Endogenous versus exogenous self-management

Self-management is considered as one of the crucial means for software systems to deal with changing demands at runtime. Self-management endows a software systems with the ability to adapt its structure or behavior without human intervention. Two different approaches are put forward for self-management: (1) the system components adapt their structure or behavior to changing requirements and cooperatively realize system adaptation - this approach can be considered as endogenous self-management; (2) the system is adapted through a control loop, i.e. the system is monitored to maintain an explicit representation of the system and based on a set of high-level objectives, the system structure or its behavior is adapted - this approach can be considered as exogenous self-management. In this paper, we introduce a hybrid software architecture that combines both approaches. A multi-agent system architecture allows agents to flexibly adapt their behavior to changes in their context providing cooperative system adaptation. Then, we extend the multi-agent system architecture with a decentralized control loop adding self-healing properties to the system. We use intelligent monitoring of traffic jams as an illustrative case.