A Routing Method for Extending Network Lifetime in Wireless Sensor Networks Using Improved PSO
Source abstract
Abstract
WSNs consist of numerous energy-constrained Sensor Nodes (SNs), making energy efficiency a critical challenge. This paper presents a novel multipath routing model designed to enhance network lifetime by simultaneously optimizing energy consumption, node connectivity, and transmission distance. The model employs an Improved Particle Swarm Optimization (IPSO) algorithm to dynamically determine the optimal weight coefficients of a cost function that integrates three parameters: residual energy, link reliability, and buffer capacity. A compressed Bloom filter is incorporated to improve packet transmission efficiency and reduce error rates. Simulation experiments conducted in the NS2 environment show that the proposed approach significantly outperforms existing protocols, including Reinforcement Learning Q-Routing Protocol (RL-QRP), Low Energy Adaptive Clustering Hierarchical (LEACH), On-Demand Distance Vector (AODV), Secure and Energy-Efficient Multipath (SEEM), and Energy Density On-demand Cluster Routing (EDOCR), achieving a 7.45% reduction in energy consumption and maintaining a higher number of active nodes over time. Notably, the model sustains 19 live nodes at round 800, whereas LEACH and APTEEN experience complete node depletion by that point. This adaptive, energy-aware routing strategy improves reliability, prolongs operational lifespan, and enhances load balancing, making it a promising solution for real-world WSN applications.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Energy Efficient Wireless Sensor Networks · IoT-based Smart Home Systems · Wireless Body Area Networks
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Electrical Engineering, Ah.C., Islamic Azad University, Ahar, Iran
Funding
Mohsen Ebadpour
References (45)
Show source-provided references
1. Systematic study of topology control methods and routing techniques in wireless sensor networks10.1007/s12083-022-01325-4 ↗
2. Mobility target tracking with meta-heuristic aided target movement prediction scheme in WSN using adaptive distributed extended Kalman filtering10.1002/dac.5789 ↗
3. QoS-based routing protocol and load balancing in wireless sensor networks using the markov model and the artificial bee colony algorithm10.1007/s12083-023-01502-z ↗
4. A multiple pheromone ant colony optimization scheme for energy-efficient wireless sensor networks10.1007/s00500-019-03933-4 ↗
5. An enhanced bio-inspired energy-efficient localization routing for mobile wireless sensor network10.1002/dac.5803 ↗
6. Cluster-based data transmission scheme in wireless sensor networks using black hole and ant colony algorithms10.1002/dac.4768 ↗
7. Block chain technology for secured dynamic optimal routing in WSN with optimized generative adversarial capsule network10.1002/dac.5711 ↗
8. Data-centric multiobjective QoS-aware routing protocol for body sensor networks10.3390/s110100917 ↗
9. Cluster-based flow control in hybrid software-defined wireless sensor networks10.1016/j.comnet.2020.107788 ↗
10. An efficient routing protocol for the QoS support of large-scale MANETs10.1002/dac.3384 ↗
11. Ghadiri, S., and Khorsandi, S. (2019, January 24–25). Data Integration in Wireless Sensor Networks Using the Bloom Filters. Proceedings of the 2019 5th International Conference on Web Research (ICWR), Tehran, Iran.10.1109/ICWR.2019.8765260 ↗
12. Wood, A., Virone, G., Doan, T., Cao, Q., Selavo, L., Wu, Y., Fang, L., He, Z., Lin, S., and Stankovic, J. (2008). ALARM-NET: Wireless Sensor Networks for Assisted-Living and Residential Monitoring, Department of Computer Science, University of Virginia.10.1109/MNET.2008.4579768 ↗
13. Energy-aware Peering Routing Protocol for indoor hospital Body Area Network Communication10.1016/j.procs.2012.06.027 ↗
14. RISA: Routing scheme for Internet of Things using shuffled frog leaping optimization algorithm10.1007/s12652-020-01708-6 ↗
15. A clustering WSN routing protocol based on node energy and multipath10.1007/s10586-017-1550-8 ↗
16. Path Generation Protocol to Improve Lifetime of WSN10.1016/j.procs.2023.01.088 ↗
17. Jiang, S., Cao, Y., Iyengar, S., Kuryloski, P., Jafari, R., Xue, Y., Bajcsy, R., and Wicker, S. (2008, January 13–17). CareNet: An Integrated Wireless Sensor Networking Environment for Remote Healthcare. Proceedings of the ICST 3rd International Conference on Body Area Networks, Tempe, AZ, USA.10.4108/ICST.BODYNETS2008.2965 ↗
18. Li, S., Kim, J.G., Han, D., and Lee, K.S. (2019). A Survey of Energy-Efficient Communication Protocols with QoS Guarantees in Wireless Multimedia Sensor Networks. Sensors, 19.10.3390/s19010199 ↗
19. Prolonging the Lifetime of Wireless Sensor Networks: A Review of Current Techniques10.1155/2018/8035065 ↗
20. Kennedy, J., and Eberhart, R. (December, January 27). Particle swarm optimization. Proceedings of the ICNN’95—International Conference on Neural Networks, Perth, WA, Australia.
21. Fuzzy logic with honey badger algorithm for cluster-based multi-hop routing protocol for wireless sensor networks10.1002/dac.5810 ↗
22. Hybrid grey wolf sunflower optimisation algorithm for energy-efficient cluster head selection in wireless sensor networks for lifetime enhancement10.1049/cmu2.12072 ↗
23. Improved buffalo optimized deep feed forward neural learning based multipath routing for energy efficient data aggregation in WSN10.1016/j.measen.2022.100662 ↗
24. Adaptive coding clustered routing protocol for energy efficient and reliable WSN10.1016/j.phycom.2022.101705 ↗
25. An evolutionary routing protocol for load balancing and QoS enhancement in IoT enabled heterogeneous WSNs10.1016/j.simpat.2023.102729 ↗
26. MOCRAW: A Meta-heuristic Optimized Cluster head selection based Routing Algorithm for WSNs10.1016/j.adhoc.2022.103079 ↗
27. Energy conservation using PISAE and cross-layer-based opportunistic routing protocol (CORP) for wireless sensor network
28. A multipath routing protocol for secure energy efficient communication in Wireless Sensor Networks10.1016/j.comnet.2023.109842 ↗
29. Proposing an Energy-Aware Routing Protocol by Using Fish Swarm Optimization Algorithm in WSN (Wireless Sensor Networks)10.1007/s11277-021-08312-7 ↗
30. A Qos-Aware, Hybrid Particle Swarm Optimization-Cuckoo Search Clustering Based Multipath Routing in Wireless Sensor Networks10.1007/s11277-021-08745-0 ↗
31. An Energy-Aware Multilayer Clustering-Based Butterfly Optimization Routing for Underwater Wireless Sensor10.1007/s11277-021-09042-6 ↗
32. Competitive swarm optimization based unequal clustering and routing algorithms (CSO-UCRA) for wireless sensor networks10.1007/s11042-021-10901-4 ↗
33. Energy-Aware Clustering-Based Routing in Wireless Sensor Networks Using Cuckoo Optimization Algorithm10.1007/s11277-017-4983-8 ↗
34. A Novel Oppositional Artificial Fish Swarm based clustering with improved moth flame optimization based Routing Protocol for Wireless Sensor Networks
35. Automata Based Hybrid PSO–GWO Algorithm for Secured Energy Efficient Optimal Routing in Wireless Sensor Network10.1007/s11277-020-07882-2 ↗
36. Compressed Bloom filters10.1109/TNET.2002.803864 ↗
37. Patgiri, R., Nayak, S., and Muppalaneni, N.B. (2023). Chapter 2—Bloom Filters: A powerful membership data structure. Bloom Filter, Academic Press.10.1016/B978-0-12-823520-1.00007-9 ↗
38. Heinzelman, W.R., Chandrakasan, A., and Balakrishnan, H. (2000, January 7). Energy-efficient communication protocol for wireless microsensor networks. Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, Maui, HI, USA.
39. Liang, X., Balasingham, I., and Byun, S.-S. (2008, January 25–28). A reinforcement learning based routing protocol with QoS support for biomedical sensor networks. Proceedings of the 2008 First International Symposium on Applied Sciences on Biomedical and Communication Technologies, Aalborg, Denmark.
40. Lindsey, S., and Raghavendra, C.S. (2002, January 9–16). PEGASIS: Power-efficient gathering in sensor information systems. Proceedings of the IEEE Aerospace Conference, Big Sky, MT, USA.
41. HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks10.1109/TMC.2004.41 ↗
42. Manjeshwar, A., and Agrawal, D.P. (2002, January 15–19). APTEEN: A hybrid protocol for efficient routing and comprehensive information retrieval in wireless. Proceedings of the 16th International Parallel and Distributed Processing Symposium, Fort Lauderdale, FL, USA.10.1109/IPDPS.2002.1016600 ↗
43. SEEM: Secure and energy-efficient multipath routing protocol for wireless sensor networks10.1016/j.comcom.2007.04.014 ↗
44. EDOCR: Energy Density On-demand Cluster Routing in Wireless Sensor Networks
45. A constraint-based parallel local search for the edge-disjoint rooted distance-constrained minimum spanning tree problem10.1007/s10732-017-9342-0 ↗