Multi-Agent Approach to Modeling and Implementing Fault-Tolerance in Reactive Autonomic Systems

Recently, autonomic computing has been proposed as a promising solution for software complexity in IT industry. As an autonomic approach, the Reactive Autonomic Systems Framework (RASF) proposes a formal modeling based on mathematical category theory, which addresses the self-* properties of reactive autonomic systems in a more abstract level. This thesis is about the specification and implementation of the reactive autonomic systems (RAS) through multi-agent approach by laying emphasis on the fault-tolerance property of RAS. Furthermore, this thesis proposes a model-driven approach to transform the RAS model to agent templates in multi-agent model using Extensible Stylesheet Language Transformation (XSLT). The multi-agent approach in this research is implemented by Jadex, a high-level Java-based agent programming language. The intelligent agents are created in Jadex based on the Belief-Desire-Intension (BDI) agent architecture. The approach is illustrated on a case study

A decentralized agent framework for dynamic composition and coordination for autonomic applications

This paper introduces a peer-to-peer agent framework for supporting autonomic applications in decentralized distributed environments. The framework provides agents to discover, compose, and control elements. It defines agent interaction and negotiation protocols to enable appropriate application behaviors to be dynamically negotiated and enacted. The defined protocols and agent activities are supported by a scalable decentralized shared-space based substrate. The implementation and experimental evaluation of the system are also presented.