USN Channel Establishment Algorithm for Sensor Authentication and Anti-collision

센서 인증과 충돌 방지를 위한 USN 채널 확립 알고리즘

  • Rhee, Kang-Hyeon (Dept. of Electronic Eng., College of Elec-Info Eng., Chosun University)
  • 이강현 (조선대학교 전자정보공과대학 전자공학과)
  • Published : 2007.05.25

Abstract

Advances in electronic and computer technologies have paved the way for the proliferation of WSN(wireless sensor networks). Accordingly, necessity of anti-collusion and authentication technology is increasing on the sensor network system. Some of the algorithm developed for the anti-collision sensor network can be easily adopted to wireless sensor network platforms and in the same time they can meet the requirements for sensor networks like: simple parallel distributed computation, distributed storage, data robustness and auto-classification of sensor readings. To achieve security in wireless sensor networks, it is important to be able to establish safely channel among sensor nodes. In this paper, we proposed the USN(Ubiquitous Sensor Network) channel establishment algorithm for sensor's authentication and anti-collision. Two different data aggregation architectures will be presented, with algorithms which use wavelet filter to establish channels among sensor nodes and BIBD (Balanced Incomplete Block Design) which use anti-collision methods of the sensors. As a result, the proposed algorithm based on BIBD and wavelet filter was made for 98% collision detection rate on the ideal environment.

전자와 컴퓨터 기술의 발전은 무선 센서 네트워크 증대의 토대를 마련하였다. 이에 따라, 센서 네트워크상의 충돌 방지와 인증 기술의 필요성이 증대되어 지고 있다. 센서 네트워크의 충돌 방지를 위해 개발될 알고리즘은 무선 센서 네트워크 플랫폼 상에 쉽게 적용될 수 있으며 또한 동시에 분산 연산, 분산 저장, 데이터 강인성, 센싱된 데이터를 자동 분류할 수 있어야한다. 그리고 무선 센서 네트워크에서 보안을 유지하기 위하여 여러 센서 간에 안전하게 채널을 확립할 수 있어야한다. 본 논문 우리는 센서의 인증과 충돌 방지를 위하여 유비쿼터스 센서 네트워크 채널 확립 알고리즘을 제안하였다. 본 논문에서는 두 가지 다른 형태의 구조를 제안하였으며, 각 구조에서는 센서 노드 사이에서 채널을 확립하기위하여 웨이블렛 필터를 사용한 알고리즘과 센서의 충돌 방지를 위하여 BIBD(Balanced Incomplete Block Design) 코드를 사용하였다. 결과적으로, BIBD와 웨이블렛 필터 기반으로 제안된 알고리즘은 이상적인 환경에서 98% 충돌 검출율을 가졌다.

Keywords

References

  1. Kang-Hyeon RHEE, 'Detection of Colluded Multimedia Fingerprint using LDPC and BIBD,'IEEK Journal CI, pp. 68-75, 2006. 9
  2. W. Jia and J. Wang, 'Analysis of connectivity for sensor networks using geometrical probability,' IEE Proc.-Commun. Vol 153, No. 2, April 2006 https://doi.org/10.1049/ip-com:20045176
  3. A. Kulakov, D. Davcev and G. Trajkovski, 'Application of Wavelet Neural-Networks in Wireless Sensor Networks,' IEEE Proc. of the Sixth International Conf. on Sofware Eng., 2005 https://doi.org/10.1109/SNPD-SAWN.2005.23
  4. Wenliang Du, Jing Deng, Yunghsiang S. Han and Pramod K. Varshney, 'A Key Predistribution Scheme for Sensor Networks Using Deployment Knowledge,' IEEE Trans. on dependable and secure computing, Vol. 3, No. 1, January 2006 https://doi.org/10.1109/TDSC.2006.2
  5. M. Gastpar and M. Vetterli, 'Source-channel communication in sensor networks,' Proc. 2nd Int. Workshop on Information Processing in Sensor Networks (IPSN'03), vol. 219, pp. 162-177, 2003 https://doi.org/10.1007/3-540-36978-3_11
  6. S. S. Pradhan, J. Kusuma, and K. Ramchandran, 'Distributed compression in a dense microsensor network,' IEEE Signal Process. Mag., vol. 19, no. 2, pp. 51-60, Mar. 2002 https://doi.org/10.1109/79.985684
  7. A. Scaglione and S. D. Servetto, 'On the interdependence of routing and data compression in multi-hop sensor networks,' in Proc. ACM MobiCom, Atlanta, GA, Sep. 2002, pp. 140-147 https://doi.org/10.1145/570645.570663
  8. 'Power, spatio-temporal bandwidth, and distortion in large sensor networks,' IEEE J. Sel. Areas Commun., vol. 23, no. 4, pp. 745-754, Apr. 2005 https://doi.org/10.1109/JSAC.2005.843542
  9. L. Zhong, R. Shah, C. Guo, and J. Rabaey, 'An ultra-lowpower and distributed access protocol for broadband wireless sensor networks,' presented at the Networld + Interop: IEEE Broadband Wireless Summit, Las Vegas, NV, May 2001
  10. A. Scaglione and S. D. Servetto, 'On the interdependence of routing and data compression in multi-hop sensor networks,' in Proc. ACM MobiCom, Atlanta, GA, Sep. 2002, pp. 140-147 https://doi.org/10.1145/570645.570663
  11. Mehmet C. Vuran and Ian F. Akyildiz, 'Spatial Correlation-Based Collaborative Medium Access Control in Wireless Sensor Networks,' IEEE/ ACM Transactions on networksing, Vol 14, No. 2, APRIL 2006 https://doi.org/10.1109/TNET.2006.872544
  12. S. Bandyopadhyay and E. J. Coyle, 'Spatio-temporal sampling rates and energy efficiency in wireless sensor networks,' in Proc. IEEE INFOCOM, Mar. 2004, vol. 3, pp. 1728-1739 https://doi.org/10.1109/INFCOM.2004.1354584
  13. W. Ye, J. Heidemann, and D. Estrin, 'Medium access control with coordinated adaptive sleeping for wireless sensor networks,' IEEE/ACM Trans. Netw., vol. 12, no. 3, pp. 493-506, Jun. 2004 https://doi.org/10.1109/TNET.2004.828953
  14. T. van Dam and K. Langendoen, 'An adaptive energy-efficient MAC protocol for wireless sensor networks,' in Proc. ACMSenSys 2003, Los Angeles, CA, Nov. 2003, pp. 171-180 https://doi.org/10.1145/958491.958512
  15. K. A. Arisha, M. A. Youssef, and M. Y. Younis, 'Energy-aware TDMA-based MAC for sensor networks,' Comput. Netw. J. (Elsevier), vol. 43, no. 5, pp. 539-694, Dec. 2003 https://doi.org/10.1016/S1389-1286(03)00289-5
  16. V. Rajendran, K. Obraczka, and J. J. Garcia-Luna-Aceves, 'Energy-efficient, collisionfree medium access control for wireless sensor networks,' in Proc. ACM SenSys 2003, Los Angeles, CA, Nov. 2003, pp. 181-192