A Hybrid Multi-Objective Optimization-Based Residual Energy and Distance-Aware Routing Protocol for Scalable Wireless Sensor Networks
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Abstract
The routing protocol of wireless sensor networks (WSNs) needs to be capable of conserving the energy of a node, delivering the packets reliably and being scalable as node density increases. In this paper, a Hybrid MOO (multi-objective optimization) based Residual Energy and Distance aware Routing Protocol (HDE-RO) has been proposed for scalable wireless sensor network, where route/convergence path formation is based on residual energy, Euclidean transmission distance, relay-load balance and congestion- aware forwarding cost. The non-dominated evolutionary search is combined with the particle-based local refinement proposed to search for efficient and sustainable source-to-sink routes in the solution space. A MATLAB-based simulation environment was designed and the performance of the protocol was analyzed as the tested number of nodes were 100, 200, and 300 comparing with the DSR, AODV, GA-AODV, and PSO-AODV. In the 100-node scenario, our proposed protocol obtains the packet delivery ratio of 98.2%, the average end-to-end delay of 24.8 ms, the routing overhead of 862 control packets, the fairness index of 0.96 along with the first-node-death round of 1167 and the last-node-death round of 3475. This protocol increases the stability period by 57.3% and decreases the average delay by 37.5% when compared to traditional AODV. In the case of 300 nodes, the packet delivery ratio was still 96. 3% and the fairness index was 0.93, indicating good scalability. Statistical analyses of 30 independent experiments also verified that the improvement in the packet delivery ratio, network lifetime, and energy efficiency were significant, with p-values less than 0.01. The results indicate that the proposed routing protocol smother the formation of energy hole, balances the usage of relays and ensures WSN performance for a long term.
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[1] X. Yang, J. Yan, D. Wang, Y. Xu, and G. Hua, “THSI-RP: A Two-Tier Hybrid Swarm Intelligence Based Node Clustering and Multi-Hop Routing Protocol Optimization for Wireless Sensor Networks,” Ad Hoc Networks, vol. 149, art. 103255, 2023, doi: 10.1016/j.adhoc.2023.103255.
[2] A. Benelhouri, H. Idrissi-Saba, and J. Antari, “An Improved Gateway-Based Energy-Aware Multi-Hop Routing Protocol for Enhancing Lifetime and Throughput in Heterogeneous WSNs,” Simulation Modelling Practice and Theory, vol. 116, art. 102471, 2022.
[3] H. Hu, X. Fan, and C. Wang, “Energy Efficient Clustering and Routing Protocol Based on Quantum Particle Swarm Optimization and Fuzzy Logic for Wireless Sensor Networks,” Scientific Reports, vol. 14, art. 18595, 2024, doi: 10.1038/s41598-024-69360-0.
[4] W. Zeng, Z. Wang, S. Yang, and J. Wang, “LEMH: Low-Energy-First Electoral Multipath Alternating Multihop Routing Algorithm for Wireless Sensor Networks,” IEEE Sensors Journal, vol. 22, no. 16, pp. 16687–16704, 2022, doi: 10.1109/JSEN.2022.3191321.
[5] M. K. Roberts and P. Ramasamy, “Optimized Hybrid Routing Protocol for Energy-Aware Cluster Head Selection in Wireless Sensor Networks,” Digital Signal Processing, vol. 130, art. 103737, 2022.
[6] J. Wang, Z. Wang, and L. Zhang, “A Simultaneous Wireless Information and Power Transfer-Based Multi-Hop Uneven Clustering Routing Protocol for EH-Cognitive Radio Sensor Networks,” Big Data and Cognitive Computing, vol. 8, no. 2, art. 15, 2024.
[7] A. S. H. Abdul-Qawy et al., “An Enhanced Energy Efficient Protocol for Large-Scale IoT-Based Heterogeneous WSNs,” Scientific African, vol. 21, art. e01807, 2023.
[8] S. El Khediri, A. Selmi, R. U. Khan, T. Moulahi, and P. Lorenz, “Energy Efficient Cluster Routing Protocol for Wireless Sensor Networks Using Hybrid Metaheuristic Approaches,” Ad Hoc Networks, vol. 158, art. 103473, 2024, doi: 10.1016/j.adhoc.2024.103473.
[9] J. Wan and J. Chen, “AHP Based Relay Selection Strategy for Energy Harvesting Wireless Sensor Networks,” Future Generation Computer Systems, vol. 128, pp. 36–44, 2022.
[10] Z. Wang, L. Shao, S. Yang, J. Wang, and D. Li, “CRLM: A Cooperative Model Based on Reinforcement Learning and Metaheuristic Algorithms of Routing Protocols in Wireless Sensor Networks,” Computer Networks, vol. 236, art. 110019, 2023.
[11] Y. Liu, H. Huang, and J. Zhou, “A Dual Cluster Head Hierarchical Routing Protocol for Wireless Sensor Networks Based on Hybrid Swarm Intelligence Optimization,” IEEE Internet of Things Journal, vol. 11, no. 9, pp. 16710–16721, 2024, doi: 10.1109/JIOT.2024.3355993.
[12] A. Naeem, A. R. Javed, M. Rizwan, S. Abbas, J. C.-W. Lin, and T. R. Gadekallu, “DARE-SEP: A Hybrid Approach of Distance Aware Residual Energy-Efficient SEP for WSN,” IEEE Transactions on Green Communications and Networking, vol. 5, no. 2, pp. 611–621, 2021, doi: 10.1109/TGCN.2021.3067885.
[13] V. Prakash and S. Pandey, “Metaheuristic Algorithm for Energy Efficient Clustering Scheme in Wireless Sensor Networks,” Microprocessors and Microsystems, vol. 101, art. 104898, 2023.
[14] N. Li, W. K. G. Seah, Z. Hou, B. Jia, B. Huang, and W. Li, “An Energy Aware Adaptive Clustering Protocol for Energy Harvesting Wireless Sensor Networks,” in Proceedings of the 18th International Symposium on Spatial and Temporal Data, pp. 161–170, 2023.
[15] J. Wang, Z. Xie, and C. Liu, “Multi-Hop Clustering Routing Protocol Design Based on Simultaneous Wireless Information and Power Transfer Technology and Imperfect Spectrum Sensing for EH-CRSNs,” Scientific Reports, vol. 14, art. 6686, 2024.
[16] M. A. Tawfeek, I. Alrashdi, M. Alruwaili, and F. M. Talaat, “A Fuzzy Multi-Objective Framework for Energy Optimization and Reliable Routing in Wireless Sensor Networks via Particle Swarm Optimization,” Computers, Materials & Continua, vol. 83, no. 2, pp. 2773–2792, 2025, doi: 10.32604/cmc.2025.061773.
[17] S. A. Sert and A. Yazici, “Increasing Energy Efficiency of Rule-Based Fuzzy Clustering Algorithms Using CLONALG-M for Wireless Sensor Networks,” Applied Soft Computing, vol. 109, art. 107510, 2021, doi: 10.1016/j.asoc.2021.107510.
[18] I. Daanoune, A. Baghdad, and W. Ullah, “Adaptive Coding Clustered Routing Protocol for Energy Efficient and Reliable WSN,” Physical Communication, vol. 52, art. 101705, 2022.
[19] A. K. Sangaiah et al., “Energy-Aware Geographic Routing for Real-Time Workforce Monitoring in Industrial Informatics,” IEEE Internet of Things Journal, vol. 8, no. 12, pp. 9753–9762, 2021.
[20] M. Kaedi, A. Bohlooli, and R. Pakrooh, “Simultaneous Optimization of Cluster Head Selection and Inter-Cluster Routing in Wireless Sensor Networks Using a 2-Level Genetic Algorithm,” Applied Soft Computing, vol. 128, art. 109444, 2022, doi: 10.1016/j.asoc.2022.109444.
[21] H. Alsuwat and E. Alsuwat, “Energy-Aware and Efficient Cluster Head Selection and Routing in Wireless Sensor Networks Using Improved Artificial Bee Colony Algorithm,” Peer-to-Peer Networking and Applications, vol. 18, art. 65, 2025, doi: 10.1007/s12083-024-01810-y.
[22] . Z. Peng, M. S. Jabloo, Y. D. Navaei, M. Hosseini, R. J. Oskouei, P. Pirozmand, and S. Mirkamali, “An improved energy-aware routing protocol using multiobjective particular swarm optimization algorithm,” Wireless Communications and Mobile Computing, vol. 2021, Art. no. 6677961, pp. 1–16, 2021, doi: 10.1155/2021/6677961.
[23] X. Chai, Y. Wu, and L. Feng, “Energy-Efficient Scalable Routing Algorithm Based on Hierarchical Agglomerative Clustering for Wireless Sensor Networks,” Alexandria Engineering Journal, vol. 120, pp. 95–105, 2025, doi: 10.1016/j.aej.2025.02.018.
[24] H. Zhang, M. Zhang, T. Qin, W. Wei, Y. Fan, and J. Yang, “An Energy Consumption Optimization Strategy for Wireless Sensor Networks via Multi-Objective Algorithm,” Journal of King Saud University - Computer and Information Sciences, vol. 36, art. 101919, 2024, doi: 10.1016/j.jksuci.2024.101919.
[25] M. F. Tewelgne, S. A. Demilew, and D. W. Girmaw, “Energy Efficient Inter-Cluster Multi-Hop Communication Routing Protocol for Wireless Sensor Network Based on Centralized Energy Efficient Clustering Routing Protocol,” Discover Applied Sciences, vol. 7, no. 7, art. 738, 2025.
[26] S. M. Bozorgi, M. R. Hajiabadi, A. A. R. Hosseinabadi, and A. K. Sangaiah, “Clustering Based on Whale Optimization Algorithm for IoT over Wireless Nodes,” Soft Computing, vol. 25, pp. 5663–5682, 2021.
[27] W. Zeng, Z. Wang, S. Yang, D. He, and S. Chan, “ICMH-CHR: An Intra-Cluster Multi-Hop Based Cluster Head Rotation Protocol for Wireless Sensor Networks,” Ad Hoc Networks, vol. 173, art. 103829, 2025, doi: 10.1016/j.adhoc.2025.