Energy-Efficient Traffic Management Scheme for Wireless Sensor Network

PDF (1949KB), PP.29-46

Views: 0 Downloads: 0

Author(s)

Shailaja S. Halli 1,* Poornima G. Patil 1

1. Visvesvaraya Technological University-RRC, Jnana Sangama, Belagavi, Karnataka, 590018, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijcnis.2025.06.03

Received: 18 Jun. 2025 / Revised: 11 Aug. 2025 / Accepted: 8 Oct. 2025 / Published: 8 Dec. 2025

Index Terms

Wireless Sensor Networks (WSN), Energy Traffic, Water Wave Optimization, Game Theory, Fuzzy Logic Control

Abstract

Densely distributed nodes and high data flow rates close to sinks can cause serious problems for WSNs, especially concerning energy consumption and network complexity. As node and channel traffic management is essential for energy efficiency, not much research has been done on how to solve these problems. This paper presented a novel method that uses a Water Wave Game Theory algorithm to identify and characterize traffic areas that use less energy. Based on different network parameters, the algorithm calculates a fitness function that estimates player stability. Mobile sinks and nearby nodes are notified when the fitness level is low, anticipating energy-efficient traffic patterns and implicitly establishing an alarm threshold. Establish the LAFLC algorithm to tackle complex energy-efficient traffic scenarios. This algorithm optimizes system decisions about mobile data collectors, routing, and node mobility by dynamically learning and adapting to the characteristics of energy-efficient traffic. As a result, it eliminates the need for data rerouting and the replacement of multiple traffic nodes when mobile data collectors are in motion. The proposed approach demonstrates a superior Packet Delivery Ratio (PDR) of 99.95%, throughput of 3500bps, energy consumption of 0.39J, reliability of 98.8% and energy efficiency of 99.9% compared to existing techniques.

Cite This Paper

Shailaja S. Halli, Poornima G. Patil, "Energy-Efficient Traffic Management Scheme for Wireless Sensor Network", International Journal of Computer Network and Information Security(IJCNIS), Vol.17, No.6, pp.29-46, 2025. DOI:10.5815/ijcnis.2025.06.03

Reference

[1]Inayat, U., Ali, F., Khan, H. M. A., Ali, S. M., Ilyas, K., & Habib, H. (2021). Wireless Sensor Networks: Security, Threats, and Solutions. In 2021 International Conference on Innovative Computing (ICIC), 1-6. 
[2]Balmuri, K. R., Sujatha, J., Arvind, S., Lal, B., &Kumari, S. (2023). An Energy Efficient and Reliable Strategies for Intra-Cluster and Inter-Cluster Communications in Wireless Sensor Networks. In 2023 IEEE International Conference on Integrated Circuits and Communication Systems (ICICACS), 1-8.
[3]Raut, A. R., Khandait, S. P., & Dongre, S. S. (2021, July). A machine learning based mission critical data transmission protocol in wireless sensor networks. In 2021 6th international conference on communication and electronics systems (ICCES) (pp. 846-852). IEEE.
[4]Jurado-Lasso, F. F., Marchegiani, L., Jurado, J. F., Abu-Mahfouz, A. M., & Fafoutis, X. (2022). A survey on machine learning software-defined wireless sensor networks (ml-SDWSNS): Current status and major challenges. IEEE Access, 10, 23560-23592.
[5]Uppalapati, S. (2020). Energy-Efficient Heterogeneous Optimization Routing Protocol for Wireless Sensor Network. Instrumentation, Mesures, Métrologies, 19(5).
[6]Ullah, A., Khan, F. S., Mohy-Ud-Din, Z., Hassany, N., Gul, J. Z., Khan, M., ... & Rehman, M. M. (2024). A Hybrid Approach for Energy Consumption and Improvement in Sensor Network Lifespan in Wireless Sensor Networks. Sensors, 24(5), 1353.
[7]Jabbar, M. S., Issa, S. S., & Ali, A. H. (2023). Improving WSNs execution using energy-efficient clustering algorithms with consumed energy and lifetime maximization. Indonesian Journal of Electrical Engineering and Computer Science, 29(2), 1122-1131.
[8]Bharany, S., Rehman, A. U., Sadiq, M. T., Farrukh, M., Alharbi, M., Hussain, A., &Issa, G. F. (2023). A Review on the need of Clustering Techniques Used for Wireless Sensor Networks. In 2023 International Conference on Business Analytics for Technology and Security (ICBATS), 1-7. 
[9]Mishra, J. P., Singh, K., & Chaudhary, H. (2023). Research advancements in ocean environmental monitoring systems using wireless sensor networks: a review. TELKOMNIKA (Telecommunication Computing Electronics and Control), 21(3), 513-527.
[10]Hamouda, Y., & Msallam, M. (2020). Variable sampling interval for energy-efficient heterogeneous precision agriculture using Wireless Sensor Networks. Journal of King Saud University-Computer and Information Sciences, 32(1), 88-98.
[11]Shah, B. R., &Yashwanth, N. (2022). Energy-Efficient Routing Protocols for Wireless Sensor Networks. In 2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT), 1-6. 
[12]Zafor, H., Mazumdar, N., & Nag, A. (2022). A comparative study of survey papers based on energy efficient, coverage-aware, and fault tolerant in static sink node of WSN. In 2022 IEEE 9th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), 1-6. 
[13]Qabouche, H., Sahel, A., Badri, A., & El Mourabit, I. (2022). Energy Efficient PSO-based routing protocol for large WSN. In 2022 2nd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET), 1-7. 
[14]Jebaraj, N. S., &Mangal, D. (2023). An Energy Balancing Clustering Based Routing Protocol For Wsn’s. In 2023 6th International Conference on Information Systems and Computer Networks (ISCON), 1-5. 
[15]Sadi, R. P. R., &Dadhirao, C. (2023). An Energy Efficient Routing Protocol based on Melioration in Distributed Energy Efficient Clustering. In 2023 11th International Conference on Internet of Everything, Microwave Engineering, Communication and Networks (IEMECON), 1-5. 
[16]Nachappa, M. N., & TP, S. S. (2022). An Energy Efficient Routing Protocol Using ABC to Increase Network Lifetime of WSN. In 2022 International Interdisciplinary Humanitarian Conference for Sustainability (IIHC), 996-1001. 
[17]Goyal, H., &Tripathi, S. (2022). Efficient scheduling for target coverage in energy harvesting wireless sensor network. In 2022 Second international conference on power, control and computing technologies (ICPC2T), 1-5. 
[18]Samara, G., Almomani, A., Alauthman, M., &Alkasassbeh, M. (2022). Energy efficiency Wireless Sensor Networks Protocols: a Survey. In 2022 International Conference on Emerging Trends in Computing and Engineering Applications (ETCEA), 1-6. 
[19]Prabha, M., Anbarasan, M., Sunithamani, S., &Saranya, M. K. (2023). Hierarchical Fuzzy Methodologies for Energy Efficient Routing Protocol for Wireless Sensor Networks. In 2023 International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT), 989-992. 
[20]Hasan, S., Saxena, A., & Singh, K. (2022). Energy Efficient Modified WSN Routing Protocol with Impact of Range and Scaling Factor: M-EESAA. In 2022 IEEE International Conference on Current Development in Engineering and Technology (CCET), (1-6). 
[21]Hamzah, H. A., Tuah, N., Lim, K. G., Tan, M. K., Zhu, L., &Teo, K. T. K. (2019). Data transmission in wireless sensor network with greedy function and particle swarm optimization. In 2019 IEEE 7th Conference on Systems, Process and Control (ICSPC), 172-177. 
[22]Abd Latif, M. Z., Lim, K. G., Tan, M. K., Chuo, H. S. E., Wang, T., &Teo, K. T. K. (2022). Energy-Efficient Ant Colony Based LEACH Routing Algorithm in Wireless Sensor Network. In 2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET), 1-6. 
[23]Yao, Y. D., Li, X., Cui, Y. P., Wang, J. J., & Wang, C. (2022). Energy-efficient routing protocol based on multi-threshold segmentation in wireless sensors networks for precision agriculture. IEEE Sensors Journal, 22(7), 6216-6231.
[24]Sravanthi, J., Subbayamma, B. V., Sultana, W., Parabrahmachari, S., Krishnan, V. G., &Sriramam, Y. S. (2023). Enhancement of Energy Efficiency using Improved Energy Efficient Routing Protocol in Wireless Sensor Networks for IoT Applications. In 2023 3rd International Conference on Advances in Computing, Communication, Embedded and Secure Systems (ACCESS), 37-40. 
[25]Reddy, A. S., &Malleswari, G. (2023). Adaptive Energy Routing Protocol using Spider Optimization in Wireless Sensor Networks. In 2023 International Conference on Computer Communication and Informatics (ICCCI), 1-6. 
[26]Biabani, M., Yazdani, N., &Fotouhi, H. (2022). EE-MSWSN: Energy-efficient mobile sink scheduling in wireless sensor networks. IEEE Internet of Things Journal, 9(19), 18360-18377.
[27]El-Fouly, F. H., & Ramadan, R. A. (2020). Real-time energy-efficient reliable traffic aware routing for industrial wireless sensor networks. IEEE Access, 8, 58130-58145.
[28]Samarji, N., &Salamah, M. (2021). ERQTM: Energy-efficient routing and QoS-supported traffic management scheme for SDWBANs. IEEE Sensors Journal, 21(14), 16328-16339.
[29]Lu, J., Feng, L., Yang, J., Hassan, M. M., Alelaiwi, A., &Humar, I. (2019). Artificial agent: The fusion of artificial intelligence and a mobile agent for energy-efficient traffic control in wireless sensor networks. Future generation computer systems, 95, 45-51.
[30]Srivastava, V., Tripathi, S., Singh, K., & Son, L. H. (2020). Energy efficient optimized rate based congestion control routing in wireless sensor network. Journal of Ambient Intelligence and Humanized Computing, 11, 1325-1338.
[31]Soundararajan, S., Gunisetti, L., Bhanu Koduri, S., & Kiranmai, B. (2023). Energy efficient congestion control scheme based on Modified Harris Hawks Optimization for heavy traffic Wireless Sensor Networks. Automatika: Journal for Control, Measurement, Electronics, Computing and Communications, 64(4), 1107-1115.
[32]Rajeswari, A. R., Ganapathy, S., Kulothungan, K., & Kannan, A. (2022). Fuzzy based congestion detection and control algorithm for energy efficient wireless sensor network (WSN). Journal of the National Science Foundation of Sri Lanka, 50(3).
[33]Panimalar, S., & Jacob, T. P. (2023). Congestion-Free Cluster Formation and Energy Efficient Path Selection in Wireless Sensor Networks using ButPCNN. IJEER, 11(2), 315-322.
[34]Shelke, M. P., Malhotra, A., &Mahalle, P. (2017). A packet priority intimation-based data transmission for congestion free traffic management in wireless sensor networks. Computers & Electrical Engineering, 64, 248-261.
[35]Ahmed, A. M., & Paulus, R. (2017). Congestion detection technique for multipath routing and load balancing in WSN. Wireless Networks, 23, 881-888.
[36]Li, M., & Jing, Y. (2012, May). Feedback congestion control protocol for wireless sensor networks. In 2012 24th Chinese Control and Decision Conference (CCDC), 4217-4220.