Abstract
Wireless sensor networks are data centric networks, which transmit gathered data to sink nodes. Considering energy constraints, how to make full use of the limited energy to reliably transmit data as much as possible becomes a main research region in sensor networks. In this paper, we focus on energy consumption and reliability of different communication modes. Single hop communication mode is simple and easy to implement, but the distant cluster members, especially those on the edge of the networks, need to enlarge transmission power. On the other hand multi-hop communication is not constrained by the communication distance. The relay communication mode guarantees data transmission to a remote cluster head. Considering of the reliability and energy consumption, we propose a voting based clustering communication algorithm. And the optimal cluster number is calculated based on the geometry locations. Finally, several experiments have been done to validate the analysis in this paper.
Similar content being viewed by others
References
Golrezaei, N., Molisch, A. F., Dimakis, A. G., et al. (2013). Femtocaching and device-to-device collaboration: A new architecture for wireless video distribution. IEEE Commununication Magazine, 51(4), 142–149.
Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(4), 660–670.
Intanagonwiwat, C., Govindan, R., & Estrin, D. (2000). Directed diffusion: A scalable and robust communication paradigm for sensor networks. In Proceedings of the sixth ACM international conference on mobile computing and networking (pp. 56–67).
Rodoplu, V., & Meng, T. H. (1999). Minimum energy mobile wireless networks. IEEE Journal on Selected Areas in Communications, 17(8), 1333–1344.
Zhang, G., Yang, K., & Hu, Q. (2012). Bargaining game theoretic framework for stimulating cooperation in wireless cooperative multicast networks. IEEE Communications Letters, 16(2), 208–211.
Liu, M., Liu, B. & Wen, Y. (2013). An efficient data evacuation strategy for sensor networks in postdisaster applications. International Journal of Distributed Sensor Networks, 9(1), 1–12.
Liu, M., Gong, H., Wen, Y., Chen, G. & Cao, J. (2011). The last minute: Efficient data evacuation strategy for sensor networks in post-disaster applications. In IEEE proceedings of the INFOCOM (pp. 291–295).
Golrezaei, N., Molisch, A. F., Dimakis, A. G., et al. (2013). Femtocaching and device-to-device collaboration: A new architecture for wireless video distribution. IEEE Communications, 51(4), 142–149.
Yu, C., Doppler, K., Ribeiro, C. B., & Tirkkonen, O. (2011). Resource sharing optimization for device-to-device communication underlaying cellular networks. IEEE Transactions on Wireless Communication, 10(8), 2752–2763.
Wang, C., Hussain, S., & Bertino, E. (2016). Dictionary based secure provenance compression for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 27(2), 405–418.
Kumari, S., Khan, M. K., & Atiquzzaman, M. (2015). User authentication schemes for wireless sensor networks: A review. Ad Hoc Networks, 27, 159–194.
Ghasemigol, M., Ghaemi-Bafghi, A., & Sadoghi-Yazdi, H. (2015). Anomaly detection and foresight response strategy for wireless sensor networks. Wireless Networks, 21(5), 1425–1442.
Cai, J., & Gu, M. (2015). Performance analysis for star topology wireless sensor networks based on IEEE 802.15.4. Journal of tinghua university, 55(5), 565–571.
Dinh, T. N., Nguyen, N. P., & Thai, M. T. (2013). An adaptive approximation algorithm for community detection in dynamic scale-free networks. In Proceedings of the 32nd IEEE INFOCOM (pp. 55–59).
Gong, M.-G., Zhang, L.-J., Ma, J.-J., & Jiao, L.-C. (2012). Community detection in dynamic social networks based on multiobjective immune algorithm. Journal of Computer Science and technology, 27(3), 455–467.
Mohamed, M. M. A., Khokhar, A. A., & Trajcevski, G. (2013). Voronoi trees for hierarchical in-network data and space abstractions in wireless sensor netowrks. In Proceedings of the 16th ACM international conference on modeling, analysis & simulation of wireless and mobile systems (pp. 207–210).
Mohamed, M. M. A., Khokhar, A., & Trajcevski, G. (2014). Energy eficient resource distribution for mobile wireless sensor networks. In Proceedings of the 15th IEEE international conference on mobile data management (pp. 49–54).
Lindsey, S., Raghavendra, C., & Sivalingam, K. M. (2002). Data gathering algorithms in sensor networks using energy metric. IEEE Transactions on Parallel and Distributed Systems, 13(9), 924–935.
Manjeshwar, A., & Agrawal, D. P. (2001). TEEN: A routing protocol for enhanced efficiency in wireless sensor networks. In Proceedings of the 15th international parallel and distributed processing symposium (pp. 2009–2015).
Manjeshwar, A., & Agrawal, D. P. (2002). APTEEN: A hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks. In Proceedings of the 16th international parallel and distributed processing symposium (pp. 195–202).
Younis, O., & Fahmy, S. (2004). HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing, 3(4), 366–379.
Silveira, D. et al. (2014). Reference frame context-adaptive variable-length coder: A real-time hardware-friendly approach for lossless external memory bandwidth reduction in current video coding systems. Journal of Real-Time Image Processing, 10(3), 1–17.
Chikkerur, S., Sundaram, V., Reisslein, M., & Karam, L. J. (2011). Objective video quality assessment methods: A classification, review, and performance comparison. IEEE Transactions on Broadcasting, 57(2), 165–182.
Shoaib, U. R., Rehman, Obaid, Akbar, Zeeshan, & Iqbal, Javed. (2012). Performance evaluation o f Bluetooth and Zigbee using monte carlo simulation. International Journal of Computer Science Issues, 9(1), 12–19.
Pudlewski, S., & Melodia, T. (2013). A tutorial on encoding and wireless transmission of compressively sampled videos. IEEE Communications Surveys and Tutorials, 15(2), 754–767.
Pudlewski, S., & Melodia, T. (2010). A distortion-minimizing rate controller for wireless multimediasensor networks. Computer Communications, 33(12), 1380–1390.
Song, Y., Wang, B., Shi, Z., Pattipati, K., & Gupta, S. (2014). Distributed algorithms for energy-efficient even self-deployment in mobile sensor networks. IEEE Transactions on Mobile Computing, 13(5), 1035–1047.
Fischer, C., & Gellersen, H. (2010). Location and navigation support for emergency responders. IEEE Pervasive Computing, 9(1), 38–47.
Wang, J., Li, Z., Li, M., Liu, Y., & Yang, Z. (2013). Sensor network navigation without locations. IEEE Transactions on Parallel and Distributed Systems, 24(7), 1436–1446.
Bocca, M., Kaltiokallio, O., Patwari, N., & Venkatasubramanian, S. (2014). Multiple target tracking with RF sensor networks. IEEE Transactions on Mobile Computing, 13(8), 1787–1800.
Acknowledgments
This work was supported by the Fundamental Research Funds for the Central Universities (2015XKMS087).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Xiao, S., Xu, Z. Reliable and Energy Efficient Communication Algorithm in Hierarchical Wireless Sensor Networks. Wireless Pers Commun 95, 1891–1909 (2017). https://doi.org/10.1007/s11277-016-3705-y
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11277-016-3705-y