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Duty Cycle Scheduling considering Delay Time Constraints in Wireless Sensor Networks

무선네트워크에서의 지연시간제약을 고려한 듀티사이클 스케쥴링

  • 부쥐손 (울산대학교 전기전자컴퓨터공학과) ;
  • 윤석훈 (울산대학교 IT융합학부)
  • Received : 2018.03.18
  • Accepted : 2018.04.06
  • Published : 2018.04.30

Abstract

In this paper, we consider duty-cycled wireless sensor networks (WSNs) in which sensor nodes are periodically dormant in order to reduce energy consumption. In such networks, as the duty cycle interval increases, the energy consumption decreases. However, a higher duty cycle interval leads to the increase in the end-to-end (E2E) delay. Many applications of WSNs are delay-sensitive and require packets to be delivered from the sensr nodes to the sink with delay requirements. Most of existing studies focus on only reducing the E2E delay, rather than considering the delay bound requirement, which makes hard to achieve the balanced performance between E2E delay and energy consumption. A few study that considered delay bound requirement require time synchronization between neighboring nodes or a specific distribution of deployed nodes. In order to address limitations of existing works, we propose a duty-cycle scheduling algorithm that aims to achieve low energy consumption, while satisfying the delay requirements. To that end, we first estimate the probability distribution for the E2E delay. Then, by using the obtained distribution we determine the maximal duty cycle interval that still satisfies the delay constraint. Simulation results show that the proposed design can satisfy the given delay bound requirements while achieving low energy consumption.

본 논문에서는 센서노드가 전력소모를 줄이기 위하여 주기적으로 휴면상태를 갖는 듀티사이클 기반 무선센서 네트워크를 고려한다. 이러한 네트워크에서는 듀티사이클 간격이 커진다면 전력소모는 감소하지만 종단간 지연시간은 늘어나게 된다. 무선센서네트워크의 많은 애플리케이션은 지연시간에 민감하며 패킷이 센서노드로부터 싱크노드에게 전달되는 데 있어서 지연시간제약 요구사항이 있다. 기존의 대부분의 연구는 종단간 지연시간을 줄이는 것에만 초점을 맞추고 지연시간제약에 대해 고려를 하지 않음으로써 종단간지연시간과 전력소모에 대한 균형을 맞추기 어려웠다. 지연시간제약을 고려하는 연구에서도 노드들간의 시각동기화를 요구하거나 노드들이 특정한 분포를 갖는다고 가정하였다. 기존 연구의 이러한 제약을 극복하기 위하여 본 논문에서는 지연시간제약조건을 충족시키면서 동시에 전력소모를 줄이기 위한 듀티사이클 스케쥴링 알고리즘을 제안한다. 먼저 종단간 지연시간의 확률분포를 추정하고 획득한 분포를 이용하여 지연시간제약조건을 만족하는 최대 듀티사이클 간격을 결정한다. 시뮬레이션 결과에 따르면 제안되는 알고리즘은 주어진 지연시간제약 요구사항을 만족하면서도 낮은 전력소모 성능을 보인다.

Keywords

References

  1. P. Rawat, K. D. Singh, H. Chaouchi, and J. Bonnin, "Wireless sensor networks: a survey on recent developments and potential synergies," The Journal of Supercomputing, vol. 68, no. 1, pp. 1-48, Apr 2014. https://doi.org/10.1007/s11227-013-1021-9
  2. W. Y. Chang, Y. C. Lee, and J. J. Kang, "Implementation of IoT sensors network using mobius platform," The Journal of The Institute of Internet, Broadcasting and Communication (JIIBC), vol. 17, no. 2, pp. 211-218, April 2017. https://doi.org/10.7236/JIIBC.2017.17.2.211
  3. J. Hao, B. Zhang, and H. T. Mouftah, "Routing protocols for duty cycled wireless sensor networks:A survey," IEEE Communications Magazine, vol. 50, no. 12, pp. 116-123, December 2012. https://doi.org/10.1109/MCOM.2012.6384460
  4. Y. Gu and T. He, "Dynamic switching-based data forwarding for low-duty-cycle wireless sensor networks," IEEE Transactions on Mobile Computing, vol. 10, no. 12, pp. 1741-1754, Dec 2011. https://doi.org/10.1109/TMC.2010.266
  5. C. J. Merlin and W. B. Heinzelman, "Node synchronization for minimizing delay and energy consumption in low-power listening mac protocols," in 2008 5th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, Sept 2008, pp. 265-274.
  6. J. Jung, J. Yoon, Y. Yun, S. So, and S. Eun, "A dynamic duty cycle adjustment mechanism for reduced latency in industrial plants," The Journal of The Institute of Internet, Broadcasting and Communication (JIIBC), vol. 16, no. 1, pp. 193-198, February 2016. https://doi.org/10.7236/JIIBC.2016.16.1.193
  7. R. C. Carrano, D. Passos, L. C. S. Magalhaes, and C. V. N. Albuquerque, "Survey and taxonomy of duty cycling mechanisms in wireless sensor networks," IEEE Communications Surveys Tutorials, vol. 16, no. 1, pp. 181-194, First 2014. https://doi.org/10.1109/SURV.2013.052213.00116
  8. J. Kim, X. Lin, N. B. Shroff, and P. Sinha, "Minimizing delay and maximizing lifetime for wireless sensor networks with anycast," IEEE/ACM Transactions on Networking, vol. 18, no. 2, pp. 515-528, April 2010. https://doi.org/10.1109/TNET.2009.2032294
  9. B. Nazir and H. Hasbullah, "Dynamic sleep scheduling for minimizing delay in wireless sensor network," in 2011 Saudi International Electronics, Communications and Photonics Conference (SIECPC), April 2011, pp. 1-5.
  10. Z. Fan, S. Bai, S. Wang, and T. He, "Delay-bounded transmission power control for low-duty-cycle sensor networks," IEEE Transactions on Wireless Communications, vol. 14, no. 6, pp. 3157-3170, June 2015. https://doi.org/10.1109/TWC.2015.2402681
  11. T. N. Dao, S. Yoon, and J. Kim, "A deadline-aware scheduling and forwarding scheme in wireless sensor networks," Sensors, vol. 16, no. 1, 2016.
  12. G. McLachlan, "Finite mixture models [electronic resource]," Hoboken, 2004.
  13. "Network simulator," accessed 03-2018. Available: https://www.isi.edu/nsnam/ns/
  14. Virtenio, "Preon32 wireless module datasheet," accessed 03-2018. Available: https://www.virtenio.com