A survey of data aggregation and routing protocols for energy-efficient wireless sensor networks

Archana Bomnale; Avinash More

doi:10.4108/eetsis.6924

Authors

Archana Bomnale Narsee Monjee Institute of Management Studies
Avinash More Narsee Monjee Institute of Management Studies

DOI:

https://doi.org/10.4108/eetsis.6924

Keywords:

Wireless sensor network, Routing Protocol, Data aggregation, Network lifetime, Energy efficiency

Abstract

The sensor nodes in wireless sensor networks (WSNs) typically have limited energy sources and are battery-operated. Reducing energy- usage, latency, and bandwidth is necessary to extend the network’s lifetime. WSN is often deployed in dynamic environments where nodes in the network can join, leave, or fail at any instant. Dynamic topology changes have the potential to disrupt established routes, necessitating more frequent route discovery and maintenance. Since a huge number of nodes are randomly deployed, a lot of redundant data packets are sent, which increases network traffic and creates delays. Robust and adaptable routing and aggregation techniques are necessary to meet these demands and adapt to shifting network conditions. The proposed survey paper offers a thorough analysis of the data aggregation mechanisms and energy-efficient routing algorithms applied to sensor networks. We have categorized the protocols depending on the network structure, data-gathering strategies, routing methodology, and node mobility. Based on the protocol performance parameters such as energy efficiency, network longevity, latency, routing overhead, packet delivery ratio, network throughput, and residual energy, we have provided a thorough classification and comparative overview of the key protocols. Moreover, we have determined the research gaps in the existing data aggregation techniques, and key areas which could point future researchers in the right direction.

References

[1] H. Yetgin, K. T. K. Cheung, M. El-Hajjar, and L. H. Hanzo, “A survey of network lifetime maximization techniques in wireless sensor networks,” IEEE Communications Surveys & Tutorials, vol. 19, no. 2, pp. 828–854, 2017.

[2] M. E. Keskin, I. K. Altınel, N. Aras, and C. Ersoy, “Wireless sensor network design by lifetime maximisation: an empirical evaluation of integrating major design issues and sink mobility,” International Journal of Sensor Networks, vol. 20, no. 3, pp. 131–146, 2016.

[3] R. Zagrouba and A. Kardi, “Comparative study of energy efficient routing techniques in wireless sensor networks,” Information, vol. 12, no. 1, p. 42, 2021.

[4] C. G. D. Mrunali Dhande, “Performance evaluation of various routing protocols in wireless sensor networks,” International Journal of Engineering Research and Applications, vol. 7, no. 2, pp. 11–13, April 2014.

[5] O. S. A. Z. Mohamed I. Gaber, Imbaby I.Mahmoud, “Comparison of routing protocols in wireless sensor networks for monitoring applications,” International Journal of Computer Applications, vol. 113, no. 12, pp. 1–7, March 2015.

[6] J. Kumari et al., “A comprehensive survey of routing protocols in wireless sensor networks,” in 2015 2nd International Conference on Computing for Sustainable Global Development (INDIACom). IEEE, 2015, pp. 325–330.

[7] D. Goyal and M. R. Tripathy, “Routing protocols in wireless sensor networks: A survey,” in 2012 Second International Conference on Advanced Computing & Communication Technologies. IEEE, 2012, pp. 474–480.

[8] M. Hosseinzadeh, S. Ali, A. H. Mohammed, J. Lansky, S. Mildeova, M. S. Yousefpoor, E. Yousefpoor, O. Hassan Ahmed, A. M. Rahmani, and A. Mehmood, “An energy-aware routing scheme based on a virtual relay tunnel in flying ad hoc networks,” Alexandria Engineering Journal, vol. 91, pp. 249–260, 2024.

[9] M. Sabet and H. R. Naji, “A decentralized energy efficient hierarchical cluster-based routing algorithm for wireless sensor networks,” AEU - International Journal of Electronics and Communications, vol. 69, no. 5, pp. 790–799, 2015.

[10] R. Maivizhi and P. Yogesh, “Spatial correlation based data redundancy elimination for data aggregation in wireless sensor networks,” in 2020 International Conference on Innovative Trends in Information Technology (ICITIIT). IEEE, 2020, pp. 1–5.

[11] L. Dash, B. K. Pattanayak, S. K. Mishra, K. S. Sahoo, N. Z. Jhanjhi, M. Baz, and M. Masud, “A data aggregation approach exploiting spatial and temporal correlation among sensor data in wireless sensor networks,” Electronics, vol. 11, no. 7, p. 989, 2022.

[12] K. Sekar, K. Suganya Devi, and P. Srinivasan, “Energy efficient data gathering using spatio-temporal compressive sensing for wsns,” Wireless Personal Communications, vol. 117, no. 2, pp. 1279–1295, 2021.

[13] M. S. Abood, H. Wang, H. F. Mahdi, M. M. Hamdi, and A. S. Abdullah, “Review on secure data aggregation in wireless sensor networks,” in IOP Conference Series: Materials Science and Engineering, vol. 1076, no. 1. IOP Publishing, 2021, p. 012053.

[14] M. K. Khan, M. Shiraz, Q. Shaheen, S. A. Butt, R. Akhtar, M. A. Khan, and W. Changda, “Hierarchical routing protocols for wireless sensor networks: functional and performance analysis,” Journal of Sensors, vol. 2021, no. 1, p. 7459368, 2021.

[15] J. Li, S. Cheng, Z. Cai, J. Yu, C. Wang, and Y. Li, “Approximate holistic aggregation in wireless sensor networks,” ACM Transactions on Sensor Networks (TOSN), vol. 13, no. 2, pp. 1–24, 2017.

[16] S. Cheng, Z. Cai, J. Li, and H. Gao, “Extracting kernel dataset from big sensory data in wireless sensor networks,” IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 4, pp. 813–827, 2016.

[17] M. Yan, S. Ji, M. Han, Y. Li, and Z. Cai, “Data aggregation scheduling in wireless networks with cognitive radio capability,” in 2014 Eleventh Annual IEEE International Conference on Sensing, Communication, and Networking (SECON). IEEE, 2014, pp. 513–521.

[18] S. Abbasian Dehkordi, K. Farajzadeh, J. Rezazadeh, R. Farahbakhsh, K. Sandrasegaran, and M. Abbasian Dehkordi, “A survey on data aggregation techniques in IoT sensor networks,” Wireless Networks, vol. 26, no. 2, pp. 1243–1263, 2020.

[19] A. Bomnale and S. Malgaonkar, “Power optimization in wireless sensor networks,” in 2018 International conference on communication information and computing technology (ICCICT). IEEE, 2018, pp. 1–6.

[20] W.-K. Yun and S.-J. Yoo, “Q-learning-based data-aggregation-aware energy-efficient routing protocol for wireless sensor networks,” IEEE Access, vol. 9, pp. 10 737–10 750, 2021.

[21] N. Sabor and M. Abo-Zahhad, “A comprehensive survey of intelligent based hierarchical routing protocols for wireless sensor networks,” Nature inspired computing for wireless sensor networks, pp. 197–257, 2020.

[22] M. Arghavani, M. Esmaeili, M. Esmaeili, F. Mohseni, and A. Arghavani, “Optimal energy aware clustering in circular wireless sensor networks,” Ad Hoc Networks, vol. 65, pp. 91–98, 2017.

[23] H. Gizachew Yirga, G. Desalegn Taye, H. Mulugeta Melaku, and G. Pau, “An optimized and energy-efficient ad-hoc on-demand distance vector routing protocol based on dynamic forwarding probability (AODVI),” Journal of Computer Networks and Communications, vol. 2022, Jan 2022.

[24] A. Kumar, H. Shwe, K. Wong, and P. Chong, “Location-based routing protocols for wireless sensor networks: A survey,” Wireless Sensor Network, vol. 9, pp. 25–72, 01 2017.

[25] P. K. Singh, A. K. Prajapati, A. Singh, and R. Singh, “Modified geographical energy-aware routing protocol in wireless sensor networks,” in 2016 International Conference on Emerging Trends in Electrical Electronics Sustainable Energy Systems (ICETEESES), 2016, pp. 208– 212.

[26] Q. Wang, J. Li, Q. Qi, P. Zhou, and D. O. Wu, “An adaptive-location based routing protocol for 3-d underwater acoustic sensor networks,” IEEE Internet of Things Journal, vol. 8, no. 8, pp. 6853–6864, 2021.

[27] W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy efficient communication protocol for wireless microsensor networks,” in Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, 2000, p. 10 pp. vol.2.

[28] P. S. Mehra, M. N. Doja, and B. Alam, “Fuzzy based enhanced cluster head selection (FBECS) for wsn,” Journal of King Saud University - Science, vol. 32, no. 1, pp. 390–401, 2020.

[29] R. S. Kumaran, A. Bagwari, G. Nagarajan, S. S. Kushwah, and R. S. Bhadoria, “Hierarchical routing with optimal clustering using fuzzy approach for network lifetime enhancement in wireless sensor networks,” Mob. Inf. Syst., vol. 2022, Jan 2022.

[30] M. Kaur and A. Munjal, “Data aggregation algorithms for wireless sensor network: A review,” Ad hoc networks, vol. 100, p. 102083, 2020.

[31] S. Sasirekha and S. Swamynathan, “Cluster-chain mobile agent routing algorithm for efficient data aggregation in wireless sensor network,” Journal of Communications and Networks, vol. 19, no. 4, pp. 392–401, 2017.

[32] S. Randhawa and S. Jain, “Dahda: Dynamic adaptive hierarchical data aggregation for clustered wireless sensor networks,” vol. 97, no. 4, 2017.

[33] R. Storn and K. Price, “Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces,” Journal of Global Optimization, vol. 11, pp. 341–359, 01 1997.

[34] M. Daszykowski, B. Walczak, and D. Massart, “Looking for natural patterns in data: Part 1. density-based approach,” Chemometrics and Intelligent Laboratory Systems, vol. 56, pp. 83–92, 05 2001.

[35] O. Younis and S. Fahmy, “Heed: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks,” IEEE Transactions on Mobile Computing, vol. 3, no. 4, pp. 366–379, 2004.

[36] X. Min, S. Wei-ren, J. Chang-jiang, and Z. Ying, “Energy efficient clustering algorithm for maximizing lifetime of wireless sensor networks,” AEU - International Journal of Electronics and Communications, vol. 64, no. 4, pp. 289–298, 2010.

[37] S. Lindsey and C. S. Raghavendra, “PEGASIS: Power-efficient gathering in sensor information systems,” in Proceedings, IEEE aerospace conference, vol. 3. IEEE, 2002, pp. 3–3.

[38] R. Sheikhpour, S. Jabbehdari et al., “A cluster-chain based routing protocol for balancing energy consumption in wireless sensor networks,” International Journal of Multimedia and Ubiquitous Engineering, vol. 7, no. 2, pp. 1–16, 2012.

[39] S. Saginbekov and A. Jhumka, “Many-to-many data aggregation scheduling in wireless sensor networks with two sinks,” Computer Networks, vol. 123, pp. 184–199, 2017.

[40] F. Liu, Y. Wang, M. Lin, K. Liu, and D. Wu, “A distributed routing algorithm for data collection in low-duty-cycle wireless sensor networks,” IEEE Internet of Things Journal, vol. 4, no. 5, pp. 1420–1433, 2017.

[41] V. K. Singh, S. Verma, and M. Kumar, “Privacy preserving in-network aggregation in wireless sensor networks,” Procedia Computer Science, vol. 94, pp. 216–223, 2016, the 11th International Conference on Future Networks and Communications (FNC 2016) / The 13th International Conference on Mobile Systems and Pervasive Computing (MobiSPC 2016) / Affiliated Workshops.

[42] S. Roy, M. Conti, S. Setia, and S. Jajodia, “Secure data aggregation in wireless sensor networks: Filtering out the attacker’s impact,” IEEE Transactions on Information Forensics and Security, vol. 9, no. 4, pp. 681–694, 2014.

[43] A. Poornima and B. Amberker, “SEEDA: Secure end-to-end data aggregation in wireless sensor networks,” in 2010 Seventh International Conference on Wireless and Optical Communications Networks - (WOCN), 2010, pp. 1–5.

[44] R. Maivizhi and P. Yogesh, “Q-learning based routing for in-network aggregation in wireless sensor networks,” Wireless Networks, vol. 27, pp. 1–20, 04 2021.

[45] Aoxiang Feng, Dezun Dong, Fei Lei, Junchao Ma, Enda Yu, Ruiqi Wang, “In-network aggregation for data center networks: A survey”, Computer Communications, Volume 198, 2023, Pages 63-76, ISSN 0140-3664, https://doi.org/10.1016/j.comcom.2022.11.004.

[46] R. E. Mohamed, W. R. Ghanem, A. T. Khalil, M. Elhoseny, M. Sajjad, and M. A. Mohamed, “Energy efficient collaborative proactive routing protocol for wireless sensor network,” Computer Networks, vol. 142, pp. 154–167, 2018.

[47] T. O. Kebeng, S. M. Sheikh, and M. Kgwadi, “Reducing routing overhead with a clustering protocol based on ad hoc distance vector and dynamic source routing protocols,” in 2022 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (ICABCD), 2022, pp. 1–6.

[48] M. E. Haque and U. Baroudi, “Dynamic energy efficient routing protocol in wireless sensor networks,” Wireless Networks, vol. 26, no. 5, p. 3715–3733, Jul 2020.

[49] M. Umar, N. Alrajeh, and A. Mehmood, “SALMA: An efficient state based hybrid routing protocol for mobile nodes in wireless sensor networks,” International Journal of Distributed Sensor Networks, vol. 2016, pp. 1–11, 02 2016.

[50] D. B.D. and F. Al-Turjman, “A hybrid secure routing and monitoring mechanism in IoT-based wireless sensor networks,” Ad Hoc Networks, vol. 97, p. 102022, 2020.

[51] P. Chugh, M. Gupta, S. Indu, G. Chaudhary, M. Khari, and V. Shanmuganathan, “Advanced energy efficient PEGASIS based routing protocol for IoT applications,” Microprocessors and Microsystems, vol. 103, p. 104727, 2023.

[52] K. Biswas, V. Muthukkumarasamy, M. J. M. Chowdhury, X.-W. Wu, and K. Singh, “A multipath routing protocol for secure energy efficient communication in wireless sensor networks,” Computer Networks, vol. 232, p. 109842, 2023.

[53] S. Sankar, S. Ramasubbareddy, A. K. Luhach, A. Nayyar, and B. Qureshi, “CT-RPL: Cluster tree based routing protocol to maximize the lifetime of internet of things,” Sensors, vol. 20, no. 20, 2020.

[54] S. Pourroostaei Ardakani, J. Padget, and M. De Vos, “A mobile agent routing protocol for data aggregation in wireless sensor networks,” International Journal of Wireless Information Networks, vol. 24, pp. 27–41, 2017.

[55] M. Venkatanaresh, R. Yadav, D. Thiyagarajan, S. Yasotha, G. Ramkumar, and P. S. Varma, “Effective proactive routing protocol using smart nodes system,” Measurement: Sensors, vol. 24, p. 100456, 2022.

[56] Singh, S., Chand, S., Kumar, R., Malik, A., & Kumar, B., “NEECP: Novel energy‐efficient clustering protocol for prolonging lifetime of WSNs”, IET Wireless Sensor Systems, 6(5), 151-157, 2016.

[57] P. Jacquet, P. Muhlethaler, T. Clausen, A. Laouiti, A. Qayyum and L. Viennot, "Optimized link state routing protocol for ad hoc networks," Proceedings. IEEE International Multi Topic Conference, IEEE INMIC, pp. 62-68, 2001. doi: 10.1109/INMIC.2001.995315.

[58] Bao Xi-rong, Qie Zhi-tao, Zhang Xue-feng and Zhang Shi, "An efficient Energy Cluster-based Routing Protocol for wireless sensor networks," Chinese Control and Decision Conference, Guilin, China, pp. 4716-4721, 2009 doi: 10.1109/CCDC.2009.5194841.

[59] Nasser, Nidal & Chen, Yunfeng. , “SEEM: Secure and energy-efficient multipath routing protocol for wireless sensor networks”, Computer Communications. 30. 2401-2412. 10.1016/j.comcom.2007.04.014, 2007.

[60] Conti, M.; Kaliyar, P.; Lal, C., “Reliable Group Communication Protocol for Internet of Things”, CORR, abs/1904.04542, 2019.

http://arxiv.org/abs/1904.04542

[61] C. Konstantopoulos, A. Mpitziopoulos, D. Gavalas and G.

Pantziou, “Effective determination of mobile agent

itineraries for data aggregation on sensor networks”, IEEE

transactions on knowledge and data engineering, Vol. 22,

No. 12, pp. 1679–1693, 2010.

[62] V. Kanakaris, D. Ndzi, and G. A. Papakostas, “Sensitivity

analysis of AODV protocol regarding forwarding

probability,” Optik, vol. 127, no. 3, pp. 1016–1021, 2016.

[63] N. Nicolaou, A. See, X. Peng, C. Jun-Hong, and D. Maggiorini, “Improving the robustness of location-based routing for underwater sensor networks,” in Proc. OCEANS Europe, pp. 1–6, 2007.

[64] P. S. Mehra, M. N. Doja, and B. Alam, “Fuzzy based enhanced cluster head selection (FBECS) for WSN,” Journal of King Saud University Science, vol. 32, no. 1, pp. 390–401, 2020.

[65] Hasan, Al-R, Ali, Al-A, Khaldoun, B., Amer, A. A., & Mel, R. Y., “Efficient routing LEACH (ER-LEACH) enhanced on LEACH protocol in wireless sensor networks”, Part I, International Journal of Academic Research, 3(3), 42–48, 2011.

[66] O. Younis and S. Fahmy, "HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks," in IEEE Transactions on Mobile Computing, vol. 3, no. 4, pp. 366-379, Oct.-Dec. 2004.

doi: 10.1109/TMC.2004.41.

[67] R. Sheikhpour, S. Jabbehdari, and A. Khademzadeh, “A cluster-chain based routing protocol for balancing energy consumption in wireless sensor networks,” International Journal of Multimedia Ubiquitous Engineering, vol. 7, no. 2, Apr. 2012.

[68] Mini, R. A., Nath, B., & Loureiro, A. A., “A probabilistic approach to predict the energy consumption in wireless sensor networks”, In IV Workshop de Comunicao sem Fio e Computao Mvel (pp. 23–25), 2002.

[69] Li, X., Liu, A., Xie, M., Xiong, N. N., Zeng, Z., & Cai, Z., “Adaptive aggregation routing to reduce delay for multi-layer wireless sensor networks”. Sensors, 18(4), 1216, 2018.

[70] Krco, Srdjan, and Marina Dupcinov. "Improved neighbor detection algorithm for AODV routing protocol." IEEE Communications Letters 7.12, pp. 584-586, 2003.

[71] S. Lai and B. Ravindran, "On Distributed Time-Dependent Shortest Paths over Duty-Cycled Wireless Sensor Networks,", Proceedings IEEE INFOCOM, San Diego, CA, USA, pp. 1-9, 2010