In recent days, wireless sensor networks (WSN) plays a major role in the real time applications like military battlefield surveillance, industrial process monitoring, machine health monitoring and so on. In WSN, selecting the cluster head (CH) is the challenging task. CH selection is done by considering parameters of single layer only. In cross layer protocol more than one layers are considered for inter related parameters such as integration of MAC/physical layer and integration routing/MAC/physical layers. The main drawback of layer-based approach is not considering the effect on improvement of particular layer parameter to other layer parameters. In this paper, new cross layer technique for energy efficient module is designed to address the energy efficiency issues, which is common to all layers and used to optimize the energy from one layer parameter by others. Nowadays everything is possible with the help of Internet, so sharing the information between WSN and TCP through the energy efficient cross layer can be done. It is done with transport layer to enhance the application filed to be reliably connected to the web. In this paper, dynamically adapted sleep scheduling mechanism is used with residual energy of each node. Virtual end-to-end packet rate selection and congestion control feedback mechanism are considered for end to end delay. This reduces the packet loss with the support of data-rate adaptation technique.
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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.
Farooq, M. O., Dogar, A. B., & Shah, G. A. (2010). MR-LEACH: Multi-hop routing with low energy adaptive clustering hierarchy. In Proceedings—4th international conference on sensor technologies and applications, SENSORCOMM 2010 (pp. 262–268).
Nazir, B., & Hasbullah, H. (2010). Energy efficient multi hierarchy clustering protocol for wireless sensor network (EMHC). In IEEE—International conference on intelligence and information technology (ICIIT 2010) (pp. 609–614).
Ramesh, K., & Somasundaram, K. (2011). A comparative study of cluster head selection algorithms in wireless sensor networks. International Journal of Computer Science & Engineering Survey (IJCSES),2(4), 153–164.
Loh, P. K. K., & Pan, Y. (2009). An energy-aware clustering approach for wireless sensor networks. International Journal of Communications, Network and System Sciences,02(May), 131–141.
Liu, M., Cao, J., Chen, G., & Wang, X. (2009). An energy-aware routing protocol in wireless sensor networks. Sensors,9(1), 445–462.
Abdulla, A. E. A. A., Nishiyama, H., Yang, J., Ansari, N., & Kato, N. (2012). HYMN: A novel hybrid multi-hop routing algorithm to improve the longevity of WSNs. IEEE Transactions on Wireless Communications,11(7), 2531–2541.
Kozat, U. C., Koutsopoulos, I., & Tassiulas, L. (2004). A framework for cross-layer design of energy-efficient communication with QoS provisioning in multi-hop wireless networks. In INFOCOM 2004. Twenty-Third Annual Joint Conference of the IEEE Computer and Communications Societies, 2004 (Vol. 2, pp. 1446–1456).
Cui, S., Madan, R., Goldsmith, A. J., & Lall, S. (2007). Cross-layer energy and delay optimization in small-scale sensor networks. IEEE Transactions on Wireless Communications,6(10), 3688–3699.
Han, G., Dong, Y., Guo, H., Shu, L., & Wu, D. (2015). Cross-layer optimized routing in wireless sensor networks with duty cycle and energy harvesting. Wireless Communications and Mobile Computing, 15(16), 1957–1981.
Boyd, S., & Vandenberge, L. (2003). Convex Optimization. Cambridge: Cambridge University Press.
Ramesh, K., & Somasundaram, K. (2016). Wireless sensor network lifetime enhancement using modified clustering and scheduling algorithm. Circuits and Systems,7, 1787–1793.
Ramesh, K., Saritha, S., & Somasundaram, K. (2016). Enhancement of network lifetime by improving the LEACH protocol for large scale WSN. Indian Journal of Science and Technology,9(16), 1–6.
Chandravathi, C., & Mahadevan, K. (2016). Low duty-cycle based optimized sleep-schedule (LDCOS) cross layer design for WSN. Asian Journal of Research in Social Sciences and Humanities,6(10), 1910–1919.
Chandravathi, C., & Mahadevan, K. (2017). Low duty-cycle based optimized sleep-schedule and active-neighbours based route (LDOSAR) cross layer design for WSN. Advances in Natural and Applied Sciences.,11(6), 536–543.
Zhang, W., Wei, X., Han, G., & Tan, X. (2018). An energy-efficient ring cross-layer optimization algorithm for wireless sensor networks. IEEE Access,6, 16588–16598.
Nazeer, M., & Murthy, G. R. (2018). Cognitive cross-layer, energy efficient MAC protocol in mobile wireless sensor networks. International Journal of Engineering and Advanced Technology,8(2), 22–28.
Tan, J., Liu, A., Zhao, M., et al. (2018). Cross-layer design for reducing delay and maximizing lifetime in industrial wireless sensor networks. Journal of Wireless Networking and Communications. https://doi.org/10.1186/s13638-018-1057-x.
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Chandravathi, C., Mahadevan, K. Web Based Cross Layer Optimization Technique for Energy Efficient WSN. Wireless Pers Commun 117, 2781–2792 (2021). https://doi.org/10.1007/s11277-020-07047-1
- Cross layer optimization
- Wireless networks
- Mac layer