| Summary: | 碩士 === 靜宜大學 === 資訊應用與科技管理碩士在職專班 === 105 === According to Gartner’s prediction, the devices available on the Internet will reach over 840 million in 2017 and over 20.4 billion in 2020. Therefore, with the evolution of the vast Internet of Things era, a network manager who deals with network parts or devices that come one after another, must understand all network behavior and activities in order to manage effectively. For example, issues like reasonable management of network traffic and safe data delivery require a manager to spend a great deal of time analyzing and conducting tests.
For several years, service availability has complied with stringent standards along with enterprises’ use of virtualization to build a private cloud for resource integration and deployment. At the same time, the business operating system of enterprises in the manufacturing industry amid the industry 4.0 era (e.g. ERP, CRM, PLM, MES, etc.), the Internet of Things, intelligent building and so on, along with the combination of relevant services puts a manager under pressure and psychological stress when dealing with structural changes and expansion due to greater demand and burden in monitoring and managing. A manager begins to review and improve management activities and expect to further reduce workload through research and analysis, introduction of tools and problem solving using automatic processes.
In current network management, there is no system available since the network management system of the commercial procurement version has budget considerations. When irregularities occur, a manager can normally analyze possible spots quickly and check the network nodes one by one using only the information provided by the respondent. Besides the unpredictable time consumption, there is also an increase in service interruption time. Building a set of intelligent network management systems using Open Source software could help a manager identify the source of the problem through a warning function provided by the system, as well as reduce business procurement cost. Moreover, service interruption may be restored directly through an external integration of the system and automatic operations.
This study combines the Nagios system to develop a private cloud service for enterprises, conduct real-time monitoring of the Internet of Things, and build a backup equipment abnormality warning mechanism that can notify the manager if there is abnormality in the network core equipment or mail host, so as to reduce troubleshooting time. The automatic recovery mechanism of the host service abnormality is additionally created so that when abnormality occurs, service may be quickly restored to normal. This helps the manager to not only reduce troubleshooting tasks and the pressure of service management, but also ensure the availability of the business system and cut losses caused by abnormalities.
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