Abstract
Industrial wireless sensor network is an important technology for precise monitoring in industrial systems. Sensors are deployed densely in various industry applications, where the high density of sensors results in large amounts of redundant data. Therefore, information aggregation is used to avoid forwarding redundant data and thus save limited resources. However, when decreasing transmission cost, existing aggregation schemes lead to low data accuracy and long delivery latency. In this paper, we propose an energy-efficient data collection solution using lossless compression for industrial wireless sensor networks, namely ECL, aiming for high energy efficiency and high information entropy. According to three aggregation rules, aggregation regions are constructed in a distributed way based on a preset threshold of sensing duplication rate. Therefore, the aggregated data are probably similar, and ECL has the original entropy through removing only the redundant data. Experiment results show that compared with other schemes, ECL keeps about 38% and 48% higher data accuracy and 12% and 25% shorter maximum end-to-end delay than EEUC and HEER, respectively, with a similar lifetime.
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References
Gungor, V.C., Hancke, G.P.: Industrial wireless sensor networks: challenges, design principles, and technical approaches. IEEE Trans. Industr. Electron. 56(10), 4258–4265 (2009)
Tang, X., Juhua, P., Gao, Y., Xiong, Z., Weng, Y.: Energy-efficient multicast routing scheme for wireless sensor networks. Trans. Emerg. Telecommun. Technol. 25(10), 965–980 (2014)
Zhang, X., Liang, W., Haibin, Y., Feng, X.: Optimal convergecast scheduling limits for clustered industrial wireless sensor networks. Int. J. Distrib. Sens. Netw. 2012, 1319–1322 (2012)
Kumar, A., Baksh, R., Thakur, R.K., Singh, A.P.: Data aggregation in wireless sensor networks. Int. J. Sci. Res. 3(3), 249–251 (2014)
Singh, S.P., Sharma, S.C.: A survey on cluster based routing protocols in wireless sensor networks. Comput. Sci. 45(18), 687–695 (2015)
Zeb, A., Muzahidul Islam, A.K.M., Zareei, M., Al Mamoon, I., Mansoor, N., Baharun, S., Katayama, Y., Komaki, S.: Cluster analysis in wireless sensor networks: the ambit of performance metrics and schemes taxonomy. Int. J. Distrib. Sensor Netw. 12(7) (2016)
Fasolo, E., Rossi, M., Widmer, J., Zorzi, M.: In-network aggregation techniques for wireless sensor networks: a survey. IEEE Wirel. Commun. 14(2), 70–87 (2007)
Zhang, Y., Juhua, P., Liu, X., Chen, Z.: An adaptive spanning tree-based data collection scheme in wireless sensor networks. Int. J. Distrib. Sens. Netw. 2 (2015)
Manjhi, A., Nath, S., Gibbons, P.B.: Tributaries and deltas: efficient and robust aggregation in sensor network stream. Int. J. Distrib. Sens. Netw. 17(1), 287–298 (2005)
Shukla, K.V.: Research on energy efficient routing protocol leach for wireless sensor networks. Int. J. Eng. 2(3), 1–5 (2013)
Younis, O., Fahmy, S.: HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans. Mob. Comput. 3(4), 660–669 (2004)
Li, C., Ye, M., Chen, G., Wu, J.: An energy-efficient unequal clustering mechanism for wireless sensor networks. In: IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, pp. 597–604 (2005)
Yi, D., Yang, H.: HEER-a delay-aware and energy efficient routing protocol for wireless sensor networks. Comput. Netw. 104(C), 155–173 (2016)
Shu, L., Mukherjee, M., Hu, L., Bergmann, N., Zhu, C.: Geographic routing in duty-cycled industrial wireless sensor networks with radio irregularity. IEEE Access 4, 9043–9052 (2016)
Shu, L., Wang, L., Niu, J., Zhu, C., Mukherjee, M.: Releasing network isolation problem in group-based industrial wireless sensor networks. IEEE Syst. J. PP(99), 1–11 (2015)
Juhua, P., Yu, G., Zhang, Y., Chen, J., Xiong, Z.: A hole-tolerant redundancy scheme for wireless sensor networks. Int. J. Distrib. Sens. Netw. 1550–1329, 184–195 (2012)
George, T., Trevor, C.: Simulation tools for multilayer fault restoration. IEEE Commun. Mag. 47(3), 128–134 (2009)
Villas, L.A., Boukerche, A., de Oliveira, H.A.B.F., de Araujo, R.B., Loureiro, A.A.F.: A special correlation aware algorithm to perform efficient data collection in wireless sensor networks. Ad Hoc Netw. 12(1), 10–30 (2011)
Dong, M., Ota, K., Liu, A.: RMER: reliable and energy-efficient data collection for large-scale wireless sensor networks. IEEE IoT J. 3(4), 511–519 (2016)
Acknowledgments
We gratefully acknowledge the support from the National Natural Science Foundation of China (61502320, 61373161, 61173009 & 61572060), Science & Technology Project of Beijing Municipal Commission of Education in China (KM201410028015), Youth Backbone Project of Beijing Outstanding Talent Training Project (2014000020124G133), 973 Program (2013CB035503), CERNET Innovation Project (NGII20151004, NGII20160316), Beijing Advanced Innovation Center for Imaging Technology, and Cultivation Object of Young Yanjing Scholar of Capital Normal University.
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Tang, X., Xie, H., Chen, W., Niu, J. (2018). Energy-Efficient Data Collection Using Lossless Compression for Industrial Wireless Sensor Networks. In: Chen, Y., Duong, T. (eds) Industrial Networks and Intelligent Systems. INISCOM 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 221. Springer, Cham. https://doi.org/10.1007/978-3-319-74176-5_2
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DOI: https://doi.org/10.1007/978-3-319-74176-5_2
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