Context Adaptive Self-configuration System Based on Multi-agent

Abstract

This paper proposes an adaptive resource self-management system that collects system resources, user information, and usage patterns as context information for utilization in self-configuration. This system will ease the system maintenance burden on users by automating a large portion of the configuration tasks such as; install, reconfiguration and update, while also decreasing cost and errors. Working from the gathered context information, this system allows users to select and install appropriate components for their system context. This also offers a more personalized configuration setting by using user’s existing application setting and usage pattern. To avoid a center server overload when transferring and managing related files, we employ Peerto- Peer method. A prototype was developed to evaluate the system with a comparison study using the conventional methods of manual configuration and MS-IBM systems was conducted to validate the proposed system in terms of functional capacity, install time, etc...

This work was supported by the Ubiquitous Autonomic Computing and Network Project, 21^stCentury Frontier R&D Program in Korea and the Brain Korea 21 Project in 2004. Dr. E. Lee is the corresponding author.