Data-Centric Routing Mechanism Using Hash-Value in Wireless Sensor Network
ABSTRACT
Traditional routing protocols as TCP/IP can not be directly used in WSN, so special data-centric routing protocols must be established. The raised data-centric routing protocols can not identify the sensor nodes, because many nodes work under a monitoring task, and the source of data is not so important some times. The sensor node in the network can not judge weather data is come from the some sink node. What’s more, the traditional method use IP to identify sensors in Internet is not suitable for WSN. In this paper, we propose a new naming scheme to identify sensor nodes, which based on a description of sensor node, the description of a sensor node is hashed to a hash value to identify this sensor. The different description generates different identifier. Different from IP schema, this identifier is something about the information of the sensor node. In the above naming scheme, we propose a new data-centric routing mechanism. Finally, the simulation of the routing mechanism is carried out on MATLAB. The result shows our routing mechanism’s predominate increase when network size increase.
Traditional routing protocols as TCP/IP can not be directly used in WSN, so special data-centric routing protocols must be established. The raised data-centric routing protocols can not identify the sensor nodes, because many nodes work under a monitoring task, and the source of data is not so important some times. The sensor node in the network can not judge weather data is come from the some sink node. What’s more, the traditional method use IP to identify sensors in Internet is not suitable for WSN. In this paper, we propose a new naming scheme to identify sensor nodes, which based on a description of sensor node, the description of a sensor node is hashed to a hash value to identify this sensor. The different description generates different identifier. Different from IP schema, this identifier is something about the information of the sensor node. In the above naming scheme, we propose a new data-centric routing mechanism. Finally, the simulation of the routing mechanism is carried out on MATLAB. The result shows our routing mechanism’s predominate increase when network size increase.
Cite this paper
nullX. Zhao, K. Mao, S. Cai and Q. Chen, "Data-Centric Routing Mechanism Using Hash-Value in Wireless Sensor Network," Wireless Sensor Network, Vol. 2 No. 9, 2010, pp. 710-717. doi: 10.4236/wsn.2010.29086.
nullX. Zhao, K. Mao, S. Cai and Q. Chen, "Data-Centric Routing Mechanism Using Hash-Value in Wireless Sensor Network," Wireless Sensor Network, Vol. 2 No. 9, 2010, pp. 710-717. doi: 10.4236/wsn.2010.29086.
References
[1] D. Chen, Z. W. Zheng and J. J. Li, “Research on Wireless Sensor Network,” Computer Measurement and Control, Vol. 12, No. 8, 2004, pp. 701-704. [2] L. M. Sun, “Wireless Sensor Network,” Tsinghua University Press, Beijing, 2005. [3] W. Ye, J. Heidemann and D. Estrin, “An Energy-Efficient MAC Protocol for Wireless Sensor Networks,” Proceedings of IEEE Infocom, New York, 2002, pp. 1567-1576. [4] W. Ye, J. Heidemann and D. Estrin, “Medium Access Control with Coordinated Adaptive Sleeping for Wireless Sensor Networks,” IEEE/ACM Transactions on Networking, Vol. 12, No. 3, December 2004, pp. 493-506. [5] Y. Li, W. Ye and J. Heidemann, “Energy and Latency Control in Low Duty Cycle MAC Protocols,” Proceedings of the IEEE Wireless Communications and Networking Conference, New Orleans, March 2005, pp. 676-682. [6] J. Kulik, W. R. Heinzelmann and H. Balakrishnan, “Adap- tive Protocols for Information Dissemination Information in Wireless Sensor Networks,” Proceedings of the 5th ADM/IEEE Mobicom Conference, Seattle, 1999, pp. 174-185. [7] C. Intanagonwiwat, R. Govindan and D. Estrin, “Directed Diffusion: A Scalable and Robust Communication Paradigm for Sensor Networks,” Proceedings of the 6th annual international conference on Mobile computing and networking, Boston, 2000, pp.56-67. [8] A. Boulis, S. Ganeriwal, M. B. Srivastava, “Aggregation in Sensor Networks: an Energy-accuracy Trade-off,” Sensor Network Protocols and Applications, Vol. 1, No. 2, September 2003, pp. 317-331. [9] S. Ratnasamy, B. Karp, L.Yin, F. Yu, D. Estrin, R. Govindan and S. Shenker, “GHT: A Geographic Hash Table for Data-Centric Storage,” Proceedings of the First ACM International Workshop on Wireless Sensor Networks and Applications, Atlanta, September 2002. [10] S. Shenke, S. Ratnasamy, B. Karp, R. Govindan and D. Estrin, “Data-Centric Storage in Sensornets,” ACM SIGCOMM Computer Communication Review, Vol. 33, No. 1, January 2003, pp.137-142.
[1] D. Chen, Z. W. Zheng and J. J. Li, “Research on Wireless Sensor Network,” Computer Measurement and Control, Vol. 12, No. 8, 2004, pp. 701-704. [2] L. M. Sun, “Wireless Sensor Network,” Tsinghua University Press, Beijing, 2005. [3] W. Ye, J. Heidemann and D. Estrin, “An Energy-Efficient MAC Protocol for Wireless Sensor Networks,” Proceedings of IEEE Infocom, New York, 2002, pp. 1567-1576. [4] W. Ye, J. Heidemann and D. Estrin, “Medium Access Control with Coordinated Adaptive Sleeping for Wireless Sensor Networks,” IEEE/ACM Transactions on Networking, Vol. 12, No. 3, December 2004, pp. 493-506. [5] Y. Li, W. Ye and J. Heidemann, “Energy and Latency Control in Low Duty Cycle MAC Protocols,” Proceedings of the IEEE Wireless Communications and Networking Conference, New Orleans, March 2005, pp. 676-682. [6] J. Kulik, W. R. Heinzelmann and H. Balakrishnan, “Adap- tive Protocols for Information Dissemination Information in Wireless Sensor Networks,” Proceedings of the 5th ADM/IEEE Mobicom Conference, Seattle, 1999, pp. 174-185. [7] C. Intanagonwiwat, R. Govindan and D. Estrin, “Directed Diffusion: A Scalable and Robust Communication Paradigm for Sensor Networks,” Proceedings of the 6th annual international conference on Mobile computing and networking, Boston, 2000, pp.56-67. [8] A. Boulis, S. Ganeriwal, M. B. Srivastava, “Aggregation in Sensor Networks: an Energy-accuracy Trade-off,” Sensor Network Protocols and Applications, Vol. 1, No. 2, September 2003, pp. 317-331. [9] S. Ratnasamy, B. Karp, L.Yin, F. Yu, D. Estrin, R. Govindan and S. Shenker, “GHT: A Geographic Hash Table for Data-Centric Storage,” Proceedings of the First ACM International Workshop on Wireless Sensor Networks and Applications, Atlanta, September 2002. [10] S. Shenke, S. Ratnasamy, B. Karp, R. Govindan and D. Estrin, “Data-Centric Storage in Sensornets,” ACM SIGCOMM Computer Communication Review, Vol. 33, No. 1, January 2003, pp.137-142.