An autonomic system is composed of ensembles of heterogeneous autonomic components in which large sets of components are dynamically added and removed. Nodes within such an ensemble should cooperate to achieve system or human goals, and systems are expected to self-adapt with little or no human-interaction. Designing such systems poses significant challenges. In this paper we propose that the system engineer might gain significant inspiration by looking to the biological immune system, particularly by adopting a perspective on the immune system proposed by Cohen known as the Cognitive Immune Network. The goal of this paper is to show how the current literature in autonomic computing could be positively enriched by considering alternative design processes based on cognitive immune networks. After sketching out the mapping in commonalities between the Cognitive Immune Network and the autonomic computing reference model, we demonstrate how these considerations regarding the design process can be exploited with an engineered autonomic system by describing experiments with a simple robotic swarm scenario.
Designing Self-Aware Adaptive Systems: from Autonomic Computing to Cognitive Immune Networks / Capodieci, Nicola; E., Hart; Cabri, Giacomo. - STAMPA. - (2013), pp. 59-64. (Intervento presentato al convegno 7th IEEE International Conference on Self-Adaptation and Self-Organizing Systems Workshops, SASOW 2013 tenutosi a Philadelphia, USA nel September, 13, 2013) [10.1109/SASOW.2013.17].