An Intrusive Analyzer for Hadoop Systems Based on Wireless Sensor Networks
Owing to the acceleration of IoT- (Internet of Things-) based wireless sensor networks, cloud-computing services using Big Data are rapidly growing. In order to manage and analyze Big Data efficiently, Hadoop frameworks have been used in a variety of fields. Hadoop processes Big Data as record value...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi - SAGE Publishing
2014-07-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2014/196040 |
| _version_ | 1797708951897243648 |
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| author | Byoung-Jin Bae Young-Joo Kim Young-Kuk Kim Ok-Kyoon Ha Yong-Kee Jun |
| author_facet | Byoung-Jin Bae Young-Joo Kim Young-Kuk Kim Ok-Kyoon Ha Yong-Kee Jun |
| author_sort | Byoung-Jin Bae |
| collection | DOAJ |
| description | Owing to the acceleration of IoT- (Internet of Things-) based wireless sensor networks, cloud-computing services using Big Data are rapidly growing. In order to manage and analyze Big Data efficiently, Hadoop frameworks have been used in a variety of fields. Hadoop processes Big Data as record values by using MapReduce programming in a distributed environment. Through MapReduce, data are stored in a Hadoop file system, and that form is not structured but unstructured. For this, it is not easy to grasp the cause, although inaccurate and unreliable data occur in the process of Hadoop-based MapReduce. As a result, Big Data may lead to a fatal flaw in the system, possibly paralyzing services. There are existing tools that monitor Hadoop systems' status. However, the status information is not related to inner structure of Hadoop system so it is not easy to analyze Hadoop systems. In this paper, we propose an intrusive analyzer that detects interesting events to occur in distributed processing systems with Hadoop in wireless sensor networks. This tool guarantees a transparent monitor as using the JDI (Java debug interface). |
| first_indexed | 2024-03-12T06:30:14Z |
| format | Article |
| id | doaj.art-94f3bc72a49a485a9d06404b5d4fadc5 |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2024-03-12T06:30:14Z |
| publishDate | 2014-07-01 |
| publisher | Hindawi - SAGE Publishing |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-94f3bc72a49a485a9d06404b5d4fadc52023-09-03T01:41:41ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772014-07-011010.1155/2014/196040196040An Intrusive Analyzer for Hadoop Systems Based on Wireless Sensor NetworksByoung-Jin Bae0Young-Joo Kim1Young-Kuk Kim2Ok-Kyoon Ha3Yong-Kee Jun4 Korea Institute of Machinery & Materials, Daejeon 305-343, Republic of Korea Electronics and Telecommunications Research Institute, Daejeon 305-700, Republic of Korea Department of Computer Science & Engineering, Chungnam National University, Daejeon 305-764, Republic of Korea Engineering Research Institute, Gyeongsang National University, Jinju 660-701, Republic of Korea Department of Informatics, Gyeongsang National University, Jinju 660-701, Republic of KoreaOwing to the acceleration of IoT- (Internet of Things-) based wireless sensor networks, cloud-computing services using Big Data are rapidly growing. In order to manage and analyze Big Data efficiently, Hadoop frameworks have been used in a variety of fields. Hadoop processes Big Data as record values by using MapReduce programming in a distributed environment. Through MapReduce, data are stored in a Hadoop file system, and that form is not structured but unstructured. For this, it is not easy to grasp the cause, although inaccurate and unreliable data occur in the process of Hadoop-based MapReduce. As a result, Big Data may lead to a fatal flaw in the system, possibly paralyzing services. There are existing tools that monitor Hadoop systems' status. However, the status information is not related to inner structure of Hadoop system so it is not easy to analyze Hadoop systems. In this paper, we propose an intrusive analyzer that detects interesting events to occur in distributed processing systems with Hadoop in wireless sensor networks. This tool guarantees a transparent monitor as using the JDI (Java debug interface).https://doi.org/10.1155/2014/196040 |
| spellingShingle | Byoung-Jin Bae Young-Joo Kim Young-Kuk Kim Ok-Kyoon Ha Yong-Kee Jun An Intrusive Analyzer for Hadoop Systems Based on Wireless Sensor Networks International Journal of Distributed Sensor Networks |
| title | An Intrusive Analyzer for Hadoop Systems Based on Wireless Sensor Networks |
| title_full | An Intrusive Analyzer for Hadoop Systems Based on Wireless Sensor Networks |
| title_fullStr | An Intrusive Analyzer for Hadoop Systems Based on Wireless Sensor Networks |
| title_full_unstemmed | An Intrusive Analyzer for Hadoop Systems Based on Wireless Sensor Networks |
| title_short | An Intrusive Analyzer for Hadoop Systems Based on Wireless Sensor Networks |
| title_sort | intrusive analyzer for hadoop systems based on wireless sensor networks |
| url | https://doi.org/10.1155/2014/196040 |
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