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access icon free Neuro-fuzzy and fuzzy schemes for cooperative communication in wireless sensor network: a military battlefield scenario

In the military battlefield, maintaining high survivability of energy constraint wireless sensor network (WSN) when some nodes are destroyed by the foe troops is one of the prominent issues for the researchers. This study proposes the fuzzy and neuro-fuzzy based relay selection schemes for cooperative WSN which reduce the bit error rate (BER) while improving the network lifetime. Meanwhile, the proposed model maintains the uninterrupted communication between military nodes in a warfare situation. The proposed proposed strategies are compared with the maximum residual energy-based relay selection (MRERS), minimum energy consumption-based relay selection (MECRS), and random relay selection (RRS) strategies. The performance of the proposed and existing strategies is evaluated on the basis of BER, network lifetime, number of dead nodes, and average energy of nodes in the network. The simulation results demonstrate that proposed schemes has 13.19–19.28% improvement in BER than the existing strategies. Moreover, 76.00–90.88% network lifetime improves when compared with the MECRS and RRS strategies. However, 6–7.76% is less than MRERS strategy. Furthermore, the results show that network survivability and average network energy is also better when the number of dead nodes in the network increases.

References

    1. 1)
      • 31. Shah, K.I., Maity, T., Dohare, S.Y.: ‘Weight based approach for optimal position of base station in wireless sensor network’. 2020 Int. Conf. on Inventive Computation Technologies (ICICT), Coimbatore, India, 2020, pp. 734738.
    2. 2)
      • 21. Hwang, K.-S., Ko, Y.-C.: ‘An efficient relay selection algorithm for cooperative networks’. 2007 IEEE Vehicular Technology Conf., Baltimore, USA, 2007, pp. 8185.
    3. 3)
      • 27. Aydin, I., Aygölü, U.: ‘A new energy-efficient relay selection technique for large-scale randomly distributed wireless networks’, Trans. Emerg. Telecommun. Technol., 2017, 28, p. e3143.
    4. 4)
      • 17. Agbulu, G.P., Kumar, G.J.R., Juliet, A.V.: ‘A lifetime-enhancing cooperative data gathering and relaying algorithm for cluster-based wireless sensor networks’, Int. J. Distrib. Sens. Netw., 2020, 16, (2), pp. 112.
    5. 5)
      • 4. Long, B.N., Kim, S.D.: ‘Efficient cooperative relaying selection scheme based on TDMA for military tactical multi-hop wireless networks’. 2017 IEEE Military Communications Conf. (MILCOM), Tampa, FL, 2017, pp. 16791684.
    6. 6)
      • 24. Amarasuriya, G., Ardakani, M., Tellambura, C.: ‘Output-threshold multiple relay selection scheme for cooperative wireless networks’, IEEE Trans. Veh. Technol., 2010, 59, (6), pp. 30913097.
    7. 7)
      • 22. Mohammed, F.A., Sergiy, A.V.: ‘Collaborative beamforming for wireless sensor networks with Gaussian distributed sensor nodes’, IEEE Trans. Wirel. Commun., 2009, 8, (2), pp. 638684.
    8. 8)
      • 16. Verma, A., Kumar, S., Gautam, P.R., et al: ‘Fuzzy logic based effective clustering of homogeneous wireless sensor networks for mobile sink’, IEEE Sens. J., 2020, 20, (10), pp. 56155623.
    9. 9)
      • 7. Wu, D., Cai, Y., Zhou, L., et al: ‘A cooperative communication scheme based on coalition formation game in clustered wireless sensor networks’, IEEE Trans. Wirel. Commun., 2012, 11, (3), pp. 11901200.
    10. 10)
      • 12. Brante, G., SantiPeron, G., Souza, R.D., et al: ‘Distributed fuzzy logic-based relay selection algorithm for cooperative wireless sensor networks’, IEEE Sens. J., 2013, 13, (11), pp. 43754386.
    11. 11)
      • 10. Ma, C., Liang, W., Zheng, M., et al: ‘Relay node placement in wireless sensor networks with respect to delay and reliability requirements’, IEEE Syst. J., 2019, 13, pp. 25702581.
    12. 12)
      • 23. Liu, Z.: ‘Single and multiple relay selection for cooperative communication under frequency selective channels’. 2013 IEEE Int. Conf. of IEEE Region 10 (TENCON), Xian, China, 2013, pp. 14.
    13. 13)
      • 9. Luo, J., Hu, J., Wu, D., et al: ‘Opportunistic routing algorithm for relay node selection in wireless sensor networks’, IEEE Trans. Ind. Inf., 2015, 11, (1), pp. 112121.
    14. 14)
      • 32. Kashyap, P.K., Kumar, S., Dohare, U., et al: ‘Green computing in sensors-enabled internet of things: neuro fuzzy logic-based load balancing’, MDPI Electron., 2019, 8, (4), pp. 384405.
    15. 15)
      • 5. Mohammad, Z.S., Krunz, M., Younis, O.: ‘Energy efficient clustering/routing for cooperative MIMO operation in sensor networks’. 2009 IEEE Int. Conf. (INFOCOM), Rio de Janeiro, Brazil, 2009, pp. 621629.
    16. 16)
      • 11. Cengiz, K., Dag, T.: ‘Energy aware multi-hop routing protocol for WSNs’, IEEE Access, 2017, 6, pp. 26222633.
    17. 17)
      • 2. Ismail, M.N., Shukran, M.A., Isa, M.R.M., et al: ‘Establishing a soldier wireless sensor network (WSN) communication for military operation monitoring’, Int. J. Inf. Commun. Technol., 2018, 7, (2), pp. 8995.
    18. 18)
      • 15. Rajput, A., Kumaravelu, V.B.: ‘Fuzzy-based clustering scheme with sink selection algorithm for monitoring applications of wireless sensor networks’, Arab. J. Sci. Eng., 2020, 45, pp. 66016623.
    19. 19)
      • 14. Baoju, Z., Cuiping, Z.: ‘An adaptive relay node selection algorithm based on opportunity’, EURASIP J. Wirel. Commun. Netw., 2017, 99, pp. 18.
    20. 20)
      • 30. Shah, K.I., Maity, T., Dohare, S.Y.: ‘Algorithm for energy consumption minimisation in wireless sensor network’, IET Commun., 2020, 14, (8), pp. 13011310.
    21. 21)
      • 25. Chen, H., Gershman, A.B., Shahbazpanahi, S.: ‘Filter-and-forward distributed beamforming in relay networks with frequency selective fading’, IEEE Trans. Signal Process., 2010, 58, (3), pp. 12511262.
    22. 22)
      • 19. Krishna, S.M., Rashmi, R.R.: ‘Adaptive fuzzy-based energy and delay-aware routing protocol for a heterogeneous sensor network’, J. Comput. Netw. Commun., 2019, 2019, pp. 111.
    23. 23)
      • 18. Agrawal, D., Pandey, S.: ‘Load balanced fuzzy-based unequal clustering for wireless sensor networks assisted internet of things’, Eng. Rep., 2020, 2, p. e12130.
    24. 24)
      • 28. Jain, K.N., Yadav, S.D., Verma, A.: ‘A fuzzy decision scheme for relay selection in cooperative wireless sensor network’, Int. J. Commun. Syst., 2019, 32, p. e4121.
    25. 25)
      • 1. Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., et al: ‘Wireless sensor networks: a survey’, Comput. Netw., 2002, 38, (4), pp. 393422.
    26. 26)
      • 8. Rahman, A.A., Kahar, M.N.M., Din, W.I.S.W., et al: ‘Distance based thresholds for 2-tier relay nodes selection in WSN’, Computer Standards and Interfaces, 2019, 66, p. 103359.
    27. 27)
      • 6. Li, B., Wang, W., Li, H., et al: ‘Performance analysis and optimization for energy efficient cooperative transmission in random wireless sensor network’, IEEE Trans. Wirel. Commun., 2013, 12, (9), pp. 46474657.
    28. 28)
      • 13. Jing, Y., Chao, Z.: ‘Energy-aware relay selections for simultaneous wireless information and power transfer’. 2017 23rd Asia-Pacific Conf. on Communications (APCC), Perth, 2017, pp. 16.
    29. 29)
      • 20. Murugaanandam, S., Ganapathy, V.: ‘Reliability-based cluster head selection methodology using fuzzy logic for performance improvement in WSNs’, IEEE Access, 2019, 7, pp. 8735787368.
    30. 30)
      • 3. Engmann, F., Katsriku, F.A., Abdulai, J., et al: ‘Prolonging the lifetime of wireless sensor networks: a review of current techniques’, Wirel. Commun. Mob. Comput., 2018, 2018, pp. 123.
    31. 31)
      • 33. Goldsmith, A.: ‘Wireless communications’ (Cambridge University Press, India, 2005, 1st edn.).
    32. 32)
      • 26. Zhang, D., Chen, Z., Zhou, H., et al: ‘Energy-balanced cooperative transmission based on relay selection and power control in energy harvesting wireless sensor network’, Comput. Netw., 2016, 104, pp. 189197.
    33. 33)
      • 29. Jain, K.N., Verma, A.: ‘Relay node selection in wireless sensor network using fuzzy inference system’, J. Commun., 2019, 14, (6), pp. 423431.
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