To date, many autonomic computing and/or networking architectures and frameworks have been proposed in the literature. Rather than present their architectural details, we focus on the promising theories that aid in the design of self-managing networks.
Design patterns offer an effective method of capturing human knowledge in how to cope with specific problems from an architectural standpoint. Applying appropriate design patterns in self-managing networks not only results in intelligent organization of autonomic components at runtime, but also provides a concrete guideline to component interactions. More importantly, autonomic systems developed using design patterns are guaranteed to yield desirable system output and correct system states. In a broad sense, design patterns could be general design practices, such as the patterns proposed in :
Goal-driven self-assembly: this pattern is useful for self-configuration. System configuration decisions are made a priori and are assigned to the system components as goals. When the component joins an autonomic system, it knows how to contact a service registry to obtain resources and services based on its goal description.
Self-regenerating cluster: two or more instances of a particular type of autonomic component are tied together in a cluster. They share the same input element and process external requests assigned by some scheduling algorithm. Instances in a cluster ...