Fundamentals of Decentralized Optimization in Autonomic Systems

An autonomic system is a complex information system comprised of many interconnected components operating at different time scales in a largely independent fashion that manage themselves to satisfy high-level system management requirements and specifications [5]. This includes providing the self∗ properties of self-configuring, self-repairing, self-organizing and self-protecting. A fundamental problem for achieving the goals of selfmanagement concerns the general optimization framework that provides the underlying foundation and supports the design, architecture and algorithms employed throughout the system. Given the increasing complexity of current and future information systems, a decentralized approach is a natural way to design and implement autonomic systems that provide self∗ properties. On the other hand, a centralized approach with complete knowledge over all constituent system components has the potential to provide significant improvements over a decentralized approach, in the same way that solutions to global optimization problems (if attainable) are often superior to the corresponding locally optimal solutions. This fundamental problem involving the tradeoff between centralized and decentralized approaches arises in a wide range of applications, and its solution is especially important to achieve the goals of self-management in autonomic systems.