Remote Industrial Sensor Network Monitoring Using M2M Based Ethical Sniffers
Diagnosing the deployed network efficiency and anomaly detection, which is an important research issue in traditional networking systems, has not been carefully addressed in industrial wireless sensor networks. Although recent wireless systems for industrial automation such as ISA100.11a employ devi...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-11-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2012/286424 |
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| _version_ | 1832555350582099968 |
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| author | Syed Muhammad Asad Zaidi Jieun Jung Minsoo Kang Byunghun Song Ki-Hyung Kim |
| author_facet | Syed Muhammad Asad Zaidi Jieun Jung Minsoo Kang Byunghun Song Ki-Hyung Kim |
| author_sort | Syed Muhammad Asad Zaidi |
| collection | DOAJ |
| description | Diagnosing the deployed network efficiency and anomaly detection, which is an important research issue in traditional networking systems, has not been carefully addressed in industrial wireless sensor networks. Although recent wireless systems for industrial automation such as ISA100.11a employ device management protocols, these protocols generate and report a large amount of status information from individual sensor nodes. Also, these protocols do not capture influences on network performance from external sources such as malicious nodes or interference from other networks. We propose a latent network diagnosis system (LaNDS) for industrial sensor networks. LaNDS employs a packet sniffing method for efficiently evaluating network performance and instantly identifying degradation causes of networking performance. LaNDS adopts an efficient network evaluation approach for detecting abnormalities from both internal and external causes. In our proposed monitoring scenario, special sniffer devices having M2M capability (WiMAX interface) are used to monitor the industrial sensor network by employing ethical sniffing. Our approach does not incur additional traffic overhead for collecting desired information. For evaluation, we have tested LaNDS locally on an ISA100.11a based sensor network in a lab environment and have validated the efficiency of the system based on the possible erroneous cases of industrial sensor network. |
| format | Article |
| id | doaj-art-9dd63237782942d6894c1b73af6a73b4 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2012-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-9dd63237782942d6894c1b73af6a73b42025-02-03T05:48:30ZengWileyInternational Journal of Distributed Sensor Networks1550-14772012-11-01810.1155/2012/286424Remote Industrial Sensor Network Monitoring Using M2M Based Ethical SniffersSyed Muhammad Asad Zaidi0Jieun Jung1Minsoo Kang2Byunghun Song3Ki-Hyung Kim4 IoT Convergence Research Center, Korea Electronics Technology Institute (KETI), Seongnam 463-816, Republic of Korea IoT Convergence Research Center, Korea Electronics Technology Institute (KETI), Seongnam 463-816, Republic of Korea RFID/USN Program, Korea Evaluation Institute of Industrial Technology, Seoul 135-080, Republic of Korea IoT Convergence Research Center, Korea Electronics Technology Institute (KETI), Seongnam 463-816, Republic of Korea School of Information & Computer Engineering, Ajou University, Suwon 443-749, Republic of KoreaDiagnosing the deployed network efficiency and anomaly detection, which is an important research issue in traditional networking systems, has not been carefully addressed in industrial wireless sensor networks. Although recent wireless systems for industrial automation such as ISA100.11a employ device management protocols, these protocols generate and report a large amount of status information from individual sensor nodes. Also, these protocols do not capture influences on network performance from external sources such as malicious nodes or interference from other networks. We propose a latent network diagnosis system (LaNDS) for industrial sensor networks. LaNDS employs a packet sniffing method for efficiently evaluating network performance and instantly identifying degradation causes of networking performance. LaNDS adopts an efficient network evaluation approach for detecting abnormalities from both internal and external causes. In our proposed monitoring scenario, special sniffer devices having M2M capability (WiMAX interface) are used to monitor the industrial sensor network by employing ethical sniffing. Our approach does not incur additional traffic overhead for collecting desired information. For evaluation, we have tested LaNDS locally on an ISA100.11a based sensor network in a lab environment and have validated the efficiency of the system based on the possible erroneous cases of industrial sensor network.https://doi.org/10.1155/2012/286424 |
| spellingShingle | Syed Muhammad Asad Zaidi Jieun Jung Minsoo Kang Byunghun Song Ki-Hyung Kim Remote Industrial Sensor Network Monitoring Using M2M Based Ethical Sniffers International Journal of Distributed Sensor Networks |
| title | Remote Industrial Sensor Network Monitoring Using M2M Based Ethical Sniffers |
| title_full | Remote Industrial Sensor Network Monitoring Using M2M Based Ethical Sniffers |
| title_fullStr | Remote Industrial Sensor Network Monitoring Using M2M Based Ethical Sniffers |
| title_full_unstemmed | Remote Industrial Sensor Network Monitoring Using M2M Based Ethical Sniffers |
| title_short | Remote Industrial Sensor Network Monitoring Using M2M Based Ethical Sniffers |
| title_sort | remote industrial sensor network monitoring using m2m based ethical sniffers |
| url | https://doi.org/10.1155/2012/286424 |
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