Abstract
Route estimation process often involves significant message exchanges among wireless sensor nodes while selecting the least cost path. Nodes along this path handle more traffic that leads to death of battery powered nodes and shortening network life. Thus, routing mechanisms for wireless sensor network (WSN) must be traffic aware and at the same time, the alternate route(s) incur less delay overhead. This paper considers a query-driven application scenario in WSN where the sink diffuses query over the network to fetch information. A novel field-based routing (FBR) mechanism is proposed that inherits the physical properties of Coulomb’s law for point charges in free space. It defines a distance field parameter corresponding to each sensor node with respect to the sink. The sink being the negatively charged particle the packets from sensor nodes (positively charged particle) flow towards the field generating sink. The algorithm considers energy depletion rate for estimating the virtual potential field at nodes so as to avoid the nodes having less remaining energy. Further, the gradient updation is based on the local information which results in less message complexity (O(n)) and low computation overhead, which is comparable to the best available approaches. NS-2 based simulation demonstrates a significant enhancement in network lifetime, increased packet reception ratio and reduction in energy dissipation rate making the FBR mechanism suitable for WSN.















Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Al-Karaki, J. N., & Kamal, A. E. (2004). Routing techniques in wireless sensor networks: A survey. IEEE Wireless Communications, 11(6), 628.
Ammari, H. (2009). Challenges and opportunities of connected k-covered wireless sensor networks. Berlin: Springer.
Basu, A., Lin, A., & Ramanathan, S. (2003). Routing using potentials: A dynamic traffic-aware routing algorithm. In Proceedings of the 2003 conference on applications, technologies, architectures, and protocols for computer communications, SIGCOMM 03 (pp. 37–48). New York, NY: ACM.
Chang, W.-R., Lin, H.-T., & Cheng, Z.-Z. (2008). CODA: A continuous object detection and tracking algorithm for wireless ad hoc sensor networks. In 5th IEEE consumer communications and networking conference, 2008. CCNC 2008 (pp. 168–174). IEEE.
Chuang, C. L., Wang, Y. C., Lee, C. H., Liu, M. Y., Hsiao, Y. T., & Jiang, J. A. (2010). An adaptive routing algorithm over packet switching networks for operation monitoring of power transmission systems. IEEE Transactions on Power Delivery, 25(2), 882890.
Demirkol, I., Ersoy, C., & Alagoz, F. (2006). MAC protocols for wireless sensor networks: A survey. IEEE Communications Magazine, 44(4), 115121.
Ding, W., Tang, L., & Ji, S. (2016). Optimizing routing based on congestion control for wireless sensor networks. Wireless Networks, 22(3), 915925.
Falconer, I. (2004). Charles Augustin Coulomb and the fundamental law of electrostatics. Metrologia, 41(5), S107.
Gehrke, J., & Madden, S. (2004). Query processing in sensor networks. IEEE Pervasive Computing, 3(1), 4655.
Han, K.-H., Ko, Y.-B., & Kim, J.-H. (2004). A novel gradient approach for efficient data dissemination in wireless sensor networks. In IEEE 60th vehicular technology conference, 2004. VTC2004-Fall (Vol. 4, pp. 2979–2983).
He, T., Stankovic, J. A., Lu, C., & Abdelzaher, T. (2003). SPEED: A stateless protocol for real-time communication in sensor networks. In Proceedings of 23rd international conference on distributed computing systems, 2003 (pp. 46–55). IEEE.
Heinzelman, W. R., Kulik, J., & Balakrishnan, H. (1999). Adaptive protocols for information dissemination in wireless sensor networks. In Proceedings of the 5th annual ACM/IEEE international conference on mobile computing and networking (pp. 174–185). ACM.
Huang, P., Chen, H., Xing, G., & Tan, Y. (2009). SGF: A state-free gradient-based forwarding protocol for wireless sensor networks. ACM Transactions on Sensor Networks (TOSN), 5(2), 14.
Hu, F., & Cao, X. (2010). Wireless sensor networks: Principles and practice. Boca Raton: CRC Press.
Hu, X., Li, Y., & Xu, H. (2017). Multi-mode clustering model for hierarchical wireless sensor networks. Physica A: Statistical Mechanics and its Applications, 469(C), 665–675.
Hull, B., Jamieson, K., & Balakrishnan, H. (2004). Mitigating congestion in wireless sensor networks. In Proceedings of the 2nd international conference on Embedded networked sensor systems (pp. 134–147). ACM.
Illingworth, V. (1991). The Penguin dictionary of physics (2nd ed.). London: Penguin Books. (First published 1977T.p. verso).
Intanagonwiwat, C., Govindan, R., & Estrin, D. (2000). Directed diffusion: A scalable and robust communication paradigm for sensor networks. In Proceedings of the 6th annual international conference on mobile computing and networking, MobiCom 00 (pp. 56–67). New York, NY: ACM.
Jangir, P., Gautam, P., Juneja, D., & Dhiman, M. (2017). Recent developments in routing protocols for wireless sensor network. Journal of Network Communications and Emerging Technologies (JNCET), 7(3). www.jncet.org.
Kumar, R., Crepaldi, R., Rowaihy, H., Harris, A. F, I. I. I., Cao, G., Zorzi, M., et al. (2008). Mitigating performance degradation in congested sensor networks. IEEE Transactions on Mobile Computing, 7(6), 682697.
Liu, S., Du, J., Liu, H., Li, R., Yang, X., & Sha, K. (2017). Energy-efficient algorithm to construct the information potential field in WSNs. IEEE Sensors Journal, 17(12), 3822–3831.
Liu, H., Zhang, Z.-L., Srivastava, J., & Firoiu, V. (2007). Pwave: A multi-source multi-sink anycast routing framework for wireless sensor networks. In International conference on research in networking (pp. 179–190). Springer.
Palani, U., Alamelumangai, V., & Nachiappan, A. (2016). Hybrid routing and load balancing protocol for wireless sensor network. Wireless Networks, 22(8), 26592666.
Popa, L., Raiciu, C., Stoica, I., & Rosenblum, D. S. (2006). Reducing congestion effects in wireless networks by multipath routing. In Proceedings of the 2006 14th IEEE international conference on network protocols, 2006. ICNP 06 (pp. 96–105). IEEE.
Qiu, Y., Li, S., Li, Z., Zhang, Y., & Yang, Z. (2017). Multi-gradient routing protocol for wireless sensor networks. China Communications, 14(3), 118129.
Ren, F., Zhang, J., He, T., Lin, C., & Ren, S. K. D. (2011). EBRP: Energy-balanced routing protocol for data gathering in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 22(12), 21082125.
Russell, S. J., Norvig, P., Canny, J. F., Malik, J. M., & Edwards, D. D. (2003). Artificial intelligence: A modern approach (Vol. 2). Upper Saddle River: Prentice Hall.
Sankarasubramaniam, Y., Akan, O. B., & Akyildiz, I. F. (2003). ESRT: Event-to-sink reliable transport in wireless sensor networks. In Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing (pp. 177–188). ACM.
Sarkar, T. K., Ji, Z., Kim, K., Medouri, A., & Salazar-Palma, M. (2003). A survey of various propagation models for mobile communication. IEEE Antennas and Propagation Magazine, 45(3), 5182.
Savvides, A., Han, C.-C., & Strivastava, M. B. (2001). Dynamic fine-grained localization in ad-hoc networks of sensors. In Proceedings of the 7th annual international conference on mobile computing and networking, MobiCom 01 (pp. 166–179). New York, NY: ACM.
Stephan, O., & Ivan, S. (2006). Design guidelines for maximizing lifetime and avoiding energy holes in sensor networks with uniform distribution and uniform reporting. In INFOCOM (pp. 1–12).
Wan, C.-Y., Eisenman, S. B., Campbell, A. T., & Crowcroft, J. (2007). Overload traffic management for sensor networks. ACM Transactions on Sensor Networks (TOSN), 3(4), 18.
Wang, Y., Vuran, M. C., & Goddard, S. (2012). Cross-layer analysis of the end-to-end delay distribution in wireless sensor networks. IEEE/ACM Transactions on Networking, 20(1), 305318.
Woo, A., Tong, T., & Culler, D. (2003). Taming the underlying challenges of reliable multihop routing in sensor networks. In Proceedings of the 1st international conference on embedded networked sensor systems (pp. 14–27). ACM.
Ya, X., John, H., & Deborah, E. (2001). Geography-informed energy conservation for ad hoc routing. In Proceedings of the 7th annual international conference on mobile computing and networking (pp. 70–84). ACM.
Yadav, S., & Yadav, R. S. (2016). A review on energy efficient protocols in wireless sensor networks. Wireless Networks, 22(1), 335350.
Yoo, H., Shim, M., Kim, D., & Kim, K. H. (2010). Global: A gradient-based routing protocol for load-balancing in large-scale wireless sensor networks with multiple sinks. In IEEE symposium on computers and communications (ISCC), 2010 (pp. 556–562).
Zhang, J., Ren, F., Gao, S., Yang, H., & Lin, C. (2015). Dynamic routing for data integrity and delay differentiated services in wireless sensor networks. IEEE Transactions on Mobile Computing, 14(2), 328343.
Acknowledgements
The authors would like to thank the reviewers for their valuable suggestions.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Anand, V., Jain, A., Pattanaik, K.K. et al. Traffic aware field-based routing for wireless sensor networks. Telecommun Syst 71, 475–489 (2019). https://doi.org/10.1007/s11235-018-0519-0
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11235-018-0519-0