Improving Node Efficiency in Wireless Sensor Networks Using Advanced Clustering and Routing Techniques

Year : 2024 | Volume :11 | Issue : 02 | Page : 35-64
By

Akash Goswami,

Shruti Dixit,

Aaradhna Soni,

  1. Student, Department of Electronics and Telecommunication Engineering, Sanjeev Agrawal Global Educational (SAGE) University, Bhopal, Madhya Pradesh, India
  2. Professor, Department of Electronics and Telecommunication Engineering, Sanjeev Agrawal Global Educational (SAGE) University, Bhopal, Madhya Pradesh, India
  3. Professor, Department of Electronics and Telecommunication Engineering, Sanjeev Agrawal Global Educational (SAGE) University, Bhopal, Madhya Pradesh, India

Abstract

Many Internet of Things (IoT) applications, such as disaster relief, smart buildings, smart farming, and healthcare monitoring, have made use of wireless sensor networks (WSN). It is one of the alternatives to address different IoT difficulties in different contexts. One of the main problems with sensor networks is power efficiency. WSN operated on the Client-Server (CS) architecture in the past, however researchers suggested Mobile Agent (MA) based WSN to increase energy efficiency. An effective clustering and routing strategy for enhancing node performance in WSN was proposed in the dissertation. ECR, an effective clustering and routing technology, is suggested for dependable and effective data gathering in large-scale wireless sensor networks. The network architecture created by ECR will be shown to be connected and efficient through theoretical analysis and simulation results.According to simulation results, the suggested effective clustering and routing method outperforms earlier findings in terms of node life time, node dead time, throughput, energy, and mobile agent. The simulation’s output demonstrates how the suggested work and the earlier work technique compare. A total of 500 by 500 meters was used for the simulation, and 1000 nodes were simulated. The prior strategy was based on a novel method, but the proposed method is based on a combined cluster. The suggested solution achieves a network transfer rate or throughput of 275 Kbps, compared to the prior 250 Kbps. It follows that the suggested methodology produces noticeably better results than the earlier strategy.

Keywords: Wireless Sensor Network (WSN), Internet of Things (IOT), Mobile agent, clustering, Efficient Clustering And Routing (ECR).

[This article belongs to Recent Trends in Sensor Research & Technology (rtsrt)]

How to cite this article:
Akash Goswami, Shruti Dixit, Aaradhna Soni. Improving Node Efficiency in Wireless Sensor Networks Using Advanced Clustering and Routing Techniques. Recent Trends in Sensor Research & Technology. 2024; 11(02):35-64.
How to cite this URL:
Akash Goswami, Shruti Dixit, Aaradhna Soni. Improving Node Efficiency in Wireless Sensor Networks Using Advanced Clustering and Routing Techniques. Recent Trends in Sensor Research & Technology. 2024; 11(02):35-64. Available from: https://journals.stmjournals.com/rtsrt/article=2024/view=177146


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References

  1. Phommasan, Widyawan and I. W. Mustika, “Cluster Selection Technique with Fuzzy Logic-based Wireless Sensor Network to increase the lifetime of networks,” 2022 5th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), Yogyakarta, Indonesia, 2022, pp. 40-46, doi: 10.1109/ISRITI56927.2022.10052871.
  2. Malik, A. Joshi and G. Sakya, “Various Optimization Algorithms for Enhancing Network Lifetime in LEACH Protocol in WSN,” 2022 8th International Conference on Signal Processing and Communication (ICSC), Noida, India, 2022, pp. 215-219, doi: 10.1109/ICSC56524.2022.10009415.
  3. Padmavathy, V. S. Akshaya, R. Menaha and S. P. Raja, “Hybrid Cluster Head Selection Approach for Node Lifetime Enhancement in Wireless Sensor Networks,” 2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Dharan, Nepal, 2022, pp. 227-236, doi: 10.1109/I- SMAC55078.2022.9987316.
  4. Rohilla, Himanshu, H. Kumar and P. S. Mehra, “Grey wolf and Fuzzy logic based enhanced clustering approach for energy efficient operation of wireless sensor networks,” 2022 7th International Conference on Communication and Electronics Systems (ICCES), Coimbatore, India, 2022, pp. 595-602, doi: 10.1109/ICCES54183.2022.9835880.
  5. Gamal, N. E. Mekky, H. H. Soliman and N. A. Hikal, “Enhancing the Lifetime of Wireless Sensor Networks Using Fuzzy Logic LEACH Technique-Based Particle Swarm Optimization,” in IEEE Access, vol. 10, pp. 36935-36948, 2022, doi: 10.1109/ACCESS.2022.3163254.
  6. Mirzaie, A. Mazinani and S. M. Mazinani, “A Fuzzy Cluster-Based Routing Algorithm to Extend Wireless Sensor Network Lifetime,” 2021 12th International Conference on Information and Knowledge Technology (IKT), Babol, Iran, Islamic Republic of, 2021, pp. 46-50, doi: 10.1109/IKT54664.2021.9685956.
  7. Kashyap, A. Jaiswal and M. Kumar, “Fuzzy K-means clustering (FKmC) to maximize the Energy Efficiency in Sensor-Enabled Internet of Things,” 2021 IEEE 4th International Conference on Computing, Power and Communication Technologies (GUCON), Kuala Lumpur, Malaysia, 2021, pp. 1-6, doi: 10.1109/GUCON50781.2021.9573937.
  8. V. Bhaskarwar and D. J. Pete, “Fuzzy Logic Implemented Routing Techniques for Underwater Wireless Sensor Networks,” 2021 2nd International Conference for Emerging Technology (INCET), Belagavi, India, 2021, pp. 1-7, doi: 10.1109/INCET51464.2021.9456144.
  9. Adnan, L. Yang, T. Ahmad and Y. Tao, “An Unequally Clustered Multi-hop Routing Protocol Based on Fuzzy Logic for Wireless Sensor Networks,” in IEEE Access, vol. 9, pp. 38531-38545, 2021, doi: 10.1109/ACCESS.2021.3063097.
  10. Lipare, D. R. Edla and R. Dharavath, “Fuzzy Rule Generation Using Modified PSO for Clustering in Wireless Sensor Networks,” in IEEE Transactions on Green Communications and Networking, vol. 5, no. 2, pp. 846-857, June 2021, doi: 10.1109/TGCN.2021.3060324.
  11. Lata, S. Mehfuz, S. Urooj and F. Alrowais, “Fuzzy Clustering Algorithm for Enhancing Reliability and Network Lifetime of Wireless Sensor Networks,” in IEEE Access, vol. 8, pp. 66013-66024, 2020, doi: 10.1109/ACCESS.2020.2985495.
  12. El Alami and A. Najid, “ECH: An Enhanced Clustering Hierarchy Approach to Maximize Lifetime of Wireless Sensor Networks,” in IEEE Access, vol. 7, pp. 107142-107153, 2019, doi: 10.1109/ACCESS.2019.2933052.
  13. He, X. Fu and Y. Yang, “Energy-Efficient Trajectory Planning Algorithm Based on Multi-Objective PSO for the Mobile Sink in Wireless Sensor Networks,” in IEEE Access, vol. 7, pp. 176204-176217, 2019, doi: 10.1109/ACCESS.2019.2957834.
  14. He, “Energy-Saving Algorithm and Simulation of Wireless Sensor Networks Based on Clustering Routing Protocol,” in IEEE Access, vol. 7, pp. 172505-172514, 2019, doi: 10.1109/ACCESS.2019.2956068.
  15. Osamy, A. M. Khedr, A. Aziz and A. A. El-Sawy, “Cluster-Tree Routing Based Entropy Scheme for Data Gathering in Wireless Sensor Networks,” in IEEE Access, vol. 6, pp. 77372-77387, 2018, doi: 10.1109/ACCESS.2018.2882639.
  16. Phoemphon, C. So-In and N. Leelathakul, “Optimized Hop Angle Relativity for DV-Hop Localization in Wireless Sensor Networks,” in IEEE Access, vol. 6, pp. 78149-78172, 2018, doi: 10.1109/ACCESS.2018.2884837.
  17. Si, J. Wang, C. Yu and H. Zhao, “Energy-Efficient and Fault-Tolerant Evolution Models Based on Link Prediction for Large-Scale Wireless Sensor Networks,” in IEEE Access, vol. 6, pp. 73341-73356, 2018, doi: 10.1109/ACCESS.2018.2882389.
  18. Wu, F. Yao, Y. Chen, Y. Liu and T. Liang, “Cluster-Based Energy Efficient Collaborative Spectrum Sensing for Cognitive Sensor Network,” in IEEE Communications Letters, vol. 21, no. 12, pp. 2722-2725, Dec. 2017, doi: 10.1109/LCOMM.2017.2758376.
  19. Rajeswari and S. Neduncheliyan, “Genetic algorithm based fault tolerant clustering in wireless sensor network,” in IET Communications, vol. 11, no. 12, pp. 1927-1932, 24 8 2017, doi: 10.1049/iet-com.2016.1074.
  20. Sivagami and J. Martin Leo Manickam, “Cluster-Based MAC Protocol for Collision Avoidance and TDMA Scheduling in Underwater Wireless Sensor Networks,” in The Computer Journal, vol. 59, no. 10, pp. 1527-1535, Oct. 2016, doi: 10.1093/comjnl/bxw049.
  21. Ray and D. De, “Energy efficient clustering protocol based on K-means (EECPK-means)-midpoint algorithm for enhanced network lifetime in wireless sensor network,” in IET Wireless Sensor Systems, vol. 6, no. 6, pp. 181-191, 12 2016, doi: 10.1049/iet-wss.2015.0087.
  22. T. A. Quang and D. Kim, “Clustering algorithm of hierarchical structures in large-scale wireless sensor and actuator networks,” in Journal of Communications and Networks, vol. 17, no. 5, pp. 473-481, Oct. 2015, doi: 10.1109/JCN.2015.000085.
  23. Lin, L. Wang and R. Kong, “Energy Efficient Clustering Protocol for Large- Scale Sensor Networks,” in IEEE Sensors Journal, vol. 15, no. 12, pp. 7150-7160, Dec. 2015, doi: 10.1109/JSEN.2015.2471843.
  24. Hamed Javadi and A. Peiravi, “Reliable distributed detection in multi-hop clustered wireless sensor networks,” in IET Signal Processing, vol. 6, no. 8, pp. 743- 750, October 2012, doi: 10.1049/iet-spr.2011.0341.
  25. Gautam and J. Pyun, “Distance aware intelligent clustering protocol for wireless sensor networks,” in Journal of Communications and Networks, vol. 12, no. 2, pp. 122-129, April 2010, doi: 10.1109/JCN.2010.6391368.
  26. Asaduzzaman and H. Y. Kong, “Energy efficient cooperative LEACH protocol for wireless sensor networks,” in Journal of Communications and Networks, vol. 12, no. 4, pp. 358-365, Aug. 2010, doi: 10.1109/JCN.2010.6388472.
  27. Wang, C. Wang and C. Liu, “Optimal Number of Clusters in Dense Wireless Sensor Networks: A Cross-Layer Approach,” in IEEE Transactions on Vehicular Technology, vol. 58, no. 2, pp. 966-976, Feb. 2009, doi: 10.1109/TVT.2008.928637.
  28. Quan, A. Subramanian and A. H. Sayed, “REACA: An Efficient Protocol Architecture for Large Scale Sensor Networks (Corrected)*,” in IEEE Transactions on Wireless Communications, vol. 6, no. 10, pp. 3846-3855, October 2007, doi: 10.1109/TWC.2007.0596402.
  29. Yu, K. K. Leung and A. Malvankar, “A dynamic clustering and energy efficient routing technique for sensor networks,” in IEEE Transactions on Wireless Communications, vol. 6, no. 8, pp. 3069-3079, August 2007, doi: 10.1109/TWC.2007.06003.
  30. M. F. AboElFotoh, S. S. Iyengar and K. Chakrabarty, “Computing reliability and message delay for Cooperative wireless distributed sensor networks subject to random failures,” in IEEE Transactions on Reliability, vol. 54, no. 1, pp. 145-155, March 2005, doi: 10.1109/TR.2004.842540.

 

Regular Issue Subscription Original Research
Volume 11
Issue 02
Received July 17, 2024
Accepted July 20, 2024
Published August 2, 2024
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