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Cluster Computing

, Volume 22, Supplement 1, pp 597–607 | Cite as

Maximum data collection rate routing for data gather trees with data aggregation in rechargeable wireless sensor networks

  • Haifeng Lin
  • Di Bai
  • Yunfei LiuEmail author
Article
  • 396 Downloads

Abstract

In rechargeable wireless sensor networks (R-WSNs), due to limited and dynamic energy supplyment, a sensor can not be always have enough energy when a network can gather excessive energy from the environment. At the same time, it is critical for higher data collection rate when sensors are working at a very low duty cycle due to sporadic availability of energy. Therefore, the sensors with surplus energy can be scheduled for strengthening packet delivery efficiency and improving data collection rate. Considering the data has some relation and redundancy, in this paper, an algorithm is proposed to achieve a high data generation rate for data-gathering trees based on data aggregation technology which can maximize data gather rate as an optimization problem for improving data generation rate in rechargeable wireless networks. An initial data-gathering tree is established and the maximum data collection rate routing is achieved by adjusting the heavily loaded and medium heavily loaded nodes. The data collection rate of the data-gathering tree produced by the proposed algorithm has been shown to be significantly higher than that of the initial tree. The simulation and experiments demonstrate that the proposed algorithm is efficient to maximize data collection rate in R-WSNs.

Keywords

Wireless sensor networks Maximum data collection rate Data gathering tree Data aggregation Rechargeable-WSNs 

Notes

Acknowledgements

This work was supported by Nanjing Forestry University Science and Technology Innovation Fund (Grant No. CX2016024), The Jiangsu Overseas Research and Training Pro-gram for University Prominent Young and Middle-Aged Teachers and Presidents, The National Natural Science Foundation of China, No. 31670554 and Natural Science Foundation of Jiangsu Province, Grant No. BK20161527.

References

  1. 1.
    Seah, W.K.G., Tan, Y.K., Chan, A.T.S.: Research in Energy Harvesting Wireless Sensor Networks and the Challenges Ahead. Springer, Berlin (2013)Google Scholar
  2. 2.
    Seah, W.K.G., Eu, Z.A., Tan, H.P.: Wireless sensor networks powered by ambient energy harvesting (WSN-HEAP)—survey and challenges. In: 1st International Conference on Wireless Communication, Vehicular Technology, Information Theory and Aerospace and Electronic Systems Technology, 2009. Wireless VITAE 2009, pp. 1–5. IEEE (2009)Google Scholar
  3. 3.
    Lin, H., Bai, D., Gao, D., Liu, Y.: Maximum data collection rate routing protocol based on topology control for rechargeable wireless sensor networks. Sensors 16(8), 1201 (2016)CrossRefGoogle Scholar
  4. 4.
    Lin, H., Bai, D., Gao, D., Liu, Y.: A light-weight linear network coding cipher model based on cloud computing for collaborative wireless sensor networks. J. Internet Technol. 16(5), 923–931 (2015)Google Scholar
  5. 5.
    Starner, T.: Human-powered wearable computing. IBM Syst. J. 35(3–4), 618–629 (1996)CrossRefGoogle Scholar
  6. 6.
    Kymissis, J., Kendall, C., Paradiso, J., Gershenfeld, N.: Parasitic power harvesting in shoes. In: Second International Symposium on Wearable Computers, October, pp. 132–139 (1998)Google Scholar
  7. 7.
    Amruta, M.K., Satish, M.T.: Solar powered water quality monitoring system using wireless sensor network. In: 2013 International Multi-conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s), pp. 281–285. IEEE (2013)Google Scholar
  8. 8.
    Kansal, A., Hsu, J., Zahedi, S., Srivastava, M.B.: Power management in energy harvesting sensor networks. ACM Trans. Embed. Comput. Syst. (2007).  https://doi.org/10.1145/1274858.1274870
  9. 9.
    Sudevalayam, S., Kulkarni, P.: Energy harvesting sensor nodes: survey and implications. IEEE Commun. Surv. Tutor. 13(3), 443–461 (2011)CrossRefGoogle Scholar
  10. 10.
    Stankovic, J.A., He, T.: Energy management in sensor networks. Philos. Trans. R. Soc. A 2012(370), 52–67 (1958)Google Scholar
  11. 11.
    Bhuvaneswari, P.T.V., Balakumar, R., Vaidehi, V., et al.: Solar energy harvesting for wireless sensor networks. In: First International Conference on Computational Intelligence, Communication Systems and Networks, 2009. CICSYN’09, pp. 57–61. IEEE (2009)Google Scholar
  12. 12.
    Wan, Z.G., Tan, Y.K., Yuen, C.: Review on energy harvesting and energy management for sustainable wireless sensor networks. In: 2011 IEEE 13th International Conference on Communication Technology (ICCT), pp. 362–367. IEEE (2011)Google Scholar
  13. 13.
    Gu, Y., He, T.: Bounding communication delay in energy harvesting sensor networks. In: 2010 IEEE 30th International Conference on Distributed Computing Systems (ICDCS), pp. 837–847. IEEE (2010)Google Scholar
  14. 14.
    Giuppi, F., Niotaki, K., Collado, A., et al.: Challenges in energy harvesting techniques for autonomous self-powered wireless sensors. In: 2013 European Microwave Conference (EuMC), pp. 854–857. IEEE (2013)Google Scholar
  15. 15.
    Olds, J.P., Seah, W.K.G.: Power considerations for very low duty cycle wireless sensor networks powered by energy harvesting[M]. Victoria University of Wellington, School of Engineering and Computer Science (2011)Google Scholar
  16. 16.
    Gnawali, O., Fonseca, R., Jamieson, K., et al.: CTP: an efficient, robust, and reliable collection tree protocol for wireless sensor networks. ACM Trans. Sens. Netw. 10(1), 16 (2013)CrossRefGoogle Scholar
  17. 17.
    Crowcroft, J., Segal, M., Levin L.: Improved structures for data collection in static and mobile wireless sensor networks. J. Heuristics (2014).  https://doi.org/10.1007/s10732-014-9250-5
  18. 18.
    Solis, I., Obraczka, K.: In-network aggregation trade-offs for data collection in wireless sensor networks. Int. J. Sens. Netw. 1(3), 200–212 (2006)CrossRefGoogle Scholar
  19. 19.
    Koutsopoulos, I., Halkidi, M.: Measurement aggregation and routing techniques for energy-efficient estimation in wireless sensor networks. In: 8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, Avignon, France, 31 May, WiOpt (2010)Google Scholar
  20. 20.
    Jeong, J., Kim, J., Cha, W., et al.: A QoS-aware data aggregation in wireless sensor networks. In: 12th International Conference on Advanced Communication Technology: ICT for Green Growth and Sustainable Development, ICACT 2010-Proceedings, Korea, pp. 156–161 (2010)Google Scholar
  21. 21.
    Shrivastava, P., Pokle, S.B.: Energy efficient scheduling strategy for data collection in wireless sensor networks. In: 2014 International Conference on Electronic Systems, Signal Processing and Computing Technologies (ICESC), pp. 170–173. IEEE (2014)Google Scholar
  22. 22.
    Incel, O.D., Krishnamachari, B.: Enhancing the data collection rate of tree-based aggregation in wireless sensor networks. In: 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, 2008. SECON’08, pp. 569–577. IEEE (2008)Google Scholar
  23. 23.
    Hakoura, B., Rabbat, M.G.: Data aggregation in wireless sensor networks: a comparison of collection tree protocols and gossip algorithms. In: 2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), pp. 1–4. IEEE (2012)Google Scholar
  24. 24.
    Shi, F., Huang, Y., Ren, Z., et al.: Design of adaptive tree-mesh hybrid wireless sensor networks for greenhouses. Trans. Chin. Soc. Agric. Eng. 29(5), 102–108 (2013)Google Scholar
  25. 25.
    Incel, O.D., Ghosh, A., Krishnamachari, B., et al.: Fast data collection in tree-based wireless sensor networks. IEEE Trans. Mob. Comput. 11(1), 86–99 (2012)CrossRefzbMATHGoogle Scholar
  26. 26.
    Wang, W., Wang, B., Liu, Z., et al.: A cluster-based and tree-based power efficient data collection and aggregation protocol for wireless sensor networks. Inf. Technol. J. 10(3), 557–564 (2011)CrossRefGoogle Scholar
  27. 27.
    Wu, F.J., Tseng, Y.C.: Distributed wake-up scheduling for data collection in tree-based wireless sensor networks. IEEE Commun. Lett. 13(11), 850–852 (2009)CrossRefGoogle Scholar
  28. 28.
    Jaiswal, N.V., Dhole, V.S., Dakhane, D.M., et al.: Strategies of data collection in tree-based wireless sensor networks. Int. J. Manag. IT Eng. 2(7) (2012). http://www.ijmra.us
  29. 29.
    Zeng, Y., Zhang, X.D., Dong, Y.H.: Effects of energy harvesting rate on lifetime and throughput capacity in wireless sensor networks. Adv. Mater. Res. 981, 482–485 (2014)CrossRefGoogle Scholar
  30. 30.
    Roseveare, N., Natarajan, B.: An alternative perspective on utility maximization in energy harvesting wireless sensor networks (2013).  https://doi.org/10.1109/TVT.2013.227224
  31. 31.
    Liu, R.S., Fan, K.W., Zheng, Z., et al.: Perpetual and fair data collection for environmental energy harvesting sensor networks. IEEE/ACM Trans. Netw. 19(4), 947–960 (2011)CrossRefGoogle Scholar
  32. 32.
    Yang, S., Mccann, J.A.: Distributed optimal lexicographic max-min rate allocation in solar-powered wireless sensor networks. ACM Trans. Sens. Netw. 11(1), 9 (2014)CrossRefGoogle Scholar
  33. 33.
    Sadlapur, A., Pushpa, P.V.: Computing optimal data collection rate for energy harvesting sensor networks. In: 2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 1468–1472. IEEE (2013)Google Scholar
  34. 34.
    Peng, S., Low, C.P.: Throughput optimal energy neutral management for energy harvesting wireless sensor networks. In: 2012 IEEE Wireless Communications and Networking Conference (WCNC), pp. 2347–2351. IEEE (2012)Google Scholar
  35. 35.
    Prabhakar, T.V., Iyer, M., Prakruthi, K., et al.: Throughput schemes for energy harvesting sensor networks. In: 2012 Fourth International Conference on Communication Systems and Networks (COMSNETS), pp. 1–7. IEEE (2012)Google Scholar
  36. 36.
    Satapathy, S.S., Sarma, N.: TREEPSI: tree based energy efficient protocol for sensor information. In: Wireless and Optical Communications Networks 2006 IFIP International Conference, April 2006Google Scholar
  37. 37.
    Sudevalayam, S., Kulkarni, P.: Energy Harvesting Sensor Nodes: Survey and Implications. Technical Report IITB/CSE/2008/December/19. TR-CSE-2008-19. Department of Computer Science and Engineering (CSE), Indian Institute of Technology Bombay (IITB) (2008)Google Scholar
  38. 38.
    von Rickenbach, P., Wattenhofer, R.: Gathering correlated data in sensor networks. In: DIALM-POMC04: Proceedings of the 2004 Joint Workshop on Foundations of Mobile Computing, pp. 60–66. ACM Press, New York (2004)Google Scholar
  39. 39.
    Cristescu, R., Beferull-Lozano, B., Vetterli, M.: On network correlated data gathering. In: Infocom04, Hong Kong (2004)Google Scholar
  40. 40.
    Nguyen, K., Nguyen, V.H., Le, D.D., et al.: ERI-MAC: An energy-harvested receiver-initiated MAC protocol for wireless sensor networks. Int. J. Distrib. Sens. Netw. (2014).  https://doi.org/10.1155/2014/514169
  41. 41.
    Sanchez, J.A.: Localized energy-efficient multicast algorithm based on geographic routing. In: Proceedings—Conference on Local Computer Networks, pp. 3–12 (2006)Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.College of Information Science and TechnologyNanjing Forestry UniversityNanjingChina
  2. 2.College of EngineeringNanjing Agricultural UniversityNanjingChina

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