International Journal of Computer Networks and Applications

Open Access Open Access  Restricted Access Subscription Access

Secure Power Aware Hybrid Routing Strategy for Large-Scale Wireless Sensor Networks


Affiliations
1 Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Hyderabad, Telangana, India
2 Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Hyderabad, University College of Engineering, Jagitial, Telangana, India
 

Wireless Sensor Networks (WSNs) in critical applications demand safe routing methods to increase network life and protect data flow. This study proposes a "Secure Power Aware Hybrid Routing Strategy for Wireless Sensor Networks (WSN) utilizing randomized cluster head selection" to address these challenges. Traditional routing systems typically face energy depletion because of uneven node energy usage and attacks. The recommended strategy uses clustering and randomization to overcome these concerns. The network is divided into clusters with dynamically designated cluster heads. Randomly selecting cluster heads (CHs) in a network strengthens it against attacks targeting fixed CHs. Thus, this randomization method enhances network security. Energy efficiency is critical in Wireless Sensor Networks. This method solves the problem by considering power while choosing cluster heads. Assigning greater probability to nodes with more residual energy for cluster head (CH) selection encourages fairer energy utilization throughout the network, extending its operational lifetime. The research also evaluates the technique's energy usage, network longevity, and security robustness. The approach is tested against conventional routing techniques in simulated tests. The research found that the proposed technique outperforms existing methods in energy efficiency, network lifetime, and security. The hybrid technique combines clustering with randomization to provide a more adaptable and safe network architecture. Finally, the proposed technology may improve Wireless Sensor Network energy efficiency and security. The hybrid strategy balances energy savings and network protection. This makes it excellent for a broad variety of critical sector applications that prioritize reliability, longevity, and data integrity.

Keywords

Secure, Power Aware, Hybrid Routing, Selective Routing, WSN, Randomized Cluster Head Selection.
User
Notifications
Font Size

  • M. E. Al-Sadoon, A. Jedidi and H. Al-Raweshidy, "Dual-Tier Cluster-Based Routing in Mobile Wireless Sensor Network for IoT Application," in IEEE Access, vol. 11, pp. 4079-4094, 2023, doi: 10.1109/ACCESS.2023.3235200.

  • Chowdhuri, R., Barma, M.K.D. Node position estimation based on optimal clustering and detection of coverage hole in wireless sensor networks using hybrid deep reinforcement learning. J Supercomput 79, 20845–20877 (2023). https://doi.org/10.1007/s11227-023-05494-8.

  • Han D, Du X, Wang L, Liu X, Tian X. Trust-Aware and Fuzzy Logic-Based Reliable Layering Routing Protocol for Underwater Acoustic Networks. Sensors. 2023; 23(23):9323. https://doi.org/10.3390/s23239323.

  • Sirajuddin, M. ., & Kumar, B. S. . (2023). Intelligent Secure and Malicious-Free Route Management Strategy for IoT-based Wireless Sensor Networks. International Journal of Intelligent Systems and Applications in Engineering, 11(7s), 369–380. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2962

  • Ahutu, O. R., & El-Ocla, H. (2020). Centralized Routing Protocol for Detecting Wormhole Attacks in Wireless Sensor Networks. IEEE Access, 8, 63270–63282. https://doi.org/10.1109/ACCESS.2020.2983438

  • Alghamdi, T. A. (2018). Secure and Energy Efficient Path Optimization Technique in Wireless Sensor Networks Using DH Method. IEEE Access, 6, 53576–53582. https://doi.org/10.1109/ACCESS.2018.2865909

  • Alotaibi, M. (2021). Improved Blowfish Algorithm-Based Secure Routing Technique in IoT-Based WSN. IEEE Access, 9, 159187–159197. https://doi.org/10.1109/ACCESS.2021.3130005

  • Bin-Yahya, M., Alhussein, O., & Shen, X. (2022). Securing Software-Defined WSNs Communication via Trust Management. IEEE Internet of Things Journal, 9(22), 22230–22245. https://doi.org/10.1109/JIOT.2021.3102578

  • Bin-Yahya, M., & Shen, X. (2023). Secure and Energy-Efficient Network Topology Obfuscation for Software-Defined WSNs. IEEE Internet of Things Journal, 10(3), 2031–2045. https://doi.org/10.1109/JIOT.2022.3144873

  • Chatterjee, T., Karmakar, S., & Das Bit, S. (2021). IPLQueeN: Integrity Preserving Low-Overhead Query Handling Over NDN-Based WSN. IEEE Access, 9, 82786–82811. https://doi.org/10.1109/ACCESS.2021.3086460

  • Feng, W., Wang, F., Xu, D., Yao, Y., Xu, X., Jiang, X., & Zhao, M. (2020). Joint Energy-Saving Scheduling and Secure Routing for Critical Event Reporting in Wireless Sensor Networks. IEEE Access, 8, 53281–53292. https://doi.org/10.1109/ACCESS.2020.2981115

  • Fu, X., Yang, Y., & Postolache, O. (2021). Sustainable Multipath Routing Protocol for Multi-Sink Wireless Sensor Networks in Harsh Environments. IEEE Transactions on Sustainable Computing, 6(1), 168–181. https://doi.org/10.1109/TSUSC.2020.2976096

  • Ganesh, S., & Amutha, R. (2013). Efficient and secure routing protocol for wireless sensor networks through SNR based dynamic clustering mechanisms. Journal of Communications and Networks, 15(4), 422–429. https://doi.org/10.1109/JCN.2013.000073

  • Gope, P., Lee, J., & Quek, T. Q. S. (2017). Resilience of DoS Attacks in Designing Anonymous User Authentication Protocol for Wireless Sensor Networks. IEEE Sensors Journal, 17(2), 498–503. https://doi.org/10.1109/JSEN.2016.2628413

  • Haseeb, K., Almustafa, K. M., Jan, Z., Saba, T., & Tariq, U. (2020). Secure and Energy-Aware Heuristic Routing Protocol for Wireless Sensor Network. IEEE Access, 8, 163962–163974. https://doi.org/10.1109/ACCESS.2020.3022285

  • Haseeb, K., Islam, N., Almogren, A., & Ud Din, I. (2019). Intrusion Prevention Framework for Secure Routing in WSN-Based Mobile Internet of Things. IEEE Access, 7, 185496–185505. https://doi.org/10.1109/ACCESS.2019.2960633

  • Haseeb, K., Islam, N., Almogren, A., Ud Din, I., Almajed, H. N., & Guizani, N. (2019). Secret Sharing-Based Energy-Aware and Multi-Hop Routing Protocol for IoT Based WSNs. IEEE Access, 7, 79980–79988. https://doi.org/10.1109/ACCESS.2019.2922971

  • Hatzivasilis, G., Papaefstathiou, I., & Manifavas, C. (2017). SCOTRES: Secure Routing for IoT and CPS. IEEE Internet of Things Journal, 4(6), 2129–2141. https://doi.org/10.1109/JIOT.2017.2752801

  • Li, S., Zhao, S., Wang, X., Zhang, K., & Li, L. (2014). Adaptive and Secure Load-Balancing Routing Protocol for Service-Oriented Wireless Sensor Networks. IEEE Systems Journal, 8(3), 858–867. https://doi.org/10.1109/JSYST.2013.2260626

  • Liu, Y., Dong, M., Ota, K., & Liu, A. (2016). ActiveTrust: Secure and Trustable Routing in Wireless Sensor Networks. IEEE Transactions on Information Forensics and Security, 11(9), 2013–2027. https://doi.org/10.1109/TIFS.2016.2570740

  • Mutalemwa, L. C., & Shin, S. (2021). Novel Approaches to Realize the Reliability of Location Privacy Protocols in Monitoring Wireless Networks. IEEE Access, 9, 104820–104836. https://doi.org/10.1109/ACCESS.2021.3099499

  • Pathak, A., Al-Anbagi, I., & Hamilton, H. J. (2022). An Adaptive QoS and Trust-Based Lightweight Secure Routing Algorithm for WSNs. IEEE Internet of Things Journal, 9(23), 23826–23840. https://doi.org/10.1109/JIOT.2022.3189832

  • Qin, D., Yang, S., Jia, S., Zhang, Y., Ma, J., & Ding, Q. (2017). Research on Trust Sensing Based Secure Routing Mechanism for Wireless Sensor Network. IEEE Access, 5, 9599–9609. https://doi.org/10.1109/ACCESS.2017.2706973

  • Rathee, M., Kumar, S., Gandomi, A. H., Dilip, K., Balusamy, B., & Patan, R. (2021). Ant Colony Optimization Based Quality of Service Aware Energy Balancing Secure Routing Algorithm for Wireless Sensor Networks. IEEE Transactions on Engineering Management, 68(1), 170–182. https://doi.org/10.1109/TEM.2019.2953889

  • Roy, S., Conti, M., Setia, S., & Jajodia, S. (2014). Secure Data Aggregation in Wireless Sensor Networks: Filtering out the Attacker’s Impact. IEEE Transactions on Information Forensics and Security, 9(4), 681–694. https://doi.org/10.1109/TIFS.2014.2307197

  • Saleem, K., Fisal, N., & Al-Muhtadi, J. (2014). Empirical Studies of Bio-Inspired Self-Organized Secure Autonomous Routing Protocol. IEEE Sensors Journal, 14(7), 2232–2239. https://doi.org/10.1109/JSEN.2014.2308725

  • Salim, A., Osamy, W., Khedr, A. M., Aziz, A., & Abdel-Mageed, M. (2021). A Secure Data Gathering Scheme Based on Properties of Primes and Compressive Sensing for IoT-Based WSNs. IEEE Sensors Journal, 21(4), 5553–5571. https://doi.org/10.1109/JSEN.2020.3032585

  • Selcuk Uluagac, A., Beyah, R. A., & Copeland, J. A. (2013). Secure SOurce-BAsed Loose Synchronization (SOBAS) for Wireless Sensor Networks. IEEE Transactions on Parallel and Distributed Systems, 24(4), 803–813. https://doi.org/10.1109/TPDS.2012.170

  • Verma, S., Zeadally, S., Kaur, S., & Sharma, A. K. (2022). Intelligent and Secure Clustering in Wireless Sensor Network (WSN)-Based Intelligent Transportation Systems. IEEE Transactions on Intelligent Transportation Systems, 23(8), 13473–13481. https://doi.org/10.1109/TITS.2021.3124730

  • R. Alkanhel, K. Chinnthambi, C. Thilagavathi, An energy-efficient multi-swarm optimization in wireless sensor networks, Intelligent Automation & soft computing IASC 36 (2) (2023), https://doi.org/10.32604/iasc.2023.033430.

  • D. S. Misbha, ‘‘Lightweight key distribution for secured and energy efficient communication in wireless sensor network: An optimization assisted model,’’ High-Confidence Comput., vol. 3, no. 2, Jun. 2023, Art. no. 100126, doi: 10.1016/j.hcc.2023.100126.


Abstract Views: 149

PDF Views: 1




  • Secure Power Aware Hybrid Routing Strategy for Large-Scale Wireless Sensor Networks

Abstract Views: 149  |  PDF Views: 1

Authors

Mohammad Sirajuddin
Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Hyderabad, Telangana, India
B. Sateesh Kumar
Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Hyderabad, University College of Engineering, Jagitial, Telangana, India

Abstract


Wireless Sensor Networks (WSNs) in critical applications demand safe routing methods to increase network life and protect data flow. This study proposes a "Secure Power Aware Hybrid Routing Strategy for Wireless Sensor Networks (WSN) utilizing randomized cluster head selection" to address these challenges. Traditional routing systems typically face energy depletion because of uneven node energy usage and attacks. The recommended strategy uses clustering and randomization to overcome these concerns. The network is divided into clusters with dynamically designated cluster heads. Randomly selecting cluster heads (CHs) in a network strengthens it against attacks targeting fixed CHs. Thus, this randomization method enhances network security. Energy efficiency is critical in Wireless Sensor Networks. This method solves the problem by considering power while choosing cluster heads. Assigning greater probability to nodes with more residual energy for cluster head (CH) selection encourages fairer energy utilization throughout the network, extending its operational lifetime. The research also evaluates the technique's energy usage, network longevity, and security robustness. The approach is tested against conventional routing techniques in simulated tests. The research found that the proposed technique outperforms existing methods in energy efficiency, network lifetime, and security. The hybrid technique combines clustering with randomization to provide a more adaptable and safe network architecture. Finally, the proposed technology may improve Wireless Sensor Network energy efficiency and security. The hybrid strategy balances energy savings and network protection. This makes it excellent for a broad variety of critical sector applications that prioritize reliability, longevity, and data integrity.

Keywords


Secure, Power Aware, Hybrid Routing, Selective Routing, WSN, Randomized Cluster Head Selection.

References





DOI: https://doi.org/10.22247/ijcna%2F2023%2F223695