in our view can lead to innovative and creative solutions to the challenges related to next generation networks.