Autonomic computing management for Unmanned Aerial Vehicles

Unmanned Aerial Vehicles (UAVs) are required to provide more and more effective operational resilience and efficient management of resources. This is in great part due to the increasingly-sophisticated autonomous capabilities to carry out more complex but also longer missions. However, most of the UAVs lack self-management to operate with effectiveness and efficiency in such missions. Autonomic Computing (AC) provides self-managing capabilities inspired by the physiological functionality of the autonomic nervous system. Homeostatic functions from such important system are essential for humans to survive. This paper introduces the AC concept to control architectures of UAVs to endow them with operational endurance. The above capabilities are essential to endure the operational persistence of UAVs in complex and long-term missions. This paper presents the self-managing aspects and a discussion on the design of this promising AC-based approach. It also introduces the biological foundations, the self-management philosophy, and challenges as to parallel computation for the AC realization in UAVs.