A task-based architecture for autonomic body sensor networks

This paper proposes an architecture conceived for supporting rapid design and implementation of Wireless Body Sensor Network (WBSN) applications having autonomic characteristics. WBSNs represent the most suitable systems for monitoring and controlling physical and biochemical parameters on the human body, and thus supporting high-impact applications in a variety of human-centered domains The effectiveness of WBSN applications is a critical issue since their correctness and efficiency have to be assured not only at design/implementation time but notably at execution time. The autonomic computing paradigm can perfectly meet the critical requirements of WBSN applications such as fault tolerance, adaptability, and reliability, due to its fundamental self-* properties. In particular, our solution is based on the SPINE2 framework and its important distinctive feature is an architecture for guaranteeing the separation of concerns between the user-defined application logic and the autonomic-related operations. Our proposal is finally exemplified through a case study concerning the development of an autonomic application for human activity monitoring.