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Bee-based reliable data collection for mobile wireless sensor network

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Abstract

In mobile wireless sensor networks (MWSNs), methods of traditional data collection only consider increasing the amount of data acquisition or reducing the energy consumption of the whole network. In the process of data collection, how to maximize the data, the shortest mobile path and the reliability of the network is an optimization problem. In order to solve the above problems, this paper proposes an algorithm of reliable data collection for mobile Sink based on improved artificial bee colony optimization. It combines the selection of cluster node, the transmission path from sensor node to cluster node, and the path optimization of mobile Sink. It provides a typical model system of data collection in MWSNs, including the method of network energy consumption in the process of data collection. An improved artificial bee colony algorithm is proposed by using the initialization method of reverse learning, and introducing the search equation inspired by differential evolution algorithm. It overcomes the shortcomings of artificial bee colony algorithm with premature convergence and poor ability to search in late evolution, which satisfying the conditions of the shortest time consumption and the shortest path length of the mobile Sink. On the one hand, it aims to improve data collection and find the shortest traversal path of the mobile Sink. On the other hand, it is necessary to improve the network efficiency and reliability by considering network energy consumption and network delay. By the improved artificial bee colony algorithm, it gets the shortest path planning of mobile Sink for searching each cluster node. The sensor node transmits data to the nearest cluster node by multi hop routing with temporarily saving, and then it is sent to the mobile Sink. The proposed algorithm can effectively reduce the amount of sensor nodes transmitted to mobile sink with improving the efficiency of data collection. Compared with other methods, it can reduce network energy consumption and increase energy consumption balance and network reliability, so as to prolong network lifetime.

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References

  1. Dominikus, S., Kraxberger, S.: Secure communication with RFID tags in the internet of things. Secur. Commun. Netw. 7(12), 2639–2653 (2015)

    Article  Google Scholar 

  2. Zhang, D., Yang, L.T., Chen, M., et al.: Real-time locating systems using active RFID for internet of things. IEEE Syst. J. 10(3), 1226–1235 (2017)

    Article  Google Scholar 

  3. Farzana, A., Neduncheliyan, S.: Ant-based routing and QoS-effective data collection for mobile wireless sensor network. Wirel. Netw. 23(6), 1697–1707 (2016)

    Article  Google Scholar 

  4. Al-Karaki, J.N., Gawanmeh, A.: The optimal deployment coverage and connectivity problems in wireless sensor networks: revisited. Access IEEE 5, 18051–18065 (2017)

    Article  Google Scholar 

  5. Crowcroft, J., Segal, M.: Improved structures for data collection in static and mobile wireless sensor networks. J. Heuristics 21(2), 233–256 (2014)

    Article  Google Scholar 

  6. Arbit, A., Livne, Y., Oren, Y., et al.: Implementing public-key cryptography on passive rfid tags is practical. Int. J. Inf. Secur. 14(1), 85–99 (2015)

    Article  Google Scholar 

  7. Rose, D.P., Ratterman, M.E., Griffin, D.K., et al.: Adhesive rfid sensor patch for monitoring of sweat electrolytes. IEEE Trans. Bio-Med. Eng. 62(6), 1457–1463 (2015)

    Article  Google Scholar 

  8. Chowdhury, S., Giri, C., MESNET: Mobile sink based energy saving network management in wireless sensor network. In: International Conference on Computational Intelligence, Communications, and Business Analytics, pp. 308–321 (2017)

  9. Zhong, R.Y., Huang, G.Q., Lan, S., et al.: A two-level advanced production planning and scheduling model for rfid-enabled ubiquitous manufacturing. Adv. Eng. Inform. 29(4), 799–812 (2015)

    Article  Google Scholar 

  10. Gholami, M., Brennan, R.W.: Comparing two clustering-based techniques to track mobile nodes in industrial wireless sensor networks. J. Syst. Sci. Syst. Eng. 25(2), 177–209 (2016)

    Article  Google Scholar 

  11. Kumari, N., Sharma, N.: Efficient data dissemination in wireless sensor network using adaptive and dynamic mobile sink based on particle swarm optimization. In: Proceedings of the International Congress on Information and Communication Technology, pp. 85–92 (2016)

  12. Wang, J., Cao, J., et al.: Energy-efficient cluster-based dynamic routes adjustment approach for wireless sensor networks with mobile sinks. J. Supercomput. 73(7), 3277–3290 (2017)

    Article  Google Scholar 

  13. Sharma, S., Puthal, D., et al.: Rendezvous based routing protocol for wireless sensor networks with mobile sink. J. Supercomput. 73(3), 1168–1188 (2017)

    Article  Google Scholar 

  14. Babu, R., Shenoy, U., Patil, K.: Lifetime elongation of wireless sensor networks with mobile sink in delay-sensitive applications. In: International Conference on Computational Intelligence, Communications, and Business Analytics, pp. 335–348 (2017)

  15. Gill, S.S., Chana, I., Buyya, R.: IoT based agriculture as a cloud and big data service: the beginning of digital India. J. Org. End User Comput. 29(4), 1–23 (2017)

    Article  Google Scholar 

  16. Nobre, G.C., Tavares, E.: Scientific literature analysis on big data and internet of things applications on circular economy: a bibliometric study. Scientometrics 111(1), 463–492 (2017)

    Article  Google Scholar 

  17. Yarinezhad, R., Sarabi, A.: Reducing delay and energy consumption in wireless sensor networks by making virtual grid infrastructure and using mobile sink. AEU-Int. J. Electron. Commun. 84, 144 (2018)

    Article  Google Scholar 

  18. Huang, H., Savkin, A.V., Huang, C.: I-UMDPC: the improved-unusual message delivery path construction for wireless sensor networks with mobile sinks. Internet Things J. IEEE 4, 1528–1536 (2017)

    Article  Google Scholar 

  19. Ibrahim, S.S., Ibrahim, A., Allah, A.N., et al.: Building of a community cattle ranch and radio frequency identification (rfid) technology as alternative methods of curtailing cattle rustling in katsina state. Pastoralism 6(1), 1–9 (2016)

    Article  Google Scholar 

  20. Hossain, M.A., Quaddus, M., Islam, N.: Developing and validating a model explaining the assimilation process of RFID: an empirical study. Inf. Syst. Front. 18(4), 645–663 (2016)

    Article  Google Scholar 

  21. Deif, D., Gadallah, Y.: A comprehensive wireless sensor network reliability metric for critical Internet of Things applications. EURASIP J. Wirel. Commun. Netw. 2017, 145–160 (2017)

    Article  Google Scholar 

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Acknowledgements

This paper is supported by the Natural Science Foundation of Hubei Province (2017CFB773).

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Authors and Affiliations

  1. Hubei University of Economics, Wuhan, China

    Gao Ren

  2. Department of Geography, National University of Singapore, Arts Link, Singapore, Singapore

    Juebo Wu

  3. Faculty of Economics and Business, KU Leuven, Leuven, Belgium

    Frederik Versonnen

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  1. Gao Ren
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  2. Juebo Wu
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  3. Frederik Versonnen
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Correspondence to Juebo Wu.

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Ren, G., Wu, J. & Versonnen, F. Bee-based reliable data collection for mobile wireless sensor network. Cluster Comput 22 (Suppl 4), 9251–9260 (2019). https://doi.org/10.1007/s10586-018-2116-0

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  • DOI: https://doi.org/10.1007/s10586-018-2116-0

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