Collaboratively Learning Network Management System Using Mobile Agent

• Main Authors: Chia-Jung Hsu, 許嘉容
• Other Authors: Chyan-Goei Chung
• Format: Others
• Language: zh-TW
• Published: 2001
• Online Access: http://ndltd.ncl.edu.tw/handle/88438279714401853176

碩士 === 國立交通大學 === 資訊工程系 === 89 === The main functionality of Network Management System (NMS) is to help network managers monitor and control the whole network for providing fast and efficient services to ensure the quality of information communication. From the perspective of network managers, we propose following four metrics to evaluate the performance of a NMS: Automation, Real-Time, Robustness and Management System Complexity. ‘Automation’ means the percentage of a NMS that can deal with the network-related tasks automatically without intervention from managers. ‘Real-Time’ means NMS can handle the tasks as soon as possible, especially for fault correction. ‘Robustness’ means any component crashes in the network, NMS can still work as usual. ‘Management System Complexity’ means the quantity of management system resource consumed by each node in NMS. Although the fast development of network has pushed NMS to evolve from centralized paradigm to hierarchy paradigm, it’s still with high system complexity and lack of real-time and robustness. Therefore, the most mature software agent, mobile agent, was proposed for NMS. Most researches think that mobile agents can promote the efficiency of management. But researches so far put the emphasis on the mobility and omit the other characteristics of mobile agents, such as automation, learning skill and cooperation. So the efficiency of using mobile agent in NMS is not so good as expectation. To improve the ‘Automation’ capability of NMS, mobile agents should learn and share knowledge automatically to enrich their own knowledge repository. To improve the ‘Real-Time’ capability of NMS, mobile agents should help each other to balance the workload and correlate the complex fault alarms by cooperation. To improve the ‘Robustness’ capability of NMS, there should be a backup mechanism with each important node in the system. To improve the ‘Management System Complexity’ capability of NMS, the knowledge repository should be simplified and distributed among all nodes. Based on these capability requirements, a collaboratively learning NMS is proposed that all the mobile agents in this system can learn experience mutually by help each other. The system architecture, detail design of the configuration/fault management-related modules and the principles of distribution and building of management knowledge of the NMS are described in this thesis.