A survey on the characterization parameters and lifetime improvement techniques of wireless sensor network

References

[1] Z. Rafique and B.-C. Seet, “Performance analysis of cooperative virtual MIMO systems for wireless sensor networks,” Sensors, vol. 13, no. 6, pp. 7033–7052, 2013, https://doi.org/10.3390/s130607033.Search in Google Scholar PubMed PubMed Central

[2] M. K. Singh, S. I. Amin, S. A. Imam, V. K. Sachan, and A. Choudhary, “A survey of wireless sensor network and its types,” in International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), 2018, pp. 326–330.10.1109/ICACCCN.2018.8748710Search in Google Scholar

[3] S. Cui, A. J. Goldsmith, and A. Bahai, “Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks,” IEEE J. Sel. Area. Commun., vol. 22, no. 6, pp. 1089–1098, 2004, https://doi.org/10.1109/jsac.2004.830916.Search in Google Scholar

[4] J. E. Mbowe and G. S. Oreku, “Quality of service in wireless sensor networks,” Wireless Sens. Netw., vol. 6, pp. 19–26, 2014, https://doi.org/10.4236/wsn.2014.62003.Search in Google Scholar

[5] L. M. Borges, F. J. Velez, and S. L. António, “Survey on the characterization and classification of wireless sensor network applications,” IEEE Commun. Surv. Tutorials, vol. 16, pp. 1860–1890, 2014, https://doi.org/10.1109/comst.2014.2320073.Search in Google Scholar

[6] H. Yetgin, K. T. K. Cheung, and M. El-Hajjar, “A survey of network lifetime maximization techniques in wireless sensor networks,” IEEE Commun. Surv. Tutorials, vol. 19, no. 2, pp. 828–854, 2017, https://doi.org/10.1109/comst.2017.2650979.Search in Google Scholar

[7] I. Snigdh and N. Gupta, “Quality of service metrics in wireless sensor networks: a survey,” J. Inst. Eng. India Ser. B, vol. 97, pp. 91–96, 2016, https://doi.org/10.1007/s40031-014-0160-6.Search in Google Scholar

[8] R. Elhabyan, W. Shi, and M. St-Hilaire, “Coverage protocols for wireless sensor networks: review and future directions,” J. Commun. Network, vol. 17, no. 4, pp. 1–15, 2019, https://doi.org/10.1109/jcn.2019.000005.Search in Google Scholar

[9] A. Tripathi, H. P. Gupta, T. Dutta, R. Mishra, K. K. Shukla, and S. Jit, “Coverage and connectivity in WSNs: a survey, research issues and challenges,” IEEE Access, vol. 6, pp. 26971–26992, 2018, https://doi.org/10.1109/access.2018.2833632.Search in Google Scholar

[10] J. Singha, R. Kaur, and D. Singh, “A survey and taxonomy on energy management schemes in wireless sensor networks,” J. Syst. Architect., vol. 111, p. 101782, 2020.10.1016/j.sysarc.2020.101782Search in Google Scholar

[11] S. Amin, A. Taherkordi, Ø. Haugen, and E. Frank, “Clustering objectives in wireless sensor networks: a survey and research direction analysis,” Comput. Network., vol. 180, p. 107376, 2020.10.1016/j.comnet.2020.107376Search in Google Scholar

[12] A. Ghosh and K. Sajal, “Das, “Coverage and connectivity issues in wireless sensor networks: a survey,” Pervasive Mob. Comput., vol. 4, pp. 303–334, 2008, https://doi.org/10.1016/j.pmcj.2008.02.001.Search in Google Scholar

[13] H. M. Ammari and S. K. Das, “Coverage, connectivity, and fault tolerance measures of wireless sensor networks,” in 8th International Symposium, Dallas, TX, USA, 2006.10.1007/978-3-540-49823-0_3Search in Google Scholar

[14] I. Khoufi, M. Pascale, A. Laouiti, and S. Mahfoudh, “Survey of deployment algorithms in wireless sensor networks: coverage and connectivity issues and challenges,” Int. J. Autonom. Adapt. Commun. Syst., vol. 10, no. 4, pp. 341–390, 2017. https://doi.org/10.1504/ijaacs.2017.088774.Search in Google Scholar

[15] S. Harizan and P. Kuila, “Coverage and connectivity aware energy efficient scheduling in target based wireless sensor networks: an improved genetic algorithm-based approach,” Wireless Network, vol. 25, pp. 1995–2011, 2019, https://doi.org/10.1007/s11276-018-1792-2.Search in Google Scholar

[16] P. Latha and S. Benitta, “Maximizing the wireless sensor networks lifetime through energy efficient connected coverage,” Ad Hoc Netw., vol. 62, pp. 1–10, 2017.10.1016/j.adhoc.2017.04.001Search in Google Scholar

[17] S. B. Takale and S. D. Lokhande, “Quality of service requirement in wireless sensor networks: a survey,” in IEEE Global Conference on Wireless Computing and Networking (GCWCN), Lonavala, India, 2018, pp. 34–38.10.1109/GCWCN.2018.8668636Search in Google Scholar

[18] M. Asif, S. Khan, R. Ahmad, M. Sohail, and D. Singh, “Quality of service of routing protocols in wireless sensor networks: a review,” IEEE Access, vol. 5, pp. 1846–1871, 2017, https://doi.org/10.1109/access.2017.2654356.Search in Google Scholar

[19] F. M. Costa and H. Ochiai, “A comparison of modulations for energy optimization in wireless sensor network links,” in IEEE Global Telecommunications Conference GLOBECOM 2010. Miami, FL, 2010, 2010, pp. 1–5.10.1109/GLOCOM.2010.5683412Search in Google Scholar

[20] A. Sharma, A. Banerjee, and P. Sircar, “Performance analysis of energy-efficient modulation techniques for wireless sensor networks,” in Annual IEEE India Conference, 2008, pp. 327–332.10.1109/INDCON.2008.4768744Search in Google Scholar

[21] S. Althunibat, K. Ala, and R. Mesleh, “On the performance of wireless sensor networks with QSSK modulation in the presence of co-channel interference,” Telecommun. Syst., vol. 68, pp. 105–113, 2018, https://doi.org/10.1007/s11235-017-0382-4.Search in Google Scholar

[22] P. Chakraborty and C. Tharini, “Analysis of suitable modulation scheme for compressive sensing algorithm in wireless sensor network,” Sens. Rev., vol. 35, pp. 168–173, 2015, https://doi.org/10.1108/sr-06-2014-666.Search in Google Scholar

[23] Z. Shelby, C. Pomalaza, H. Karvonen, and J. Haapola, “Energy optimization in multihop wireless embedded and sensor networks,” Int. J. Wireless Inf. Network, vol. 1, pp. 221–225, 2005, https://doi.org/10.1007/s10776-005-5166-1.Search in Google Scholar

[24] M. Carlos-Mancilla, E. López-Mellado, and M. Siller, “Wireless sensor networks formation: approaches and techniques,” J. Sensors, vol. 2016, pp. 1–18, 2016, Article ID 2081902, https://doi.org/10.1155/2016/2081902.Search in Google Scholar

[25] N.-T. Dinh and Y. Kim, “Auto-configuration in wireless sensor networks: a review,” Sensors, 19, no 9, pp. 4281, 2019.10.3390/s19194281Search in Google Scholar PubMed PubMed Central

[26] Y. Chen and Q. Zhao, “On the lifetime of wireless sensor networks,” IEEE Commun. Lett., vol. 9, no. 11, pp. 976–978, 2005, https://doi.org/10.1109/lcomm.2005.11010.Search in Google Scholar

[27] X. Hao, N. Yao, L. Wang, and J. Wang, “Joint resource allocation algorithm based on multi-objective optimization for wireless sensor networks,” Appl. Soft Comput. J., vol. 94, p. 106470, 2020.10.1016/j.asoc.2020.106470Search in Google Scholar

[28] D. Jiang, Y. Wang, Y. Han, and H. Lv, “Maximum connectivity-based channel allocation algorithm in cognitive wireless networks for medical applications,” Neurocomputing, vol. 220, pp. 41–51, 2017, https://doi.org/10.1016/j.neucom.2016.05.102.Search in Google Scholar

[29] A. Ahmad, S. Ahmad, M. H. Rehmani, and N. U. Hassan, “A survey on radio resource allocation in cognitive radio sensor networks,” IEEE Commun. Surv. Tutorials, vol. 17, pp. 888–917, 2015, https://doi.org/10.1109/comst.2015.2401597.Search in Google Scholar

[30] T. Zhang, A. F. Molisch, Y. Shen, Q. Zhang, H. Feng, and M. Z. Win, “Joint power and bandwidth allocation in wireless cooperative localization networks,” IEEE Trans. Wireless Commun., vol. 15, pp. 6527–6540, 2016, https://doi.org/10.1109/twc.2016.2580504.Search in Google Scholar

[31] P. Kuila and P. K. Jana, “Energy efficient clustering and routing algorithms for wireless sensor networks: particle swarm optimization approach,” Eng. Appl. Artif. Intell., vol. 33, pp. 127–140, 2014, https://doi.org/10.1016/j.engappai.2014.04.009.Search in Google Scholar

[32] G. Wang, H. Zhu, H. Dai, L. Wu, and B. Xiong, “The clustering algorithm of wireless sensor networks based on multi-hop between clusters,” in WRI World Congress on Computer Science and Information Engineering, Los Angeles, CA, 2009, pp. 177–181.10.1109/CSIE.2009.593Search in Google Scholar

[33] F. Zhu and J. Wei, “An energy-efficient unequal clustering routing protocol for wireless sensor networks,” Int. J. Distributed Sens. Netw., vol. 15, no. 9, 2019, https://doi.org/10.1177/1550147719879384.Search in Google Scholar

[34] K. Xu, Z. Zhao, Y. Luo, G. Hui, and L. Hu, “An energy-efficient clustering routing protocol based on a high-QoS node deployment with an inter-cluster routing mechanism in WSNs,” Sensors, vol. 19, p. 2752, 2019, https://doi.org/10.3390/s19122752.Search in Google Scholar PubMed PubMed Central

[35] A. Ghosal, S. Halder, and S. K. Das, “Distributed on-demand clustering algorithm for lifetime optimization in wireless sensor networks,” J. Parallel Distr. Comput., vol. 141, pp. 129–142, 2020, https://doi.org/10.1016/j.jpdc.2020.03.014.Search in Google Scholar

[36] S. Dehghani, M. Pourzaferani, and B. Barekatain, “Comparison on energy-efficient cluster-based routing algorithms in wireless sensor network,” Procedia Computer Science, vol. 72, pp. 535–542, 2015, https://doi.org/10.1016/j.procs.2015.12.161.Search in Google Scholar

[37] M. Sabet and H. Naji, “An energy efficient multi-level route-aware clustering algorithm for wireless sensor networks: a self-organized approach,” Comput. Electr. Eng., vol. 72, pp. 3399–3417, 2016, https://doi.org/10.1016/j.compeleceng.2016.07.009.Search in Google Scholar

[38] W. Wu, N. Xiong, and C. Wu, “Improved clustering algorithm based on energy consumption in wireless sensor networks,” IET Networks, vol. 6, pp. 47–53, 2017, https://doi.org/10.1049/iet-net.2016.0115.Search in Google Scholar

[39] H. A. Babaeer and S. A. Al-Ahmadi, “Efficient and secure data transmission and sinkhole detection in a multi-clustering wireless sensor network based on homomorphic encryption and watermarking,” IEEE Access, vol. 8, pp. 92098–92109, 2020, https://doi.org/10.1109/access.2020.2994587.Search in Google Scholar

[40] F. Fanian and M. K. Rafsanjani, “Cluster-based routing protocols in wireless sensor networks: a survey based on methodology,” J. Netw. Comput. Appl., vol. 56, no. 142, pp. 111–142, 2019, https://doi.org/10.1016/j.jnca.2019.04.021.Search in Google Scholar

[41] K. Adam and J. Sosnowski, “Energy efficiency trade-off between duty-cycling and wake-up radio techniques in IoT networks,” Wireless Pers. Commun., vol. 107, pp. 1951–1971, 2019.10.1007/s11277-019-06368-0Search in Google Scholar

[42] A. A. A. Shabaneh, A. M. Ali, C. K. Ng, N. K. Noordin, A. Sali, and M. H. Yaacob, “Review of energy conservation using duty cycling schemes for IEEE 802.15.4 wireless sensor network,” Wireless Pers. Commun., vol. 77, pp. 589–604, 2014.10.1007/s11277-013-1524-ySearch in Google Scholar

[43] D. Ye and M. Zhang, “A self-adaptive sleep/wake-up scheduling approach for wireless sensor networks,” IEEE Trans. Cybern., vol. 48, no. 3, pp. 979–992, 2018, https://doi.org/10.1109/tcyb.2017.2669996.Search in Google Scholar

[44] T. A. Al-Janabi and H. S. Al-Raweshidy, “An energy efficient hybrid MAC protocol with dynamic sleep-based scheduling for high density IoT networks,” IEEE Internet of Things Journal, vol. 6, no. 2, pp. 2273–2287, 2019, https://doi.org/10.1109/jiot.2019.2905952.Search in Google Scholar

[45] X. Zhang, F. Yan, C. Li, and Q. Ding, “Coverage efficiency-based broadcast protocol for asynchronous wireless sensor networks,” IEEE Wireless Commun. Lett., vol. 5, no. 1, pp. 76–79, 2016, https://doi.org/10.1109/lwc.2015.2498173.Search in Google Scholar

[46] A. Guidara, F. Derbel, G. Fersi, S. Bdiri, and M. B. Jemaa, “Energy-efficient on-demand indoor localization platform based on wireless sensor networks using low power wake up receiver,” Ad Hoc Netw., vol. 93, p. 101902, 2019, https://doi.org/10.1016/j.adhoc.2019.101902.Search in Google Scholar

[47] L. Qiu, K. I. Wang, and Z. Salcic, “Dynamic duty cycle-based Wireless Sensor Network for underground pipeline monitoring,” in 9th International Conference on Sensing Technology (ICST), Auckland, New Zealand, 2015, pp. 116–121.10.1109/ICSensT.2015.7438375Search in Google Scholar

[48] S. A. Imam, M. K. Singh, V. K. Sachan, A. Choudhary, and A. M. Zaidi, “An energy-efficient data transmission scheme based on DSC-MIMO for wireless sensor network,” in 2nd IEEE International Conference on Integrated Circuits and Microsystems (ICICM). Nanjing, 2017.10.1109/ICAM.2017.8242191Search in Google Scholar

[49] M. Sartipi and F. Fekri, “Distributed source coding using short to moderate length rate-compatible LDPC codes the entire slepian-wolf rate region,” IEEE Trans. Commun., vol. 56, no. 3, pp. 400–411, 2008, https://doi.org/10.1109/tcomm.2008.060006.Search in Google Scholar

[50] A. D. Liveris, Z. Xiong, and C. N. Georghiades, “Compression of binary sources with side information at the decoder using LDPC codes,” IEEE Commun. Lett., vol. 6, pp. 1300–1304, 2002, https://doi.org/10.1109/lcomm.2002.804244.Search in Google Scholar

[51] A. D. Liveris and Z. Xiong, “A distributed source coding technique for correlated images using turbo-codes,” IEEE Commun. Lett., vol. 6, no. 9, pp. 379–381, 2002, https://doi.org/10.1109/lcomm.2002.803479.Search in Google Scholar

[52] N. Li, L. Zhang, and B. Li, “A new energy-efficient data transmission scheme based on DSC and virtual MIMO for wireless sensor network,” J. Contr. Sci. Eng., vol. 2015, 2015, Art no. 904274, https://doi.org/10.1155/2015/904274.Search in Google Scholar

[53] J. Chen and X. Han, “The distributed source coding method research based on clustering wireless sensor networks,” Int. J. Sens. Netw., vol. 17, no. 4, pp. 224–228, 2015. https://doi.org/10.1504/ijsnet.2015.069585.Search in Google Scholar

[54] M. Aktas, M. Kuscu, E. Dinc, and O. B. Akan, “D-DSC: decoding delay-based distributed source coding for internet of sensing things,” PloS One, vol. 13, p. e0193154, 2018, https://doi.org/10.1371/journal.pone.0193154.Search in Google Scholar PubMed PubMed Central

[55] M. Chen, M. Qiu, L. Liao, and J. Park, “Distributed multi-hop cooperative communication in dense wireless sensor networks,” J. Supercomput., vol. 56, pp. 353–369, 2011, https://doi.org/10.1007/s11227-010-0382-6.Search in Google Scholar

[56] J.-M. Chung, J. Kim, and D. Han, “Multihop hybrid virtual MIMO scheme for wireless sensor networks,” IEEE Trans. Veh. Technol., vol. 61, no. 9, pp. 4069–4078, 2012.10.1109/TVT.2012.2213620Search in Google Scholar

[57] I. Dey, M. M. Butt, and N. Marchetti, “Throughput analysis for virtual MIMO WSNs over measured MIMO channels,” IEEE Trans. Instrum. Meas., vol. 68, no. 1, pp. 297–299, 2019, https://doi.org/10.1109/tim.2018.2874370.Search in Google Scholar

[58] P. Patcharamaneepakorn, S. Wu, C.-X. Wang, et al., “Spectral, energy, and economic efficiency of 5G multicell massive MIMO systems with generalized spatial modulation,” IEEE Trans. Veh. Technol., vol. 65, no. 12, pp. 9715–9731, 2016, https://doi.org/10.1109/tvt.2016.2526628.Search in Google Scholar

[59] A. Mukherjee, D. K. Jain, P. Goswami, Q. Xin, L. Yang, and J. J. P. C. Rodrigues, “Back propagation neural network based cluster head identification in MIMO sensor networks for intelligent transportation systems,” IEEE Access, vol. 8, pp. 28524–28532, 2020, https://doi.org/10.1109/access.2020.2971969.Search in Google Scholar

[60] M. A. Hossain, R. M. Noor, K. A. Yau, I. Ahmedy, and S. S. Anjum, “A survey on simultaneous wireless information and power transfer with cooperative relay and future challenges,” IEEE Access, vol. 7, pp. 19166–19198, 2019, https://doi.org/10.1109/access.2019.2895645.Search in Google Scholar

[61] D. N. Nguyen and M. Krunz, “Cooperative MIMO in wireless networks: recent developments and challenges,” IEEE Network, vol. 27, no. 4, pp. 48–54, 2013, https://doi.org/10.1109/MNET.2013.6574665.Search in Google Scholar

[62] M. Singh, S. I. Amin, V. Sachan, and A. Choudhary, “Improving energy- efficiency in wireless sensor network using cooperative MIMO technique based on SM,” in 2nd International Conference on Micro-Electronics and Telecommunication Engineering, ICMETE, Ghaziabad, India, 2018, pp. 136–139.10.1109/ICMETE.2018.00040Search in Google Scholar

[63] D. Jiang, W. Li, and H. Lv, “An energy-efficient cooperative multi cast routing in multi-hop wireless networks for smart medical applications,” Neurocomputing, vol. 220, pp. 160–169, 2017, https://doi.org/10.1016/j.neucom.2016.07.056.Search in Google Scholar

[64] M. K. Singh and S. I. Amin, “Energy‐efficient data transmission technique for wireless sensor networks based on DSC and virtual MIMO,” ETRI J., vol. 42, no. 3, pp. 341–350, 2020, https://doi.org/10.4218/etrij.2018-0632.Search in Google Scholar

[65] S. P. Singh and S. C. Sharma, “Genetic-algorithm-based energy-efficient clustering (GAEEC) for homogenous wireless sensor networks,” IETE J. Res., vol. 64, pp. 1–12, 2017, https://doi.org/10.1080/03772063.2017.1364981.Search in Google Scholar

[66] J. Bhola, S. Soni, and G. K. Cheema, “Genetic algorithm based optimized leach protocol for energy efficient wireless sensor networks,” J. Ambient Intell. Humanized Comput., vol. 11, pp. 1281–1288, 2019. https://doi.org/10.1007/s12652-019-01382-3.Search in Google Scholar

[67] M. Elhoseny, X. Yuan, Z. Yu, C. Mao, H. K. El-Minir, and A. M. Riad, “Balancing energy consumption in heterogeneous wireless sensor networks using genetic algorithm,” IEEE Commun. Lett., vol. 19, no. 12, pp. 2194–2197, 2015, https://doi.org/10.1109/lcomm.2014.2381226.Search in Google Scholar

[68] A. Verma, S. Kumar, P. R. Gautam, T. Rashid, and A. Kumar, “Fuzzy logic based effective clustering of homogeneous wireless sensor networks for mobile sink,” IEEE Sensor. J., vol. 20, no. 10, pp. 5615–5623, 2020, https://doi.org/10.1109/jsen.2020.2969697.Search in Google Scholar

[69] T. Wang, G. Zhang, X. Yang, and A. Vajdi, “Genetic algorithm for energy-efficient clustering and routing in wireless sensor networks,” J. Syst. Software, vol. 146, pp. 196–214, 2018, https://doi.org/10.1016/j.jss.2018.09.067.Search in Google Scholar

[70] J. R. Srivastava and T. S. B. Sudarshan, “A genetic fuzzy system based optimized zone based energy efficient routing protocol for mobile sensor networks (OZEEP),” Appl. Soft Comput., vol. 37, pp. 863–886, 2015, https://doi.org/10.1016/j.asoc.2015.09.025.Search in Google Scholar

[71] N. Ali and A. H. Zaim, “Genetic algorithm application in optimization of wireless sensor networks,” Sci. World J., vol. 2014, 2014, Art no. 286575, https://doi.org/10.1155/2014/286575.Search in Google Scholar PubMed PubMed Central

[72] M. Rakibul and J. K. Islam, “On the cooperative MIMO communication for energy-efficient cluster-to-cluster transmission at wireless sensor network,” Ann. Telecommun., vol. 65, pp. 325–340, 2010.10.1007/s12243-009-0151-9Search in Google Scholar

[73] L. Wenxing, W. Muqing, Z. Min, L. Peizhe, and L. Tianze, “Hop count limitation analysis in wireless multi-hop networks,” Int. J. Distributed Sens. Netw., vol. 13, no. 1, 2017. https://doi.org/10.1177/1550147716683606.Search in Google Scholar

[74] K. Mekkaoui and A. Rahmoun, “Analysis of hops length in wireless sensor networks,” Wireless Sens. Netw., vol. 6, pp. 109–117, 2014.10.4236/wsn.2014.66012Search in Google Scholar

[75] A. Alsaafin, A. M. Khedr, and Z. Al Aghbari, “Distributed trajectory design for data gathering using mobile sink in wireless sensor networks,” Int. J. Electron. Commun., vol. 96, pp. 1–12, 2018, https://doi.org/10.1016/j.aeue.2018.09.005.Search in Google Scholar

[76] H. T. Nguyen, L. Van Nguyen, and X. L. Hai, “Efficient approach for maximizing lifespan in wireless sensor networks by using mobile sinks,” ETRI J., vol. 39, no. 3, pp. 353–363, 2017. https://doi.org/10.4218/etrij.17.0116.0629.Search in Google Scholar

[77] Y. Gu, F. Ren, Y. Ji, and J. Li, “The evolution of sink mobility management in wireless sensor networks: a survey,” IEEE Commun. Surv. Tutorials, vol. 18, no. 1, pp. 507–524, 2016, https://doi.org/10.1109/comst.2015.2388779.Search in Google Scholar

[78] J. Wang, Y. Gao, W. Liu, A Kumar and H.-J. Kim, “Energy efficient routing algorithm with mobile sink support for wireless sensor networks,” Sensors, vol. 19, 2019, https://doi.org/10.3390/s19071494.Search in Google Scholar PubMed PubMed Central

[79] L. Farzinvash, S. Najjar-Ghabel, and T. Javadzadeh, “A distributed and energy-efficient approach for collecting emergency data in wireless sensor networks with mobile sinks,” Int. J. Electron. Commun., vol. 108, pp. 79–86, 2019, https://doi.org/10.1016/j.aeue.2019.06.007.Search in Google Scholar

[80] G. Xie and F. Pan, “Cluster-based routing for the mobile sink in wireless sensor networks with obstacles,” IEEE Access, vol. 4, pp. 2019–2028, 2016, https://doi.org/10.1109/access.2016.2558196.Search in Google Scholar

[81] M. Abo-Zahhad, S. M. Ahmed, N. Sabor, and S. Sasaki, “Mobile sink-based adaptive Immune energy-efficient clustering protocol for improving the lifetime and stability period of wireless sensor networks,” IEEE Sensor. J., vol. 15, no. 8, pp. 4576–4586, 2015, https://doi.org/10.1109/jsen.2015.2424296.Search in Google Scholar

[82] C. Wu, Y. Liu, F. Wu, W. Fan, and B. Tang, “Graph-based data gathering scheme in WSNs with a mobility-constrained mobile sink,” IEEE Access, vol. 5, pp. 19463–19477, 2017, https://doi.org/10.1109/access.2017.2742138.Search in Google Scholar

[83] H. Huang, C. Huang, and D. Ma, “The cluster based compressive data collection for wireless sensor networks with a mobile sink,” Int. J. Electron. Commun., vol. 108, pp. 206–214, 2019, https://doi.org/10.1016/j.aeue.2019.06.019.Search in Google Scholar

[84] J. Wang, Y. Gao, W. Liu, A. Kumar, and H.-J. Kim, “Energy efficient routing algorithm with mobile sink support for wireless sensor networks,” Sensors, vol. 19, p. 1494, 2019, https://doi.org/10.3390/s19071494.Search in Google Scholar PubMed PubMed Central

[85] K. S. A. Manu, N. Adam, C. Tapparello, H. Ayatollahi, and W. Heinzelman, “Energy-harvesting wireless sensor networks (EH-WSNs): a review,” ACM Trans. Sens. Netw., vol. 14, no. 2, pp. 1–50, 2018. https://doi.org/10.1145/3183338.Search in Google Scholar

[86] T. Ruan, Z. J. Chew, and M. Zhu, “Energy-aware approaches for energy harvesting powered wireless sensor nodes,” IEEE Sensor. J., vol. 17, no. 7, pp. 2165–2173, 2017, https://doi.org/10.1109/jsen.2017.2665680.Search in Google Scholar

[87] H. Yoo, M. Shim, and D. Kim, “Dynamic duty-cycle scheduling schemes for energy-harvesting wireless sensor networks,” IEEE Commun. Lett., vol. 16, no. 2, pp. 202–204, 2012, https://doi.org/10.1109/lcomm.2011.120211.111501.Search in Google Scholar

[88] A. Ammar and D. Reynolds, “An adaptive scheduling scheme for cooperative energy harvesting networks,” J. Commun. Network., vol. 17, no. 3, pp. 256–264, 2015, https://doi.org/10.1109/jcn.2015.000047.Search in Google Scholar

[89] D. Zhang, Z. Chen, H. Zhou, L. Chen, and X. S Shen, “Energy-balanced cooperative transmission based on relay selection and power control in energy harvesting wireless sensor network,” Comput. Network., vol. 104, pp. 189–197, 2016, https://doi.org/10.1016/j.comnet.2016.05.013.Search in Google Scholar

[90] D. K. Sah and T. Amgoth, “Renewable energy harvesting schemes in wireless sensor networks: a Survey,” Inf. Fusion, vol. 63, pp. 223–247, 2020, https://doi.org/10.1016/j.inffus.2020.07.005.Search in Google Scholar

[91] H. Sharma, A. Haque, and Z. A. Jaffery, “Maximization of wireless sensor network lifetime using solar energy harvesting for smart agriculture monitoring,” Ad Hoc Netw., vol. 94, 2019, https://doi.org/10.1016/j.adhoc.2019.101966.Search in Google Scholar

[92] D. Kaur and N. Kumar, “Cost reduction and channel capacity enhancement of MIMO system using antenna selection techniques,” Int. J. Electron. Telecommun., vol. 65, no. 2, pp. 189–194, 2019.10.24425/ijet.2019.126300Search in Google Scholar

[93] N. Zaman, T. J. Low, and M. Mehboob, “Enhancing energy efficiency of wireless sensor network through the design of energy efficient routing protocol,” J. Sensors, vol. 2016, 2016, Art no. 9278701, https://doi.org/10.1155/2016/9278701.Search in Google Scholar

[94] A. Kozłowski and J. Sosnowski, “Energy efficiency trade-off between duty-cycling and wake-up radio techniques in IoT networks,” Wireless Pers. Commun., vol. 107, pp. 1951–1971, 2019.10.1007/s11277-019-06368-0Search in Google Scholar

[95] M. K. Singh, S. I. Amin, and C. Amit, “Genetic algorithm-based sink mobility for energy efficient data routing in wireless sensor networks,” AEU - Int. J. Electron. Commun., vol. 131, 2021.10.1016/j.aeue.2021.153605Search in Google Scholar

[96] A. Bilami and D. E. Boubiche, “A hybrid energy aware routing algorithm for wireless sensor networks,” in IEEE Symposium on Computers and Communications, Marrakech, Morocco, 2008, pp. 975–980.10.1109/ISCC.2008.4625739Search in Google Scholar

[97] J. Jagannath, N. Polosky, A. Jagannath, F. Restuccia, and T. Melodia, “Machine learning for wireless communications in the Internet of Things: a comprehensive survey,” Ad Hoc Netw., vol. 93, 2019, https://doi.org/10.1016/j.adhoc.2019.101913.Search in Google Scholar

[98] R. E. Mohamed, A. I. Saleh, and M. Abdelrazzak, “Survey on wireless sensor network applications and energy efficient routing protocols,” Wireless Pers. Commun., vol. 101, pp. 1019–1055, 2018, https://doi.org/10.1007/s11277-018-5747-9.Search in Google Scholar

[99] D. Kandris, C. Nakas, D. Vomvas, and G. Koulouras, “Applications of wireless sensor networks: an up-to-date survey,” App. Syst. Innov., vol. 3, no. 14, 2020. https://doi.org/10.3390/asi3010014.Search in Google Scholar

[100] A. Ali, Y. Ming, S. Chakraborty, and S. Iram, “A comprehensive survey on real-time applications of WSN,” Future Internet, vol. 9, no. 77, 2017, https://doi.org/10.3390/fi9040077.Search in Google Scholar

[101] T. Rault, A. Bouabdallah, and Y. Challal, “Energy-efficiency in wireless sensor networks: a top-down review approach,” Comput. Network., vol. 67, pp. 104–122, 2014, https://doi.org/10.1016/j.comnet.2014.03.027.Search in Google Scholar