KSII Transactions on Internet and Information Systems (TIIS)

  • 제3권6호
  • /
  • Pages.612-627
  • /
  • 2009
  • /
  • 1976-7277(pISSN)
  • /
  • 1976-7277(eISSN)
한국인터넷정보학회 (Korean Society for Internet Information)
권호 표지
DOI QR코드

DOI QR Code

Use of Tree Traversal Algorithms for Chain Formation in the PEGASIS Data Gathering Protocol for Wireless Sensor Networks

  • 발행 : 2009.12.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

The high-level contribution of this paper is to illustrate the effectiveness of using graph theory tree traversal algorithms (pre-order, in-order and post-order traversals) to generate the chain of sensor nodes in the classical Power Efficient-Gathering in Sensor Information Systems (PEGASIS) data aggregation protocol for wireless sensor networks. We first construct an undirected minimum-weight spanning tree (ud-MST) on a complete sensor network graph, wherein the weight of each edge is the Euclidean distance between the constituent nodes of the edge. A Breadth-First-Search of the ud-MST, starting with the node located closest to the center of the network, is now conducted to iteratively construct a rooted directed minimum-weight spanning tree (rd-MST). The three tree traversal algorithms are then executed on the rd-MST and the node sequence resulting from each of the traversals is used as the chain of nodes for the PEGASIS protocol. Simulation studies on PEGASIS conducted for both TDMA and CDMA systems illustrate that using the chain of nodes generated from the tree traversal algorithms, the node lifetime can improve as large as by 19%-30% and at the same time, the energy loss per node can be 19%-35% lower than that obtained with the currently used distance-based greedy heuristic.

키워드

참고문헌

  1. W. Heinzelman, A. Chandrakasan and H. Balakarishnan, “Energy-Efficient Communication Protocols for Wireless Microsensor Networks,” Proceedings of the Hawaaian International Conference on Systems Science, Jan. 2000.
  2. S. Lindsey, C. Raghavendra and K. M. Sivalingam, “Data Gathering Algorithms in Sensor Networks using Energy Metrics,” IEEE Transactions on Parallel and Distributed Systems, vol. 13,no. 9, pp. 924-935, Sep. 2002. https://doi.org/10.1109/TPDS.2002.1036066
  3. S. Lindsey, C. Raghavendra and K. M. Sivalingam, “Data Gathering in Sensor Networks using the Energy*Delay Metric,” Proceedings of the 15th International Parallel and Distributed Processing Symposium, pp. 2001-08, Apr. 2001.
  4. R. Osso, “Handbook of Emerging Communications Technologies: The Next Decade,” 1st edition, CRC, ISBN: 0849395941, Aug. 1999.
  5. A. J. Viterbi, “CDMA: Principles of Spread Spectrum Communication,” 1st edition, Prentice Hall, ISBN: 0201633744, Apr. 1995.
  6. N. Meghanathan, “An Algorithm to Determine Energy-aware Connected Dominating Set and Data Gathering Tree for Wireless Sensor Networks,” Proceedings of the 2009 International Conference on Wireless Networks, pp. 608-614, Las Vegas, USA, July 13-16, 2009.
  7. N. Meghanathan, “Grid Block Energy based Data Gathering Algorithm for Lower Energy*Delay and Longer Lifetime in Wireless Sensor Networks,” Proceedings of the ISCA First International Conference on Sensor Networks and Applications, San Francisco, USA, Nov. 2009.
  8. T. H. Cormen, C. E. Leiserson, R. L. Rivest and C. Stein, “Introduction to Algorithms,” 2nd Edition, MIT Press, 2001.
  9. S-M. Jung, Y-J. Han and T-M. Chung, “The Concentric Clustering Scheme for Efficient Energy Consumption in the PEGASIS,” Proceedings of the 9th International Conference on Advanced Communication Technology, vol. 1, pp. 260-265, Gangwon-Do, South Korea, Feb. 2007.
  10. J-E. Lee and K. Kim, “Diamond-Shaped Routing Method for Reliable Data Transmission in Wireless Sensor Networks,” Proceedings of the IEEE International Symposium on Parallel and Distributed Processing with Applications, pp. 799 . 801, Sydney, Australia, Dec. 2008.
  11. N. Tabassum, Q. E. K. M. Mamun and Y. Urano, “COSEN: A Chain Oriented Sensor Network for Efficient Data Collection,” Proceedings of the 3rd International Conference on Information Technology: New Generations, pp. 262-267, Las Vegas, USA, Apr. 2006.
  12. I. Shukla and N. Meghanathan, “Impact of Leader Selection Strategies on the PEGASIS Data Gathering Protocol for Wireless Sensor Networks,” accepted for publication in Ubiquitous Computing and Communication Journal.
  13. H. O. Tan and I. Korpeoglu, “Power Efficient Data Gathering and Aggregation in Wireless Sensor Networks,” SIGMOD Record, vol. 32, no. 4, pp. 66-71, 2003. https://doi.org/10.1145/959060.959072
  14. H. O. Tan, I. Korpeoglu and I. Stojmenovic, “A Distributed and Dynamic Data Gathering Protocol for Sensor Networks,” Proceedings of the 21st IEEE International Conference on Advanced Networking and Applications, pp. 220-227, Niagara Falls, Canada, May 2007.
  15. L. King and N. Meghanathan, “A Weighted-Density Connected Dominating Set Data Gathering Algorithm for Wireless Sensor Networks,” Journal of Computer and Information Science, vol. 2, no. 4, pp. 3-13, Nov. 2009.
  16. T. S. Rappaport, “Wireless Communications: Principles and Practice,” 2nd edition, Prentice Hall, ISBN: 0130422323, Jan. 2002.
  17. N. Meghanathan and A. Farago, “On the Stability of Paths, Steiner Trees and Connected Dominating Sets in Mobile Ad hoc Networks,” Ad hoc Networks, vol. 6, no. 5, pp. 744-769, July 2008. https://doi.org/10.1016/j.adhoc.2007.06.005

피인용 문헌

  1. Adaptive concentric chains protocol for energy efficient routing in wireless sensor networks vol.12, pp.7, 2012, https://doi.org/10.1002/wcm.1001
  2. Decentralized and energy‐balanced algorithms for maintaining temporal full‐coverage in mobile WSNs vol.12, pp.5, 2009, https://doi.org/10.1002/wcm.977
  3. A Comprehensive Review and Performance Analysis of Data Gathering Algorithms for Wireless Sensor Networks : vol.4, pp.2, 2009, https://doi.org/10.4018/jitn.2012040101
  4. A Comprehensive Review and Performance Analysis of Data Gathering Algorithms for Wireless Sensor Networks : vol.4, pp.2, 2009, https://doi.org/10.4018/jitn.2012040101
  5. Robust and Energy-Efficient Data Gathering in Wireless Sensor Network vol.10, pp.10, 2009, https://doi.org/10.1155/2014/960242
  6. A Segment-based Tree Traversal Algorithm for Enhancing Data Gathering in Wireless Sensor Networks vol.20, pp.None, 2009, https://doi.org/10.37394/23205.2021.20.8
  7. A Segment-based Tree Traversal Algorithm for Enhancing Data Gathering in Wireless Sensor Networks vol.20, pp.None, 2009, https://doi.org/10.37394/23205.2021.20.8