Efficient routing and lifetime extension in wireless sensor network performance Using Masnui honey bee colony algorithm and sleep and wake algorithm

Subject Areas : information technology

Seyadeh Mahsa Hosseini Kia ^{1 *} , Mohammad mehdi shirmohammadi ²

1 - Computer Department, Hamedan Branch, Islamic Azad University, Hamedan, Iran
2 - Computer Department, Hamedan Branch, Islamic Azad University, Hamedan, Iran

Received: 2025-01-21 Accepted : 2025-01-26 Published : 2025-03-04

Keywords: WSN, ABC, SWA, TEER, Clustering, Efficient Routing, Lifetime,

Abstract :

To increase the lifetime of wireless sensor networks (WSN), there is a need for efficient routing protocols to establish communication channels between source and destination. Because nodes are randomly scattered in relatively insecure environments, these routing protocols are vulnerable to various types of attacks.For wireless sensor networks, trust-based routing protocols have been designed that use trusted routes instead of the fastest route to avoid these attacks. To reduce the energy consumption of the nodes, the artificial bee colony-based clustering technique (ABC) that divides the energy consumption in the sensor network equally and the Sleep-Wake Algorithm (SWA) that only a part of the nodes Keeps active at any moment used.Based on the simulation analysis, the proposed ABC-SWA algorithm is compared with other protocols and shows that its performance is better in terms of reducing energy consumption, the number of active nodes, and network lifetime.

References:

[1] O. Kaiwartya, A. H. Abdullah, Y. Cao et al., “Virtualization in wireless sensor networks: fault tolerant embedding for Internet of things,” IEEE Internet of Things Journal, vol. 5, no. 2, pp. 571–580, 2018.
[2] P. K. Shukla et al., “Network Physical Address Based Encryption Technique Using Digital Logic”, International Journal of Scientific & Technology Research, Vol. 9, No. 4, 2020, Pp no.- 3119-3122.
[3] O. Kaiwartya, A. H. Abdullah, Y. Cao, et al., “Internet of vehicles: motivation, layered architecture, network model, challenges, and future aspects,” IEEE Access, vol. 4, pp. 5356–5373, 2016.
[4] V. Roy. "An Improved Image Encryption Consuming Fusion Transmutation and Edge Operator." Journal of Cybersecurity and Information Management, Vol. 8, No. 1, 2021, PP. 42-52.
[5] L. Farhan, R. Kharel, O. Kaiwartya, M. Hammoudeh, and B. Adebisi, “Towards green computing for Internet of things: energy-oriented path and message scheduling approach,” Sustainable Cities and Society, vol. 38, pp. 195–204, 2018.
[6] V. Roy. " Breast cancer Classification with Multi-Fusion Technique and Correlation Analysis" Fusion: Practice & Applications, Vol. 9, No. 2, 2023, PP. 48-61.
[7] Roy, V., Shukla, P. K., Gupta, A. K., Goel, V., Shukla, P. K., & Shukla, S. (2021). Taxonomy on EEG Artifacts Removal Methods, Issues, and Healthcare Applications. Journal of Organizational and End User Computing (JOEUC), 33(1), 19-46. http://doi.org/10.4018/JOEUC.2021010102.
[8] O. Kaiwartya, A. H. Abdullah, Y. Cao et al., “Internet of vehicles: motivation, layered architecture, network model, challenges, and future aspects,” IEEE Access, vol. 4, pp. 5356–5373, 2016.
[9] A. Khatri, S. Kumar, O. Kaiwartya, and A. H. Abdullah, “Green computing for wireless sensor networks: optimization and Huffman coding approach,” Peer-to-Peer Networking and Applications, vol. 10, no. 3, pp. 592–609, 2017.
[10] P. Kumar, A. Baliyan, K. R. Prasad, N. Sreekanth, P. Jawarkar, V. Roy, E. T. Amoatey, "Machine Learning Enabled Techniques for Protecting Wireless Sensor Networks by Estimating Attack Prevalence and Device Deployment Strategy for 5G Networks", Wireless Communications and Mobile Computing, vol. 2022, Article ID 5713092, 15 pages, 2022. https://doi.org/10.1155/2022/5713092
[11] Saranya, V., Shankar, S., & Kanagachidambaresan, G. R. (2018). Energy efficient clustering scheme (EECS) for wireless sensor network with mobile sink. Wireless Personal Communications, 100(4), 1553–1567. https://doi.org/10.1007/s11277-018-5653-1
[12] Roy, S., Mazumdar, N., & Pamula, R. (2021). An energy and coverage sensitive approach to hierarchical data collection for mobile sink-based wireless sensor networks. Journal of Ambient Intelligence and Humanized Computing, 12(1), 1267–1291.
[13] Nabil M. AbdelAziz,Hassan H. Mohammed,Khalid A. Eldrandaly, An effective Decision making model through Fusion Optimization and risk associated with flash flood hazards: A case study Asyut, Egypt, Journal of Fusion: Practice and Applications, Vol. 12 , No. 1 , (2023) : 64-94 (Doi : https://doi.org/10.54216/FPA.120105)
[14] Yalcin, S., & Erdem, E. (2019). Bacteria interactive cost and balanced-compromised approach to clustering and transmission boundary-range cognitive routing in mobile heterogeneous wireless sensor networks. Sensors. https://doi.org/10.3390/s19040867
[15] Fotohi, R., & Bari, S. F. (2020). A novel countermeasure technique to protect WSN against denial-ofsleep attacks using Firefly and Hopfield neural network (HNN) algorithms. Journal of Supercomputing, 76(6), 6860–6886. https://doi.org/10.1007/s11227-019-03131-x
[16] Sharmin, N., Karmaker, A., Lambert, W. L., Alam, M. S., & Shawkat, M. S. T. S. A. (2020). Minimizing the energy hole problem in wireless sensor networks: A Wedge Merging Approach. Sensors.
[17] Zahra, M., Wang, Y., & Ding, W. J. (2019). Cross-layer routing for a mobility support protocol based on handover mechanism in cluster-based wireless sensor networks with mobile sink. Sensors.
[18] Basumatary, H., Debnath, A., Barma, M. K. D., & Bhattacharyya, B. K. (2020). Centroid-based routing protocol with moving sink node for uniform and non-uniform distribution of wireless sensor nodes. Journal of Supercomputing, 77(4), 3727–3751.
[19] Zhang, J., Tang, J., Wang, Z. H., Wang, F., & Yu, G. (2020). Load-balancing rendezvous approach for mobility-enabled adaptive energy-efficient data collection in WSNs. KSII Transactions on Internet and Information Systems, 14(3), 1204–1227.
[20] Theodorou, T., & Mamatas, L. (2021). SD-MIoT: A software-defined networking solution for mobile internet of things. IEEE Internet Things, 8(6), 4604–4617.
[21] Maruthupandi, J., Prasanna, S., Jayalakshmi, P., Mareeswari, V., Kumar, B. S., & Sanjeevi, P. (2021). Route manipulation aware software-defined networks for effective routing in SDN controlled MANET by Disney routing protocol. Microprocessors and Microsystems.
[22] Guo, W. J., Yan, C. R., & Lu, T. (2019). Optimizing the lifetime of wireless sensor networks via reinforcement-learning-based routing. International Journal of Distributed Sensor Networks.
[23] Alghamdi, T. A. (2020). Energy efficient protocol in wireless sensor network: Optimized cluster head selection model. Telecommunication Systems, 74(3), 331–345. https://doi.org/10.1007/s11235-020- 00659-9
[24] Balamurugan, A., Priya, M. D., Janakiraman, S., & Malar, A. C. J. (2021). Hybrid stochastic ranking and opposite differential evolution-based enhanced Firefly Optimization Algorithm for extending network lifetime through efficient clustering in WSNs. Journal of Network and Systems Management, 29(3), 1–31.
[25] Baradaran, A. A., & Navi, K. (2020). HQCA-WSN: High-quality clustering algorithm and optimal cluster head selection using fuzzy logic in wireless sensor networks. Fuzzy Sets and Systems, 389(1), 114–144.
[26] Mohd Zainal Abidin Ab Kadir , Mhmed Algrnaodi , Ahmed N. Al-Masri, Optimal Algorithm for Shared Network Communication Bandwidth in IoT Applications, International Journal of Wireless and Ad Hoc Communication, Vol. 2 , No. 1 , (2021) : 33-48 (Doi : https://doi.org/10.54216/IJWAC.020103)
[27] Muhammad Edmerdash, Waleed khedr, Ehab Rushdy, An Overview of Cloud-Based Secure Services for Enterprise Drug–Drug Interaction Systems, International Journal of Wireless and Ad Hoc Communication, Vol. 2 , No. 2 , (2021) : 49-58 (Doi : https://doi.org/10.54216/IJWAC.020201)
[28] Andino Maseleno, Design of Optimal Machine Learning based Cybersecurity Intrusion Detection Systems, Journal of Cybersecurity and Information Management, Vol. 0 , No. 1 , (2019) : 32-43 (Doi : https://doi.org/10.54216/JCIM.000103).
[29] Ahmed Abdelhafeez, Hoda K. Mohamed, Skin Cancer Detection using Neutrosophic c-means and Fuzzy c-means Clustering Algorithms, Journal of Intelligent Systems and Internet of Things, Vol. 8 , No. 1 , (2023) : 33-42 (Doi : https://doi.org/10.54216/JISIoT.080103)
[30] Lobna Osman, Olutosin Taiwo, Ahmed Elashry, Absalom E. Ezugwu, Intelligent Edge Computing for IoT: Enhancing Security and Privacy, Journal of Intelligent Systems and Internet of Things, Vol. 8, No. 1, (2023): 55-65 (Doi : https://doi.org/10.54216/JISIoT.080105