An Application of Fuzzy Controllers: Autonomic Computing Systems

The difficulty of managing today’s computing systems goes well beyond the administration of individual software environments. The need to integrate several heterogeneous environments into corporate-wide computing systems, and to extend that beyond company boundaries into the Internet, introduces new levels of complexity. Relying solely on further innovations in programming methods will not get us through the present complexity crisis. The only option remaining is Autonomic Computing – computing systems that can manage themselves given high level objectives from administrators. An autonomic system has four major characteristics: self-configure, self-heal, self-optimize and self-protect (Salehie & Tahvildari, 2005). Self-configuring is the capability of adapting automatically and dynamically to environmental changes. This characteristic has two aspects 1. installing, (re-)configuring and integrating large, complex network intensive systems 2. adaptability in architecture or component level to re-configure the system for achieving the desired quality factors. Self-healing is the capability of discovery, diagnosing and reacting to disruptions. Such a system must be able to recover by detecting a failed component, taking it off-line to be fixed, and replacing the fixed component into the system without any apparent disruption. Self-optimizing is the capability to efficiently maximize resource allocation and utilization for satisfying requirements of different users. While, in a short term, self-optimizing can address the complexity of managing system performance, in a long run its components will automatically and proactively seek ways to tune their operations and make themselves more cost efficient. Self-protecting is the capability of reliably establishing trust, and anticipating, detecting and recovering from the effects of attacks with two aspects 1. defending the system against correlated problems arising from malicious attacks or cascading failures that remain uncorrected by self-healing measures 2. anticipating problems based on early reports from sensors and taking steps to avoid or mitigate them. The autonomic computing architecture (explained later) provides a blue print for developing feedback control loops for self-managing systems. This observation suggests