Abstract
Internet of Things (IoT) has sensor nodes (SNs) in its primitive layer for collecting data from an area of interest. These SNs are powered by a battery which is a significant constraint due to its limited capacity(battery) in ad-hoc IoT networks. Since these SNs are deployed in large numbers forming a network, the network’s lifetime is required to be prolonged to serve the objective of deploying the SNs. If the SNs exhaust their energy at par, then the network’s lifetime can easily be extended. For achieving an almost equal energy dissipation rate of SNs, the load among the SNs should be balanced. This paper has propounded a load-balanced, efficient clustering and routing (LBECR) protocol for sustainable IoT in smart cities to muddle through this issue. Since in Adhoc IoT networks, the nodes are resource-constrained, with the escalation of input variables in the fuzzy system, the number of rules increases exponentially, leading to more energy dissipation. Therefore we have designed three Fuzzy Inference Systems with minimal inputs for cluster head (CH) selection, formation of clusters and routing of data. The cost to the CH node is considered as one of the parameters of the Fuzzy system as it has a significant impact on the stability period. A fuzzy system is designed for efficient multi-hop routing, conserving a significant amount of network energy. The proposed LBECR protocol is simulated for four different cases and compared with some recent protocols. The obtained experimental results reveal significant improvement with proficiency in balancing the network load by better average energy, delayed death rate of SNs and prolonged lifetime.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Afsar MM, Tayarani-N MH (2014) Clustering in sensor networks: a literature survey. J Netw Comput Appl 46:198–226. https://doi.org/10.1016/j.jnca.2014.09.005
Alkhawlani M, Ayesh A (2008) Access network selection based on fuzzy logic and genetic algorithms. Adv Artif Intell 793058:12. https://doi.org/10.1155/2008/793058
Baranidharan B, Santhi B (2016) DUCF: distributed load balancing unequal clustering in wireless sensor networks using fuzzy approach. Appl Soft Comput 40:495–506. https://doi.org/10.1016/J.ASOC.2015.11.044
Brincat AA, Pacifici F, Martinaglia S, Mazzola F (2019) The Internet of Things for Intelligent Transportation Systems in Real Smart Cities Scenarios. In: IEEE 5th World Forum on Internet of Things, WF-IoT 2019 - Conference Proceedings, 128–132. https://doi.org/10.1109/WF-IoT.2019.8767247
Chithaluru P, Al-Turjman F, Kumar M, Stephan T (2020) I-AREOR: an energy-balanced clustering protocol for implementing green IoT in smart cities. Sustain Cities Soc 61:102254. https://doi.org/10.1016/j.scs.2020.102254
Dabirmoghaddam A, Ghaderi M, Williamson C (2014) On the optimal randomized clustering in distributed sensor networks. Comput Netw 59:17–32. https://doi.org/10.1016/J.BJP.2013.12.008
Dwivedi AK, Sharma AK (2020) NEEF: a novel energy efficient fuzzy logic based clustering protocol for wireless sensor network. Scalable Comput Pract Exp 21(3):555–568. https://doi.org/10.12694/scpe.v21i3.1749
Dwivedi A, Sharma A, Mehra PS (2020b) Energy-aware routing protocols for wireless sensor network based on fuzzy logic: a 10-years analytical review. EAI Endorsed Trans Energy Web. https://doi.org/10.4108/eai.6-10-2020.166548
Dwivedi AK, Sharma AK, Mehra PS (2020) Energy efficient sensor node deployment scheme for two stage routing protocol of wireless sensor networks assisted iot. ECTI Trans Electr Eng Electron Commun. https://doi.org/10.37936/ecti-eec.2020182.240541
El Alami H, Najid A (2017) Fuzzy logic based clustering algorithm for wireless sensor networks. Int J Fuzzy Syst Appl (IJFSA) 6(4):63–82. https://doi.org/10.4018/IJFSA.2017100105
Gaur A, Scotney B, Parr G, McClean S (2015) Smart City architecture and its applications based on IoT. Procedia Computer Science 52(1):1089–1094. https://doi.org/10.1016/J.PROCS.2015.05.122
Gupta P, Raj P, Tiwari S, Kumari P, Mehra PS (2020) Energy efficient diagonal based clustering protocol in wireless sensor network. SSRN Electron J. https://doi.org/10.2139/ssrn.3565781
Gupta I, Riordan D, Sampalli S (2005) Cluster-Head Election Using Fuzzy Logic for Wireless Sensor Networks. In: 3rd Annual Communication Networks and Services Research Conference (CNSR’05), 255–260. https://doi.org/10.1109/CNSR.2005.27
Haseeb K, Din IU, Almogren A, Islam N (2020) An energy efficient and secure IoT-based WSN framework: an application to smart agriculture. Sensors (switzerland). https://doi.org/10.3390/s20072081
Heinzelman WR, Chandrakasan A, Balakrishnan H (2000) Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, vol.1, 10. https://doi.org/10.1109/HICSS.2000.926982
Jain K, Kumar A (2020) An energy-efficient prediction model for data aggregation in sensor network. J Ambient Intell Hum Comput 11(11):5205–5216. https://doi.org/10.1007/S12652-020-01833-2
Kavitha BC, Vallikannu R (2019) IoT Based Intelligent Industry Monitoring System. In: 2019 6th International Conference on Signal Processing and Integrated Networks, SPIN 2019, pp 63–65. https://doi.org/10.1109/SPIN.2019.8711597
Kim J, Park S, Han Y, Chung T (2008) CHEF: Cluster Head Election mechanism using Fuzzy logic in Wireless Sensor Networks. In: Proceedings of 10th International Conference on Advanced Communication Technology, pp 654–659. https://doi.org/10.1109/ICACT.2008.4493846
Kumar N, Dash D (2020) Flow based efficient data gathering in wireless sensor network using path-constrained mobile sink. J Ambient Intell Humaniz Comput 11(3):1163–1175. https://doi.org/10.1007/s12652-019-01245-x
Kumaresan K, Kalyani SN (2020) Energy efficient cluster based multilevel hierarchical routing for multi-hop wireless sensor network. J Ambient Intell Humaniz Comput 1:3. https://doi.org/10.1007/s12652-020-01700-0
Lazarescu MT (2016) Wireless sensor networks for the internet of things: Barriers and synergies. In; Components and Services for IoT Platforms: Paving the Way for IoT Standards (pp. 155–186). Springer International Publishing. https://doi.org/10.1007/978-3-319-42304-3_9
Lenka RK, Rath AK, Sharma S (2019) Building reliable routing infrastructure for green IoT network. IEEE Access. https://doi.org/10.1109/ACCESS.2019.2939883
Logambigai R, Kannan A (2016) Fuzzy logic based unequal clustering for wireless sensor networks. Wirel Netw 22(3):945–957. https://doi.org/10.1007/s11276-015-1013-1
Mamdani HE (1977) Application of fuzzy logic to approximate reasoning using linguistic synthesis. IEEE Trans Comput 26(12):1182–1191. https://doi.org/10.1109/TC.1977.1674779
Mazumdar N, Om H (2018) Distributed fuzzy approach to unequal clustering and routing algorithm for wireless sensor networks. Int J Commun Syst 31(12):e3709. https://doi.org/10.1002/dac.3709
Mehra PS (2021) E-FUCA: enhancement in fuzzy unequal clustering and routing for sustainable wireless sensor network. Complex Intell Syst. https://doi.org/10.1007/S40747-021-00392-Z
Mehra PS, Doja MN, Alam B (2019) Enhanced clustering algorithm based on fuzzy logic (E-CAFL) for WSN. Scalable Comput Pract Exp 20(1):41–54. https://doi.org/10.12694/scpe.v20i1.1443
Mehra PS, Doja MN, Alam B (2020) Fuzzy based enhanced cluster head selection (FBECS) for WSN. J King Saud Univ Sci 32(1):390–401. https://doi.org/10.1016/J.JKSUS.2018.04.031
Mehra PS, Doja MN, Alam B (2018) Stable Period Extension for Heterogeneous Model in Wireless Sensor Network. In: Advances in Intelligent Systems and Computing (Vol. 638, pp 479–487). Springer, Singapore. https://doi.org/10.1007/978-981-10-6005-2_48
Memon I, Hasan MK, Shaikh RA, Nebhen J, Bakar KAA, Hossain E, Tunio MH (2021) Energy-efficient fuzzy management system for internet of things connected vehicular Ad Hoc networks. Electronics 10(9):1068. https://doi.org/10.3390/ELECTRONICS10091068
Mohamed RE, Ghanem WR, Khalil AT, Elhoseny M, Sajjad M, Mohamed MA (2018) Energy efficient collaborative proactive routing protocol for wireless sensor network. Comput Netw 142:154–167. https://doi.org/10.1016/J.COMNET.2018.06.010
Nayak P, Devulapalli A (2016) A fuzzy logic-based clustering algorithm for WSN to extend the network lifetime. IEEE Sens J 16(1):137–144. https://doi.org/10.1109/JSEN.2015.2472970
Pirbhulal S, Zhang H, Alahi EM, Ghayvat H, Mukhopadhyay S, Zhang Y-T, Wu W (2016) A novel secure IoT-based smart home automation system using a wireless sensor network. Sensors 17(12):69. https://doi.org/10.3390/s17010069
Ran G, Zhang H, Gong S (2010) Improving on LEACH protocol of wireless sensor networks using fuzzy logic. J Inf Comput Sci 7(3):767–775. https://doi.org/10.1109/SENSORCOMM.2007.21
Rattan KS, Van Cleave D (2000) Design and implementation of a reduced rule fuzzy logic PID controller. In: Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS, pp 465–469. https://doi.org/10.1109/nafips.2000.877475
Rawat P, Chauhan S (2020) Probability based cluster routing protocol for wireless sensor network. J Ambient Intell Humaniz Comput 1:3. https://doi.org/10.1007/s12652-020-02307-1
Roy NR, Chandra P (2020) Threshold sensitive clustering in SEP. Sustain Comput Inform Syst 25:100367. https://doi.org/10.1016/j.suscom.2019.100367
Sethi P, Sarangi SR (2017) Internet of things: architectures, protocols, and applications. J Electr Comput Eng. https://doi.org/10.1155/2017/9324035
Shahraki A, Taherkordi A, Haugen O, Eliassen F (2020) A survey and future directions on clustering: from WSNs to IoT and modern networking paradigms. IEEE Trans Netw Serv Manag. https://doi.org/10.1109/TNSM.2020.3035315
Smaragdakis G, Matta I, Bestavros A (2004) SEP: A Stable Election Protocol for clustered heterogeneous wireless sensor networks
Syed AS, Sierra-Sosa D, Kumar A, Elmaghraby A (2021) IoT in Smart Cities: a survey of technologies, practices and challenges. Smart Cities 4(2):429–475. https://doi.org/10.3390/SMARTCITIES4020024
Tanwar S, Kumar N, Niu J-W (2014) EEMHR: energy-efficient multilevel heterogeneous routing protocol for wireless sensor networks. Int J Commun Syst 27(9):1289–1318. https://doi.org/10.1002/dac.2780
Yarinezhad R, Hashemi SN (2020) A sensor deployment approach for target coverage problem in wireless sensor networks. J Ambient Intell Humaniz Comput 1:3. https://doi.org/10.1007/s12652-020-02195-5
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Mehra, P.S. LBECR: load balanced, efficient clustering and routing protocol for sustainable internet of things in smart cities. J Ambient Intell Human Comput 14, 10493–10515 (2023). https://doi.org/10.1007/s12652-022-03706-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-022-03706-2