Waste Electric Appliance Recycling Information System Based on Cloud Computing Technology and Assurance of Continuous Service When a Single Point of Failure Occurs

碩士 === 國立宜蘭大學 === 多媒體網路通訊數位學習碩士在職專班 === 102 === How to ensure business continuity is an important issue for each organization's core information system. Once the core information system suffered a serious disaster, it leads to difficulties in the business operations of the organization. In an a...

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Bibliographic Details
Main Authors: Hsu, Peng-Chao, 徐鵬超
Other Authors: Huang, Chao-Hsi
Format: Others
Language:zh-TW
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/09405437724873383967
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Summary:碩士 === 國立宜蘭大學 === 多媒體網路通訊數位學習碩士在職專班 === 102 === How to ensure business continuity is an important issue for each organization's core information system. Once the core information system suffered a serious disaster, it leads to difficulties in the business operations of the organization. In an attempt to ensure that the organization's core information systems would continue operating in the face of disaster, organizations are always required to enhance software and hardware to build a high-availability system which is considered effective to prevent the loss of critical data caused by single point of failure. However, the corresponding software and hardware investment to create a high-availability system is considerable. Cloud Computing is the most popular issue in the technology industry and has been widely researched and applied in recent years due to its characteristics including high computing ability, high fault tolerance, high load and high scalability. Through these characteristics of cloud computing, limited hardware resources can be fully utilized thereby creating high-availability information system. In this paper, it aims to establish waste electric appliance recycling information system which is based on Apache open-source Hadoop and HBase cluster distributed cloud computing architecture technology, combined with Apache open-source Tomcat web server. In this study, it is conducted to examine whether the operation of the system remains persistent by installing the virtual machine software and simulating a single point of failure occurred in our Hadoop distributed computing clusters environment. The data processing performance tests confirm that up to 100,000 records can be processed before a single point of failure occurs. The experimental study of this thesis proves that organizations can take advantage of low-cost equipment to run the cluster system that ensures the system would still continue providing services when a single point of failure occurs.