A customizable multi-agent system for distributed data mining
Di Fatta, G. and Fortino, G. (2007) A customizable multi-agent system for distributed data mining. In: The 22nd ACM Symposium on Applied Computing (SAC 2007), March 11-15, 2007, Seoul, Korea, pp. 42-47.
To link to this article DOI: 10.1145/1244002.1244012
We present a general Multi-Agent System framework for distributed data mining based on a Peer-to-Peer model. Agent protocols are implemented through message-based asynchronous communication. The framework adopts a dynamic load balancing policy that is particularly suitable for irregular search algorithms. A modular design allows a separation of the general-purpose system protocols and software components from the specific data mining algorithm. The experimental evaluation has been carried out on a parallel frequent subgraph mining algorithm, which has shown good scalability performances.