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Network Self-Fault Management Based on Multi-Intelligent Agents and Windows Management Instrumentation (WMI) | ||
| Baghdad Science Journal | ||
| Article 1, Volume 14, Issue 4, 2017, Pages 823-831 | ||
| Authors | ||
| Hasanen S. Abdullah; Maha Abdulkareem Alrawi; Dalal N. Hammod | ||
| Abstract | ||
| This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to 92.19%, availability 92.375%, and reliability 100%. The proposed system managed five devices. The NSFM implemented using Java and C# languages. | ||
| Keywords | ||
| Network Self; Fault Management; Intelligent Agent; fault detection; Fault Identification; Fault Recovery | ||
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