정보과학회 논문지 (Journal of KIISE)

  • 제42권12호
  • /
  • Pages.1495-1502
  • /
  • 2015
  • /
  • 2383-630X(pISSN)
  • /
  • 2383-6296(eISSN)
한국정보과학회 (Korean Institute of Information Scientists and Engineers)
권호 표지
DOI QR코드

DOI QR Code

태양 에너지 기반 무선 센서 네트워크를 위한 에너지 적응형 선택적 압축 기법

Energy-aware Selective Compression Scheme for Solar-powered Wireless Sensor Networks

  • 강민재 (숭실대학교 전자공학과) ;
  • 정세미 (숭실대학교 융합소프트웨어학과) ;
  • 노동건 (숭실대학교 융합소프트웨어학과)
  • 투고 : 2015.08.17
  • 심사 : 2015.09.22
  • 발행 : 2015.12.15
⟨ 이전 논문 다음 논문 ⟩

초록

센서 네트워크에서 압축은 종단 간 지연시간과 에너지 사용량 사이의 이율배반적인 관계가 있다. 데이터의 크기를 줄이기 위해 압축을 하면, 추가적인 지연시간과 에너지 소비가 발생하지만, 전송으로 인한 에너지 소모는 감소하게 된다. 일반적으로, 배터리기반 센서 네트워크에서는 지연시간을 손해 보더라도 네트워크의 생존시간을 최대화하기위해 압축을 널리 사용하고 있다. 한편 태양 에너지 기반 센서 네트워크에서는 주기적으로 에너지 재생산이 이루어짐에 따라, 동작하는데 충분한 에너지양 이상의 에너지가 존재할 가능성이 있다. 본 논문에서는 여분의 에너지를 사용해 종단 간 지연시간을 감소시키는 에너지 적응형 선택적 압축 기법을 제안한다. 제안하는 기법은 노드의 에너지가 충분하지 않을 때, 에너지 소비를 줄이기 위해 압축을 사용하고, 에너지가 충분한 경우에는 종단 간 지연시간 감소를 위해 압축을 사용하지 않는다. 시뮬레이션을 통한 에너지와 지연시간의 성능평가를 통하여 제안하는 기법의 우수성을 증명하였다.

Data compression involves a trade-off between delay time and data size. Greater delay times require smaller data sizes and vice versa. There have been many studies performed in the field of wireless sensor networks on increasing network life cycle durations by reducing data size to minimize energy consumption; however, reductions in data size result in increases of delay time due to the added processing time required for data compression. Meanwhile, as energy generation occurs periodically in solar energy-based wireless sensor networks, redundant energy is often generated in amounts sufficient to run a node. In this study, this excess energy is used to reduce the delay time between nodes in a sensor network consisting of solar energy-based nodes. The energy threshold value is determined by a formula based on the residual energy and charging speed. Nodes with residual energy below the threshold transfer data compressed to reduce energy consumption, and nodes with residual energy above the threshold transfer data without compression to reduce the delay time between nodes. Simulation based performance verifications show that the technique proposed in this study exhibits optimal performance in terms of both energy and delay time compared with traditional methods.

키워드

참고문헌

  1. S. Sudevalayam and P. Kulkarni, "Energy harvesting sensor nodes: Survey and implications," Journal of IEEE Communications Surveys & Tutorials, Vol. 13, No. 3, pp. 443-461, Jul. 2010.
  2. Y. Yang, L. Wang, D. K. Noh, H. K. Le and T. F. Abdelzaher, "SolarStore: Enhancing Data Reliability in Solar-powered Storage-centric Sensor Networks," Proc. of the 7th Annual International Conference on Mobile Systems, Applications, and Services, pp. 333-346, Jun. 2009.
  3. H. J. Lee, H. Kim and I. J. Chang, "CPAC: Energy-Efficient Data Collection through Adaptive Selection of Compression Algorithms for Sensor Networks," Journal of Sensors 2014, Vol. 14, No. 4, pp. 6419-6442, Apr. 2014. https://doi.org/10.3390/s140406419
  4. I. Stojmenovic. Handbook of Sensor Networks. Wiley-Interscience, 2005.
  5. C. Alippi, G. Anastasi, M. D. Francesco, and M. Roveri, "Energy Management in Wireless Sensor Networks with Energy-hungry Sensors," Journal of IEEE Instrumentation & Measurement Magazine, Vol. 12, No. 2, pp. 16-23, Apr. 2009.
  6. A. Kansal, J. Hsu, S. Zahedi, and M. B. Srivastava, "Power management in energy harvesting sensor networks," Journal of ACM Transactions on Embedded Computing Systems, Vol. 6, No. 4, Sep. 2007.
  7. X. Jiang, J. Polastre, and D. Culler, "Perpetual environmentally powered sensor networks," Forth International Symposium on Information Processing in Sensor Networks 2005, pp. 463-468, Apr. 2005.
  8. A. Kansal, J. Hsu, M. Srivastava and V. Raghunathan, "Harvesting aware power management for sensor networks," Proc. of 43rd Annual Design Automation Conference, pp. 651-656, Jul. 2006.
  9. C. Alippi. and C, Galperti, "An Adaptive System for Optimal Solar Energy Harvesting in Wireless Sensor Network Nodes," IEEE Trans. on Circuits and Systems, Vol. 55, No. 6, pp. 1742-1750, Jul. 2008. https://doi.org/10.1109/TCSI.2008.922023
  10. J. Taneja, J. Jeong and D. Culler, "Design, Modeling, and Capacity Planning for Micro-solar Power Sensor Networks," Proc. of 7th international conference on Information processing in sensor networks, pp. 407-418, Apr. 2008.
  11. D. Noh, D. Lee, H. Shin, "QoS-Aware Geographic Routing for Solar-Powered Wireless Sensor Networks," Journal of The Institute of Electronics, Information and Communication Engineers Transactions on Communications, Vol. 90-B, No. 12, pp. 3373-3382, Jan. 2007.
  12. D. Noh, I. Yoon and H. Shin, "Low-latency geographic routing for asynchronous energy-harvesting WSNs," Journal of Networks, Vol. 3, No. 1, pp. 78-85, Jan. 2008.
  13. D. Petrović, R. C. Shah, K. Ramchandran and J. Rabaey, "Data Funneling: Routing with Aggregation and Compression for Wireless Sensor Networks," Proc. of First IEEE International Workshop on Sensor Network Protocols and Applications, pp. 156-162, May 2003.
  14. T. Srisooksai, K. Keamarungsi, P. Lamsrichan and K. Araki, "Practical data compression in wireless sensor networks: A survey," Journal of Network and Computer Applications, Vol. 35, No. 1, pp. 37-59, Jan. 2012. https://doi.org/10.1016/j.jnca.2011.03.001
  15. C. M. Sadler and M. Martonosi, "Data compression algorithms for energy-constrained devices in delay tolerant networks," Proc. of the 4th international conference on Embedded networked sensor systems, pp. 265-278, Nov. 2006.
  16. S. Madden, Intel Lab Data, Intel Research Lab at Berkeley, [online]. Available: http://db.lcs.mit. edu/ labdata/labdata.html(downloaded 2013, Aug.16).
  17. J. Yi, M. Kang and D. Noh, "SolarCastalia - Solar Energy Harvesting Wireless Sensor Network Simulator," Journal of Distributed Sensor Networks, Vol. 2015, pp. 1-10, May. 2015.
  18. M. Kang, J. Kim, H. Yang and D. K. Noh, "Energy-aware Transmission Power Control for Solar Energy harvesting Wireless sensor system and Its Effects on Network-wide Performance," Proc. of the 34th KIICE Fall Conference, pp. 316, Nov. 2013. (in Korean)
  19. R. Wu, M. Chen, Y. Su and H. J. Siddiqui, "A Novel Location-Based Routing Algorithm or Energy balance in Wireless Sensor Networks," Proc. of the IEEE Communications and Mobile Computing, pp. 568-572, Jan. 2009.