A technique for measuring the level of autonomicity of self-managing systems

Autonomic and self-managing systems are increasingly pervasive across an ever-widening spectrum of application domains. Autonomic technology is advancing at a high rate, yet there are no universal standards for the technology itself and the design methods used. There are also significant limitations to the way in which these systems are validated, with heavy reliance on traditional design-time techniques, despite the highly dynamic behaviour of these systems in dealing with run-time configuration changes and environmental and context changes. These limitations ultimately undermine the trustability of these systems and are barriers to eventual certification. This paper is concerned with setting the groundwork for the introduction of standards for Autonomic Computing (AC), in terms of technologies and the composition of functionality as well as validation methodologies. We propose that the first vital step in this chain is to introduce robust techniques by which the systems can be described in universal language, starting with a description of, and means to measure the extent of autonomicity exhibited by a particular system. We present a novel technique for measuring the Level of Autonomicity (LoA) along several dimensions of autonomic system self-CHOP (self-configuration, self-healing, self-optimisation and self-protection) functionalities