SymbioticSphere: A Biologically-Inspired Autonomic Architecture for Self-Managing Network Systems

The proposed architecture, called SymbioticSphere, consists of two major system components: application service and middleware platform. Each of them is modeled as a biological entity, analogous to an individual bee in a bee colony. They are designed to follow several biological principles such as decentralization, autonomy, emergence, redundancy, natural selection and symbiosis. An application service is implemented as an autonomous software agent. Each agent implements a functional service and follows biological behaviors such as migration, replication, death, energy exchange and environment sensing. A middleware platform runs on a network host and operates agents. Each platform provides a set of runtime services that agents use to perform their services and behaviors, and implements biological behaviors such as replication, death, energy exchange and environment sensing. The objectives of this study are to design and implement SymbioticSphere and evaluate the biologically-inspired mechanisms in SymbioticSphere in terms of autonomy, scalability, adaptability and survivability. Simulation results show that agents and platforms autonomously scale to network size and demand volume and adapt to dynamic changes in the network conditions (e.g., user locations, network traffic and resource availability). They also autonomously survive partial system failures such as host failures and link failures in order to retain their availability and performance