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Boundary Node Detection in Wireless Sensor Network

무선 센서 네트워크의 경계노드 검출

  • 김영균 (안산대학교 인터넷정보과)
  • Received : 2018.08.12
  • Accepted : 2018.09.24
  • Published : 2018.11.30

Abstract

This paper proposed an algorithm that detects boundary nodes effectively in wireless sensor network. A boundary node is a sensor that lies on the border of network holes or the outer boundary of wireless sensor network. Proposed algorithm detects boundary nodes using only the position information of sensors. In addition, to improve detect performance, sensor computes the overlap area of nearest sensor first. Simulation is performed to validate the process of the proposed algorithm. In Simulation, several obstacles are placed and varying number of sensors in the range of 500~1500 are deployed in the area in order to reflect real world. The simulation results shows that proposed algorithm detects boundary nodes effectively that are located on the border of holes and the outer boundary of wireless sensor network.

본 논문은 무선 센서 네트워크의 경계노드를 효과적으로 검출하는 알고리즘을 제안한다. 경계노드는 센서 네트워크의 외부 경계 또는 홀의 경계에 존재하는 센서이다. 제안한 알고리즘은 센서의 위치정보만을 이용하여 네트워크의 경계노드를 검출한다. 또한 검출 속도를 향상시키기 위해 센서는 거리에 따라 근접한 센서와의 중첩영역을 먼저 계산한다. 알고리즘의 동작을 검증하기 위해 시뮬레이션을 수행하였다. 시뮬레이션에서 현실 세계를 최대한 반영하기 위해 정해진 영역에 여러 개의 장애물을 설치하고 센서의 개수를 500~1500개 범위에서 다르게 배치하였다. 시뮬레이션을 통하여 제안한 알고리즘이 네트워크 외부 및 홀의 경계에 존재하는 경계노드들을 효과적으로 검출하는 것을 확인하였다.

Keywords

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그림 1. 센서의 감지영역과 경계교차점 Figure 1. Sensing area and boundary intersection points of sensors

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그림 2. 센서 배치에 따른 경계노드 구분 Figure 2. Boundary node decision based on sensor deployment

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그림 3. 제안 알고리즘의 흐름도 Figure 3. Proposed algorithm flowchart

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그림 4. 센서 네트워크의 경계노드 검출 Figure 4. Boundary nodes detection of sensor network

표 1. 시뮬레이션 파라미터 Table 1. Simulation Parameters

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References

  1. Sabri, Naseer, et al. "Towards smart wireless sensor actor networks: Design factors and applications", IEEE Symposium on Industrial Electronics and Applications (ISIEA), pp. 704-708, 2011.
  2. Y. C. Wang, F. J. Wu, and Y. C. Tseng, "Mobility management algorithms and applications for mobile sensor networks", Wireless Communications and Mobile Computing, vol. 12, no. 1, pp. 7-21, 2012. https://doi.org/10.1002/wcm.886
  3. M. Saoudi, et al. "D-LPCN: A distributed least polar-angle connected node algorithm for finding the boundary of a wireless sensor network". Ad Hoc Networks, pp. 56-71, 2017.
  4. A. M. Khedr, W. Osamy, "Minimum connected cover of a query region in heterogeneous wireless sensor networks", Information Sciences, pp. 153-163, 2013.
  5. W. T. Wang and K. F. Ssu, "Obstacle detection and estimation in wireless sensor networks", Computer Networks, vol. 57, no. 4, pp. 858-868, 2013. https://doi.org/10.1016/j.comnet.2012.11.004
  6. L. Zhao, et al. "Detecting boundary nodes and coverage holes in wireless sensor networks", Mobile Information Systems, 2016.
  7. W. Li and W. Zhang, "Coverage hole and boundary nodes detection in wireless sensor networks", Journal of Network and Computer Applications, vol. 48, pp. 35-43, 2015. https://doi.org/10.1016/j.jnca.2014.10.011
  8. X. Y. Li, G. Calinescu, P. J.Wan and Y.Wang, "Localized delaunay triangulation with application in ad hoc wireless networks", IEEE Transactions on Parallel and Distributed Systems, vol. 14, no. 10, pp. 1035-1047, 2003. https://doi.org/10.1109/TPDS.2003.1239871
  9. W. C. Chu and K. F. Ssu, "Location-free boundary detection in mobile wireless sensor networks with a distributed approach", Computer Networks, vol. 70, pp. 96-112, 2014. https://doi.org/10.1016/j.comnet.2014.05.005
  10. B. Huang, W. Wu, G. Gao and T. Zhang, "Recognizing boundaries in wireless sensor networks based on local connectivity information", International Journal of Distributed Sensor Networks, vol. 2014, Article ID 897039, 12 pages, 2014.
  11. I. M. Khan, N. Jabeur and S. Zeadally, "Hop-based approach for holes and boundary detection in wireless sensor networks," IET Wireless Sensor Systems, vol. 2, no. 4, pp. 328-337, 2012. https://doi.org/10.1049/iet-wss.2012.0076
  12. Y. Kim, "Clustering for improved Actor Connectivity and Coverage in Wireless Sensor and Actor Networks", Journal of The Korea Society of Computer and Information, Vol. 19, No. 8, pp. 63-71, 2014. https://doi.org/10.9708/JKSCI.2014.19.8.063
  13. Y. M. Kim, et al. "Adaptive method for selecting Cluster Head according to the energy of the sensor node", International Journal of Advanced Culture Technology(IJACT), Vol. 4 No. 2, pp. 19-26, 2016. https://doi.org/10.17703/IJACT.2016.4.2.19