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

Korea Information Processing Society (한국정보처리학회)
권호 표지
DOI QR코드

DOI QR Code

An Energy-Efficient Algorithm for Solving Coverage Problem and Sensing Big Data in Sparse MANET Environments

희소 모바일 애드 혹 네트워크 환경에서 빅데이터 센싱을 위한 에너지 효율적인 센서 커버리지 알고리즘

  • 길준민 (대구가톨릭대학교 IT공학부)
  • Received : 2017.09.18
  • Accepted : 2017.10.16
  • Published : 2017.11.30
Download PDF
⟨ Previous Next ⟩

Abstract

To sense a wide area with mobile nodes, the uniformity of node deployment is a very important issue. In this paper, we consider the coverage problem to sense big data in sparse mobile ad hoc networks. In most existing works on the coverage problem, it has been assumed that the number of nodes is large enough to cover the area in the network. However, the coverage problem in sparse mobile ad hoc networks differs in the sense that a long-distance between nodes should be formed to avoid the overlapping coverage areas. We formulate the sensor coverage problem in sparse mobile ad hoc networks and provide the solution to the problem by a self-organized approach without a central authority. The experimental results show that our approach is more efficient than the existing ones, subject to both of coverage areas and energy consumption.

모바일 노드를 이용하여 넓은 범위를 센싱하기 위해서는 노드 배치의 균일성이 매우 중요한 이슈 중 하나이다. 본 논문에서는 희소 모바일 애드 혹 네트워크 환경에서 빅 데이터 센싱을 위한 커버리지 문제에 대한 주제를 다룬다. 커버리지 문제에 관한 기존 연구에서는 넓은 범위를 센싱하기 위해 노드의 수가 충분히 많은 환경을 가정하였다. 하지만 희소 모바일 애드 혹 네트워크 환경에서 센서 커버리지 문제는 노드들 간의 센싱 범위가 겹치는 범위를 최소화하기 위해 노드들 간의 거리가 충분히 멀어야 한다. 따라서 본 논문에서는 희소 모바일 애드 혹 네트워크 환경에서 센서 커버리지 문제를 정의하고 중앙 중재자 없이 자가 조직의 방식에 의한 해결 방안을 제시한다. 실험 결과를 통해 제안하는 방식은 커버리지 영역과 에너지 소비 관점에서 효율적임을 보인다.

Keywords

References

  1. E. Fadel, V. C. Gungor, L. Nassef, N. Akkari, M. G. Malik, S, Almasri, and I. F. Akyildiz, "A survey on wireless sensor networks for smart grid," Computer Communications, Vol. 71, pp.22-33, 2015. https://doi.org/10.1016/j.comcom.2015.09.006
  2. G. P. Gupta, M. Misra, and K. Garg, "An Energy Efficient Distributed Approach-Based Agent Migration Scheme for Data Aggregation in Wireless Sensor Networks," Journal of Information Processing Systems, Vol.11, No.1, pp.148-164, 2015. https://doi.org/10.3745/JIPS.03.0018
  3. Yasmine-Derdour, Bouabdellah-Kechar, and M. Faycal-Khelfi, "Using Mobile Data Collectors to Enhance Energy Efficiency and Reliability in Delay Tolerant Wireless Sensor Networks," Journal of Information Processing Systems, Vol.12, No.2, pp.275-294, 2016. https://doi.org/10.3745/JIPS.03.0032
  4. M. Conti and S. Giordano, "Mobile ad hoc networking: milestones, challenges, and new research directions," IEEE Communications Magazine, Vol.52, No.1, pp.85-96, 2014. https://doi.org/10.1109/MCOM.2014.6710069
  5. M. Conti and S. Giordano, "Multihop Ad Hoc Networking: The Evolutionary Path," in Mobile Ad Hoc Networking: John Wiley & Sons, Inc., 2013, pp.1-33.
  6. M. S. Gaur and B. Pant, "Trusted and secure clustering in mobile pervasive environment," Human-centric Computing and Information Sciences, Vol.5, No.1, pp.1-17, 2015. https://doi.org/10.1186/s13673-014-0018-6
  7. D. Kim, J.-H. Kim, C. Moon, J. Choi, and I. Yeom, "Efficient content delivery in mobile ad-hoc networks using CCN," Ad Hoc Networks, Vol.36, Part 1, pp.81-99, 2016. https://doi.org/10.1016/j.adhoc.2015.06.007
  8. X. M. Zhang, E. B. Wang, J. J. Xia, and D. K. Sung, "A Neighbor Coverage-Based Probabilistic Rebroadcast for Reducing Routing Overhead in Mobile Ad Hoc Networks," IEEE Transactions on Mobile Computing, Vol.12, No.3, pp. 424-433, 2013. https://doi.org/10.1109/TMC.2011.277
  9. W. Sun, Z. Yang, X. Zhang, and Y. Liu, "Energy-Efficient Neighbor Discovery in Mobile Ad Hoc and Wireless Sensor Networks: A Survey," IEEE Communications Surveys & Tutorials, Vol.16, No.3, pp.1448-1459, 2014. https://doi.org/10.1109/SURV.2013.012414.00164
  10. P. Bellavista, G. Cardone, A. Corradi, and L. Foschini, "Convergence of MANET and WSN in IoT Urban Scenarios," IEEE Sensors Journal, Vol.13, No.10, pp.3558-3567, 2013. https://doi.org/10.1109/JSEN.2013.2272099
  11. M. Conti et al., "From MANET to people-centric networking: Milestones and open research challenges," Computer Communications, Vol.71, pp.1-21, 2015. https://doi.org/10.1016/j.comcom.2015.09.007
  12. S. Mini, S. K. Udgata, and S. L. Sabat, "Sensor Deployment and Scheduling for Target Coverage Problem in Wireless Sensor Networks," IEEE Sensors Journal, Vol.14, No.3, pp. 636-644, 2014. https://doi.org/10.1109/JSEN.2013.2286332
  13. B. Liu, O. Dousse, P. Nain, and D. Towsley, "Dynamic Coverage of Mobile Sensor Networks," IEEE Transactions on Parallel and Distributed Systems, Vol.24, No.2, pp.301-311, 2013. https://doi.org/10.1109/TPDS.2012.141
  14. C. Zhu, C. Zheng, L. Shu, and G. Han, "A survey on coverage and connectivity issues in wireless sensor networks," Journal of Network and Computer Applications, Vol.35, No. 2, pp.619-632, 2012. https://doi.org/10.1016/j.jnca.2011.11.016
  15. A. Sangwan and R. P. Singh, "Survey on Coverage Problems in Wireless Sensor Networks," Wireless Personal Communications, Vol.80, No.4, pp.1475-1500, 2015. https://doi.org/10.1007/s11277-014-2094-3
  16. W. Luo, J. Wang, J. Guo, and J. Chen, "Parameterized complexity of Max-lifetime Target Coverage in wireless sensor networks," Theoretical Computer Science, Vol.518, pp.32-41, 2014. https://doi.org/10.1016/j.tcs.2013.06.008
  17. Z. Liao, J. Wang, S. Zhang, J. Cao, and G. Min, "Minimizing Movement for Target Coverage and Network Connectivity in Mobile Sensor Networks," IEEE Transactions on Parallel and Distributed Systems, Vol.26, No.7, pp.1971-1983, 2015. https://doi.org/10.1109/TPDS.2014.2333011
  18. Z. Lu, W. W. Li, and M. Pan, "Maximum Lifetime Scheduling for Target Coverage and Data Collection in Wireless Sensor Networks," IEEE Transactions on Vehicular Technology, Vol.64, No.2, pp.714-727, 2015. https://doi.org/10.1109/TVT.2014.2322356
  19. A. S. M. Zahid Kausar, A. W. Reza, M. U. Saleh, and H. Ramiah, "Energizing wireless sensor networks by energy harvesting systems: Scopes, challenges and approaches," Renewable and Sustainable Energy Reviews, Vol.38, pp. 973-989, 2014. https://doi.org/10.1016/j.rser.2014.07.035
  20. F. K. Shaikh and S. Zeadally, "Energy harvesting in wireless sensor networks: A comprehensive review," Renewable and Sustainable Energy Reviews, Vol.55, pp.1041-1054, 2016. https://doi.org/10.1016/j.rser.2015.11.010
  21. P. V. Mekikis, E. Kartsakli, A. S. Lalos, A. Antonopoulos, L. Alonso, and C. Verikoukis, "Connectivity of large-scale WSNs in fading environments under different routing mechanisms," in 2015 IEEE International Conference on Communications (ICC), pp.6553-6558, 2015.