Your browser does not support JavaScript!

Efficient approach to maximise WSN lifetime using weighted optimum storage-node placement, efficient and energetic wireless recharging, efficient rule-based node rotation and critical-state-data-passing methods

Efficient approach to maximise WSN lifetime using weighted optimum storage-node placement, efficient and energetic wireless recharging, efficient rule-based node rotation and critical-state-data-passing methods

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Networks — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

The sensor nodes of wireless sensor networks (WSNs) are usually positioned in remote or inaccessible areas and hence the physical maintenance such as battery replacement is more difficult. One of the core challenges of WSN is to increase the network life time, meaning that the efficiency of power utilisation should be the maximum. The major reasons for high power consumption are drawn out transmission path to reach sink, work load add-ons on nodes closer to storage medium, and the energy necessary for storage. This study proposes a novel method of data storage and retrieval for WSN environment to improve the network lifetime by minimising the energy consumption. The proposed method accomplishes this milestone using four novel algorithms, namely weighted optimum storage-node placement(SNP), efficient and energetic wireless recharging, efficient rule-based node rotation and critical-state-data passing. The areas of influence of this proposed method are SNP, wireless recharging, node rotation and cooperative multi-input–multi-output clustering/routing. Simulation results claim that the proposed method multiplies the WSN topology lifetime ratio by a significant level and outperforms the earlier versions significantly.


    1. 1)
      • 25. Abdelrahman, A., Mohammad, H., Bamidele, A., et al: ‘Dynamic clustering and management of mobile wireless sensor networks’, Elsevier, Comput. Netw., 2017, 117, pp. 6275.
    2. 2)
      • 4. Albano, M., Chessa, S., Nidito, F., et al: ‘Dealing with non uniformity in data centric storage for wireless sensor networks’, IEEE Trans. Parallel Distrib. Syst., 2011, 22, (8), pp. 13981406.
    3. 3)
      • 12. Fu, L., Cheng, P., Gu, Y., et al: ‘Minimizing charging delay in wireless rechargeable sensor networks’. IEEE Proc. INFOCOM, 2013.
    4. 4)
      • 3. Ahn, J., Krishnamachar, B.: ‘Fundamental scaling laws for energy efficient storage and querying in wireless sensor networks’, ACM MobiHoc, 2006, pp. 2225.
    5. 5)
      • 6. Mane, S.M., Bhanwase, V.V., Vadhoot, A., et al: ‘Efficient an optimal storage placement in sensor network’, Int. J. Sci. Eng. Res., 2014, 5, (2), pp. 5459.
    6. 6)
      • 10. Peng, Y., Li, Z., Zhang, W., et al: ‘Prolonging sensor network lifetime through wireless charging’. IEEE Real-Time Systems Symp. (RTSS), 2010.
    7. 7)
      • 24. Chao-Tsun, C., Chih-Yung, C., Shenghui, Z.: ‘SRA: a sensing radius adaptation mechanism for maximizing network lifetime in WSNs’, IEEE Trans. Veh. Technol., 2016, 65, (12), pp. 98179833.
    8. 8)
      • 16. Jain, S., Shah, R., Brunette, W., et al: ‘Exploiting mobility for energy efficient data collection in wireless sensor networks’, Mob. Netw. Appl., 2006, 11, (3), pp. 327339.
    9. 9)
      • 14. Yuanchao, S., Hamed, Y., Peng, C., et al: ‘Near-optimal velocity control for mobile charging in wireless rechargeable sensor networks’, IEEE Trans. Mob. Comput., 2016, 15, (7), pp. 16991713.
    10. 10)
      • 21. Handy, M.J., Haase, M., Timmermann, D.: ‘Low energy adaptive clustering hierarchy with deterministic cluster-head selection’. Proc. Fourth Int. Workshop on Mobile and Wireless Communications Network, 2002, pp. 368372.
    11. 11)
      • 7. Yao, W., Li, M., Wu, M.: ‘Inductive charging with multiple charger nodes in wireless sensor networks’ (APWeb Workshops Springer, 2006).
    12. 12)
      • 22. Liang, Q.: ‘Cluster head election for mobile ad hoc wireless network’. Proc. 14th IEEE Int. Symp. Personal, Indoor and Mobile Radio Comm.(PIMRC), 2003, pp. 16231628.
    13. 13)
      • 11. Sharifi, M., Sedighian, S., Kamali, M.: ‘Recharging sensor nodes using implicit actor coordination in wireless sensor actor network’, Wirel. Sens. Netw., 2010.
    14. 14)
      • 18. Kansal, A.D., Jea, D., Estrin, D., et al: ‘Controllably mobile infrastructure for low energy embedded networks’, IEEE Trans. Mob. Comput., 2006, 5, (8), pp. 958973.
    15. 15)
      • 9. Tong, B., Li, Z., Wang, G., et al: ‘How wireless power charging technology affects sensor network deployment and routing’. IEEE ICDCS, 2010.
    16. 16)
      • 23. Mohammad, Z., Siam, K.M., Younis, O.: ‘Energy-efficient clustering/routing for cooperative MIMO operation in sensor networks’, TR-UA-ECE, 2008.
    17. 17)
      • 13. Yang, Y., Wang, C., Li, J.: ‘Wireless rechargeable sensor networks – current status and future trends’, J. Commun., 2015, 10, (9), pp. 696706.
    18. 18)
      • 26. Kurs, A., Karalis, M.R., Joannopoulos, J.D., et al: ‘Wireless power transfer via strongly coupled magnetic resonances’, Science, 2007, 317, p. 83.
    19. 19)
      • 5. Apte, S.S., Mane, S.M.: ‘Improvement of limited storage placement in wireless sensor networks’, IOSR J. Comput. Eng. (IOSR-JCE), 2013, 12, (2), pp. 107111.
    20. 20)
      • 15. Yuanchao, S., Kang, G.S., Jiming, C., et al: ‘Joint energy replenishment and operation scheduling in wireless rechargeable sensor networks’, IEEE Trans. Ind. Inf., 2017, 13, (1), pp. 125134.
    21. 21)
      • 17. Luo, J.J., Hubaux, P.: ‘Joint mobility and routing for lifetime elongation in wireless sensor networks’. IEEE 24th Annual Joint Conf., IEEE Computer Communication Society, 2005, pp. 17351746.
    22. 22)
      • 19. El-Moukaddem, F., Torng, E., Xing, G.: ‘Maximizing network topology lifetime using mobile node rotation’, IEEE Trans. Parallel Distrib. Syst., 2015, 26, (7), pp. 19581970.
    23. 23)
      • 1. Sheng, B., Li, Q., Mao, W.: ‘Optimized storage placement in sensor networks’, IEEE Trans. Mob. Comput., 2010, 9, (10), pp. 14371450.
    24. 24)
      • 20. Zitterbart, D.P., Wienecke, B., Butler, J.P., et al: ‘Coordinated movements prevent jamming in an emperor penguin huddle’, PLoS ONE, 2011, 6, (6), p. e20260, doi: 10.1371/journal.pone.0020260.
    25. 25)
      • 8. Afzal, M.I., Mahmood, W., Sajid, S.M., et al: ‘Optical wireless communication and recharging mechanism of wireless sensor network by using CCRs’, Int. J. Adv. Sci. Technol., 2009, 13, pp. 4959.
    26. 26)
      • 2. Ganesan, D., Greenstein, B., Heidemann, J., et al: ‘Multi resolution storage and search in sensor networks’, ACM Trans. Storage, 2005, V, (N), pp. 277315.

Related content

This is a required field
Please enter a valid email address