Improved Secure Distributed Routing Using Extended DART with Fault Avoidance and Queue-Based Load Balancing Protocol for WSN

International Journal of Electronics and Communication Engineering

© 2024 by SSRG - IJECE Journal

Volume 11 Issue 8

Year of Publication : 2024

Authors : B.R. Sathishkumar, B. Subbarayudu, P.M. Benson Mansingh, A. Senthilkumar

10.14445/23488549/IJECE-V11I8P104

How to Cite?

B.R. Sathishkumar, B. Subbarayudu, P.M. Benson Mansingh, A. Senthilkumar, "Improved Secure Distributed Routing Using Extended DART with Fault Avoidance and Queue-Based Load Balancing Protocol for WSN," SSRG International Journal of Electronics and Communication Engineering, vol. 11,  no. 8, pp. 31-41, 2024. Crossref, https://doi.org/10.14445/23488549/IJECE-V11I8P104

Abstract:

Wireless Sensor Networks (WSNs), especially deployed wearing urbanized uses as automobile traffic surveillance, are the primary supply of serious details and create an enormous volume of information. Multipath routing kindness dependable details shipping and delivery within the situation of vulnerable information. Nevertheless, the drawback is the fact that lots of routes may boost the variety of command packets. This paper presents an advanced approach to secure distributed routing in WSNs, integrating Extended DART Fault Avoidance and Queue-based Load Balancing (DFAQLB). The proposed system aims to enhance the reliability and efficiency of routing mechanisms in challenging environments characterized by node failures and network congestion. The Extended DFAQLB offers robust fault tolerance capabilities by dynamically adjusting routing paths to circumvent faulty nodes and ensure reliable data delivery. Concurrently, the DFAQLB protocol optimizes network performance by distributing the traffic load across sensor nodes based on real-time queue monitoring and balancing strategies. Through extensive simulations and analysis, our results demonstrate significant improvements in network reliability, fault tolerance, and load distribution efficiency compared to traditional routing protocols. The proposed framework for enhancing the resilience and performance of WSNs deployed in mission-critical applications requires secure and efficient data transmission.

Keywords:

Secure distributed routing, Wireless sensor network, Extended DART, Fault avoidance queue-based load balancing, Fault tolerance, Network reliability, Load distribution, Data transmission, Resilience.

References:

[1] Abdelkader Benelhouri, Hafida Idrissi-Saba, and Jilali Antari, “An Evolutionary Routing Protocol for Load Balancing and QoS Enhancement in IoT-Enabled Heterogeneous WSNs,” Simulation Modelling Practice and Theory, vol. 124, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[2] M. Revanesh, John M. Acken, and V. Sridhar, “DAG Block: Trust Aware Load Balanced Routing and Lightweight Authentication Encryption in WSN,” Future Generation Computer Systems, vol. 140, pp. 402-421, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Nagesh Mallaiah Vaggu, and Ravi Sankar Barpanda, “DBlock-RLB: An Energy Efficient Framework for Intelligent Routing and Trading based Load Balancing in SDWSN Environment,” Ad Hoc Networks, vol. 159, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[4] GSR Yogaraja, MN. Thippeswamy, and K. Venkatesh, “A Literature Study and Performance Gaps on Centralized Server-Based Load Balancing and Routing Strategies Under Cloud-IoT-WSN,” Australian Journal of Electrical and Electronics Engineering, vol. 21, no. 2, pp. 138-160, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Majid Altuwairiqi, “An Optimized Multi-Hop Routing Protocol for Wireless Sensor Network Using Improved Honey Badger Optimization Algorithm for Efficient and Secure QoS,” Computer Communications, vol. 214, pp. 244-259, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Najib Ahmed Mohammed, and Mohamed Othman, “A Load-Balanced Algorithm for Internet Gateway Placement in Backbone Wireless Mesh Networks,” Future Generation Computer Systems, vol. 150, pp. 144-159, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[7] G. Ramani, and K. Amarendra, “An Optimized Energy Management and Load Balancing System Based on Cluster Head Selection for Vehicular Network Communication,” Multimedia Tools and Applications, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Huilong Jiang, “Exploration of Load Balancing Data Aggregation Algorithm in Wireless Sensor Network Based on Big Data Artificial Intelligence,” Internet Technology Letters, vol. 7, no. 2, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[9] S. Vishwas and K. Hareesh, “An Energy Efficient Cloud-Based Routing Protocol for Wireless Sensor Network (WSN) for Improving Throughput and Packet Delivery Ratio,” International Journal of Intelligent Systems and Applications in Engineering, vol. 12, no. 13s, pp. 697-710, 2024.
[Google Scholar] [Publisher Link]
[10] K. Dinesh, and SVN. Santhosh Kumar, “GWO-SMSLO: Grey Wolf Optimization-Based Clustering with Secured Modified Sea Lion Optimization Routing Algorithm in Wireless Sensor Networks,” Peer-to-Peer Networking and Applications, vol. 17, pp. 585-611, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Neha Ahlawat, and Jasvinder Kaur, “A Mobility-Based Approach to Strengthen the Network Lifetime of Wireless Sensor Networks in 3D Region,” International Journal of Sensors Wireless Communications and Control, vol. 14, no. 1, pp. 36-44, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Mohammad Sirajuddin, and B. Sateesh Kumar, “Secure Power Aware Hybrid Routing Strategy for Large-Scale Wireless Sensor Networks,” International Journal of Computer Networks and Applications, vol. 10, no. 6, pp. 1015-1029, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Harshvardhan Singh Chauhan et al., Named Data Networking: Content Based Routing-Architecture Challenges and Applications Emerging Technologies and the Application of WSN and IoT: Smart Surveillance, Public Security, and Safety Challenges, 1st ed., CRC Press, pp. 43-64, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Jayantkumar A Rathod, and Manjunath Kotari, “TriChain: Kangaroo-Based Intrusion Detection for Secure Multipath Route Discovery and Route Maintenance in MANET Using Advanced Routing Protocol,” International Journal of Computer Networks and Applications, vol. 11, no. 1, pp. 61-81, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Vishal Sharma, Rohit Beniwal, and Vinod Kumar, “Multi-Level Trust-Based Secure and Optimal IoT-WSN Routing for Environmental Monitoring Applications,” The Journal of Supercomputing, vol. 80, pp. 11338-11381, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Liyazhou Hu et al., “Security Enhancement for Deep Reinforcement Learning-based Strategy in Energy-Efficient Wireless Sensor Networks,” Sensors, vol. 24, no. 6, pp. 1-14, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[17] B.S. Venkatesh Prasad, and H.R. Roopashree, “Energy-Aware and Secure Routing for Hierarchical Cluster Through Trust Evaluation,” Measurement: Sensors, vol. 33, pp. 1-8, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Anurag Shukla et al., “SEE2PK: Secure and Energy Efficient Protocol Based on Pairwise Key for Hierarchical Wireless Sensor Network,” Peer-to-Peer Networking and Applications, vol. 17, pp. 701-721, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Shuaijie Li et al., “Analyzing the Robustness of LEO Satellite Networks Based on Two Different Attacks and Load Distribution Methods,” Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 34, no. 3, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Walid Osamy et al., “SEACDSC: Secure and Energy-Aware Clustering Based on Discrete Sand Cat Swarm Optimization for IoT-Enabled WSN Applications,” Wireless Networks, vol. 30, pp. 2781-2800, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[21] S. Suresh Babu, and N. Geethanjali, “Lifetime Improvement of Wireless Sensor Networks by Employing Trust Index Optimized Cluster Head Routing (TIOCHR),” Measurement: Sensors, vol. 32, 2024.
[[CrossRef] [Google Scholar] [Publisher Link]
[22] Shiv Dutta Mishra, and Dipti Verma, “Energy-Efficient and Reliable Clustering with Optimized Scheduling and Routing for Wireless Sensor Networks,” Multimedia Tools and Applications, vol. 83, pp. 68107–68133, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Hongzhang Han, Jun Tang, and Zhengjun Jing, “Wireless Sensor Network Routing Optimization Based on Improved Ant Colony Algorithm in the Internet of Things,” Heliyon, vol. 10, no. 1, pp. 1-16, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Osama A. Khashan et al., “Innovative Energy-Efficient Proxy Re-Encryption for Secure Data Exchange in Wireless Sensor Networks,” IEEE Access, vol.12, pp. 23290-23304, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[25] Songhao Jia et al., “Research on WSN Intelligent Routing Algorithm Based on Bayesian Learning and Particle Swarm Optimization,” Recent Advances in Electrical & Electronic Engineering, vol. 17, no. 3, pp. 304-315, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[26] Yogesh Patidar, Manish Jain, and Ajay Kumar Vyas, Routing in Wireless Sensor Networks and Internet of Things: Systematic Analysis and Discussion, AIoT and Smart Sensing Technologies for Smart Devices, Engineering Science Reference, pp. 181-196, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[27] M. Karthikeyan, D. Manimegalai, and Karthikeyan RajaGopal, “Firefly Algorithm-Based WSN-IoT Security Enhancement with Machine Learning for Intrusion Detection,” Scientific Reports, vol. 14, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[28] R. K. Krishna et al., “Hybrid Energy Balancer for Clustering and Routing Techniques to Enhance the Lifetime and Energy-Efficiency of Wireless Sensor Networks,” Journal of Autonomous Intelligence, vol. 7, no. 2, pp. 1-10, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[29] Tariq Mahmood et al., “Energy-Optimized Data Fusion Approach for Scalable Wireless Sensor Network Using Deep Learning-Based Scheme,” Journal of Network and Computer Applications, vol. 224, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[30] Amar Deep Gupta, and Ranjeet Kumar Rout, “SMEOR: Sink Mobility‐Based Energy‐Optimized Routing in Energy Harvesting‐Enabled Wireless Sensor Network,” International Journal of Communication Systems, vol. 37, no. 4, 2023.
[CrossRef] [Google Scholar] [Publisher Link]