A Neural Network-Based Agent Framework for Mail Server Management

Amidst the era of e-economy, one of the difficulties from the standpoint of the information systems manager is, among others, the forecast of memory needs for the organization. In particular, the manager is often confronted with maintaining a certain threshold amount of memory for a prolonged period of time. However, this constraint requires more than technical and managerial resolutions, encompassing knowledge management for the group, eliciting tacit knowledge from the end users, and pattern and time series analyses of utilization for various applications. This paper proposes a framework for building an automated intelligent agent for memory management under the client-server architecture. The emphasis is on collecting the needs of the organization and acquiring the application usage patterns for each client involved in real time. Due to the dynamic nature of the tasks, incorporation of a neural network architecture with tacit knowledge base is suggested. Considerations for future work associated with technical matters comprising platform independence, portability, and modularity are discussed.