Abstract
As application-driven networks, Wireless Sensor Networks generally require short transmission delay and high data reliability when minimizing energy consumption. Although some approaches have been proposed to tackle this issue, there are few studies that draw attention to the effect of transmission delay and data reliability on minimizing energy consumption. In this paper, we have lots of comprehensive theoretical studies and give the computation models of energy consumption, data transmission delay and data transmission success rate based on IEEE 802.15.4 standard. What’s more, we propose an objective optimization model that minimizing energy consumption while having the constraints of data transmission time and accuracy. The optimization model could dynamically achieve the optimal equilibrium solution by setting the parametric values of optimal equation according to the different requirements of data transmission time and data transmission success rate. The simulation results demonstrate that the validity of computation models. And we find the objective optimization model has a better performance than traditional approaches in the case of dynamically balancing data transmission time and data transmission success rate. Specifically, the proposed optimization model can save up to 41.85% energy consumption compared to Flooding routing algorithm and improve the energy efficient of Reed Solomon code by a factor of 52.6% for the best result.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Change history
24 April 2019
The original version of chapter 18 starting on p. 238 was revised. The name of the second author has been deleted. Instead of Wenwen Liu, Rebecca J. Stones, Gang Wang, and Xiaoguang Liu it should be read as Wenwen Liu, Gang Wang, and Xiaoguang Liu. The original Chapter was corrected. The original version of chapter 40 starting on p. 524 was revised. The grant numbers of the Joint Research Fund in Astronomy were incorrect in the acknowledgement on p. 536. The original chapter was corrected.
References
Ipopt. https://projects.coin-or.org/Ipopt. Accessed Jan 2018
Bolot, J.C.: End-to-end packet delay and loss behavior in the internet. In: Conference Proceedings on Communications Architectures, Protocols and Applications, pp. 289–298 (1993)
Buttyán, L., Gessner, D., Hessler, A., Langendoerfer, P.: Application of wireless sensor networks in critical infrastructure protection: challenges and design options. IEEE Wirel. Commun. 17(5), 44–49 (2010)
Dâmaso, A., Rosa, N., Maciel, P.: Integrated evaluation of reliability and power consumption of wireless sensor networks. Sensors 17(11), 2547 (2017)
Khan, M.K., Kumari, S.: An improved user authentication protocol for healthcare services via wireless medical sensor networks. Int. J. Distrib. Sens. Netw., 1–10 (2014)
Kashani, Z.H., Shiva, M.: Channel coding in multi-hop wireless sensor networks. In: International Conference on ITS Telecommunications Proceedings, pp. 965–968 (2007)
Konstantopoulos, C., Vathis, N., Pantziou, G., Gavalas, D.: Employing mobile elements for delay-constrained data gathering in WSNs. Comput. Netw. 135, 108–131 (2018)
Liu, A., Chen, Z., Xiong, N.N.: An adaptive virtual relaying set scheme for loss-and-delay sensitive WSNs. Inf. Sci. 424, 118–136 (2017)
Liu, J., Shen, H.: A low-cost multi-failure resilient replication scheme for high data availability in cloud storage. In: IEEE International Conference on High Performance Computing (2017)
Liu, Y., Ota, K., Zhang, K., Ma, M., Xiong, N., Liu, A., Long, J.: QTSAC: an energy-efficient MAC protocol for delay minimization in wireless sensor networks. IEEE Access 6(99), 8273–8291 (2018)
Marco, P.D., Park, P., Fischione, C., Johansson, K.H.: Trend: a timely, reliable, energy-efficient and dynamic WSN protocol for control applications. In: IEEE International Conference on Communications, pp. 1–6 (2010)
Mittal, N., Singh, U., Sohi, B.S.: A stable energy efficient clustering protocol for wireless sensor networks. Wirel. Netw. 23(6), 1809–1821 (2017)
Mohemed, R.E., Saleh, A.I., Abdelrazzak, M., Samra, A.S.: Energy-efficient routing protocols for solving energy hole problem in wireless sensor networks. Comput. Netw. 114, 51–66 (2016)
Sankarasubramaniam, Y., Akyildiz, I.F., Mclaughlin, S.W.: Energy efficiency based packet size optimization in wireless sensor networks. In: Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications, pp. 1–8 (2003)
Singh, V.K., Kumar, R., Sahana, S.: To enhance the reliability and energy efficiency of WSN using new clustering approach. In: International Conference on Computing, Communication and Automation, pp. 488–493 (2017)
Torres, C., Glösekötter, P.: Reliable and energy optimized WSN design for a train application. J. Syst. Archit. 57(10), 896–904 (2011)
Tse, R.T., Xiao, Y.: A portable wireless sensor network system for real-time environmental monitoring. In: World of Wireless, Mobile and Multimedia Networks, pp. 1–6 (2016)
Wächter, A., Biegler, L.T.: On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming. Math. Program. 106(1), 25–57 (2006)
Wen, H., Lin, C., Ren, F., Yue, Y., Huang, X.: Retransmission or redundancy: transmission reliability in wireless sensor networks. In: IEEE International Conference on Mobile Adhoc and Sensor Systems, pp. 1–7 (2008)
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Liu, W., Wang, G., Liu, X. (2018). An Energy-Efficient Objective Optimization Model for Dynamic Management of Reliability and Delay in WSNs. In: Vaidya, J., Li, J. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2018. Lecture Notes in Computer Science(), vol 11335. Springer, Cham. https://doi.org/10.1007/978-3-030-05054-2_18
Download citation
DOI: https://doi.org/10.1007/978-3-030-05054-2_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-05053-5
Online ISBN: 978-3-030-05054-2
eBook Packages: Computer ScienceComputer Science (R0)