정보처리학회논문지:컴퓨터 및 통신 시스템 (KIPS Transactions on Computer and Communication Systems)

  • 제7권12호
  • /
  • Pages.301-312
  • /
  • 2018
  • /
  • 2287-5891(pISSN)
  • /
  • 2734-049X(eISSN)
한국정보처리학회 (Korea Information Processing Society)
권호 표지
DOI QR코드

DOI QR Code

산업용 무선 센서망을 이용한 연속개체 탐지에서 이동 싱크 지원을 위한 발원점 중심의 통신방안

An Origin-Centric Communication Scheme to Support Sink Mobility for Continuous Object Detection in IWSNs

  • 김명은 (한국전자통신연구원 IoT연구본부) ;
  • 김천용 (충남대학교 컴퓨터공학과) ;
  • 임용빈 (충남대학교 컴퓨터공학과) ;
  • 김상하 (충남대학교 컴퓨터공학과) ;
  • 손영성 (한국전자통신연구원 IoT연구본부)
  • 투고 : 2018.05.02
  • 심사 : 2018.08.14
  • 발행 : 2018.12.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

오늘날 산업용 무선 센서 망 환경에서 화재나 유독가스와 같은 연속 개체 탐지는 위험성과 대규모 피해로 인해 중요한 문제로 다뤄지고 있다. 연속 개체는 한 지점에서 발생하여 점차 넒은 범위로 확산되는 특징을 가지기 때문에 자원 제약적인 무선 센서 망 환경에서 연속 개체를 탐지한 다수의 센서 노드가 고정 싱크에게 데이터를 전송하게 되면 막대한 통신 오버헤드가 발생하게 된다. 따라서 기존 연구에서는 실시간으로 확장되는 연속 개체를 정확하게 탐지하고, 다량의 센싱 데이터를 에너지 효율적인 방식으로 전송하는 데에 중점을 두었다. 그러나 최근 들어 화재 진압과 같은 실시간 대응이 필요한 응용분야를 위해 연속 개체 탐지에 이동 싱크 도입이 필요하다는 의견이 나타나고 있다. 이러한 경우, 이동 싱크의 위치 갱신을 위해 다수의 소스와 이동 싱크 간 통신이 빈번하게 일어남으로써 무선 센서망의 에너지 소모가 급격하게 증가하는 문제가 발생한다. 본 논문에서는 무선 센서 망을 이용한 연속 개체 탐지에서 이동 싱크를 지원하기 위한 발원점 중심의 통신 방안을 제안한다. 실험결과는 제안 방안이 기존 방안에 비해 이동 싱크의 위치정보 갱신 및 센싱 데이터 보고에 더 적은 에너지를 소모함을 보인다.

In industrial wireless sensor networks, the continuous object detection such as fire or toxic gas detection is one of major applications. A continuous object occurs at a specific point and then diffuses over a wide area. Therefore, many studies have focused on accurately detecting a continuous object and delivering data to a static sink with an energy-efficient way. Recently, some applications such as fire suppression require mobile sinks to provide real-time response. However, the sink mobility support in continuous object detection brings challenging issues. The existing approaches supporting sink mobility are designed for individual object detection, so they establish one-to-one communication between a source and a mobile sink for location update. But these approaches are not appropriate for a continuous object detection since a mobile sink should establish one-to-many communication with all sources. The one-to-many communication increases energy consumption and thus shortens the network lifetime. In this paper, we propose the origin-centric communication scheme to support sink mobility in a continuous object detection. Simulation results verify that the proposed scheme surpasses all the other work in terms of energy consumption.

키워드

JBCRIN_2018_v7n12_301_f0001.png 이미지

Fig. 1. A Use Case of Continuous Object Detection with a Mobile Sink

JBCRIN_2018_v7n12_301_f0002.png 이미지

Fig. 2. An Example of Wireless Sensor Network

JBCRIN_2018_v7n12_301_f0003.png 이미지

Fig. 3. Origin-Centric Virtual Network Construction (a) The Propagation of Setup Messages (b) An Example of Origin-Centric Virtual Network After Initial Routes Setup

JBCRIN_2018_v7n12_301_f0004.png 이미지

Fig. 4. An Example of Boundary Detection

JBCRIN_2018_v7n12_301_f0005.png 이미지

Fig. 5. A State Transition Diagram of a Routing Node

JBCRIN_2018_v7n12_301_f0006.png 이미지

Fig. 6. Two Phase-based Location Update (a) The First Phase of Location Update (b) The Second Phase of Location Update

JBCRIN_2018_v7n12_301_f0007.png 이미지

Fig. 7. Comparing Nodes Energy Consumption in Updating Mobile Sink’s Location for Different Sizes of Network

JBCRIN_2018_v7n12_301_f0008.png 이미지

Fig. 8. Comparing Nodes Energy Consumption in Updating Mobile Sink’s Location for Different Sizes of a Continuous Object

JBCRIN_2018_v7n12_301_f0009.png 이미지

Fig. 9. Comparing Nodes Energy Consumption in Reporting Data to the Mobile Sink for Different Network Sizes

참고문헌

  1. Soltani, Mohammad Reza et al., "Power-aware and voidavoidant routing protocol for reliable Industrial Wireless Sensor Networks," in Proceedings of the International Conference on Wireless Communications, Networking and Mobile Computing, 2011.
  2. Ovsthus, Knut and Lars M. Kristensen, "An industrial perspective on wireless sensor networks-a survey of requirements, protocols, and challenges," IEEE Communications Surveys & Tutorials, Vol.16, No.3, pp. 1391-1412, 2014. https://doi.org/10.1109/SURV.2014.012114.00058
  3. Han, Guangjie et al., "BRTCO: a novel boundary recognition and tracking algorithm for continuous objects in wireless sensor networks," IEEE Systems Journal, 2016.
  4. Chang, Wang-Rong, Hui-Tang Lin, and Zong-Zhi Cheng, "CODA: a continuous object detection and tracking algorithm for wireless ad hoc sensor networks," in Proceedings of the IEEE Consumer Communications and Networking Conference, 2008.
  5. Jung-Hwan, K. I. M. et al., "DEMOCO: Energy-efficient detection and monitoring for continuous objects in wireless sensor networks," IEICE Transactions on Communications, Vol.91, No.11, pp.3648-3656, 2008. https://doi.org/10.1093/ietcom/e91-b.11.3648
  6. Soochang Park, Hosung Park, Euisin Lee, and Sang-Ha Kim, "Reliable and Flexible Detection of Large-Scale Phenomena on Wireless Sensor Networks," IEEE Communications Letter, Vol.16, No.6, pp.933-936, 2012. https://doi.org/10.1109/LCOMM.2012.032612.112345
  7. Pantazis, Nikolaos A., Stefanos A. Nikolidakis, and Dimitrios D. Vergados, "Energy-efficient routing protocols in wireless sensor networks: A survey," IEEE Communications Surveys & Tutorials, Vol.15, No.2, pp.551-591, 2013. https://doi.org/10.1109/SURV.2012.062612.00084
  8. Luo, Haiyun et al., "TTDD: Two-tier data dissemination in large-scale wireless sensor networks," Wireless Networks, Vol.11, No.1-2, pp.161-175, 2005. https://doi.org/10.1007/s11276-004-4753-x
  9. Hamida, Elyes Ben, and Guillaume Chelius, "A line-based data dissemination protocol for wireless sensor networks with mobile sink," in Proceedings of the IEEE International Conference on Communications, 2008.
  10. Kweon, Kisuk et al., "Grid-based energy-efficient routing from multiple sources to multiple mobile sinks in wireless sensor networks," in Proceedings of the IEEE International Symposium on Wireless Pervasive Computing, 2009.
  11. Khan, Abdul Waheed et al., "VGDRA: a virtual grid-based dynamic routes adjustment scheme for mobile sink-based wireless sensor networks," IEEE Sensors Journal, Vol.15, No.1, pp.526-534, 2015. https://doi.org/10.1109/JSEN.2014.2347137
  12. Yarinezhad, Ramin, and Amir Sarab, "Reducing delay and energy consumption in wireless sensor networks by making virtual grid infrastructure and using mobile sink," AEUInternational Journal of Electronics and Communications. Vol.84, pp.144-152, 2018.
  13. Rhee, Sokwoo, Deva Seetharam, and Sheng Liu, "Techniques for minimizing power consumption in low data-rate wireless sensor networks," in Wireless Communications and Networking Conference, Vol.3, pp.1727-1731, 2004.
  14. Zhao, Gang, "Wireless sensor networks for industrial process monitoring and control: A survey," Network Protocols and Algorithms, Vol.3, No.1, pp.46-63, 2011.
  15. Hill, Jason L., and David E. Culler, "Mica: A wireless platform for deeply embedded networks," IEEE Micro, Vol.22, No.6, pp.12-24, 2002. https://doi.org/10.1109/MM.2002.1134340
  16. Han, Guangjie, Jinfang Jiang, Chenyu Zhang, Trung Q. Duong, Mohsen Guizani, and George K. Karagiannidis, "A Survey on Mobile Anchor Node Assisted Localization in Wireless Sensor Networks," IEEE Communications Surveys and Tutorials, Vol.18, No.3, pp.2220-2243, 2016. https://doi.org/10.1109/COMST.2016.2544751