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<p>Wireless Sensor Networks (WSNs), in most cases, are prone to congestion when subjected to high traffic, which results in the loss of packets, high delay, and heavy energy consumption. The current congestion control techniques have a hard time providing efficient routing, energy conservation, and data protection intermittently. To overcome these challenges, the paper suggests OptiConNet, a combined congestion control and energy-efficient WSNs framework. OptiConNet starts with grouping sensor nodes; cluster heads (CH) are chosen with Hive Path Optimizer (HPO), and various sink nodes are posted to distribute the data load and avoid bottlenecks. The compression and security of data packets are achieved with AES-aided Huffman Coding (AES-HuffShield) to decrease the load of transmission and energy consumption and ensure confidentiality. Firefly-Ant Colony Optimization (FACO) algorithm is a hybrid algorithm that selectively forwards data to sink nodes and is efficient in reducing congestion and network energy consumption. Additional security is also achieved through a lightweight authentication scheme, SVM-Guard, to ward off unauthorized access. Monitoring at the cluster level makes sure the congestion is controlled and that anomalies are detected. Simulation findings reveal that OptiConNet provides 20% more throughput, 18% less packet loss, and 15% less energy consumption than state-of-the-art models, which provide reliable and secure WSN communication.</p>

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Opticonnet: Enhancing Reliability and Energy Efficiency Through Congestion Control and Security in Wireless Sensor Networks

  • 期刊论文

  • 发表日期：

    2026年6月30日

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  • Srinivasan G.,
  • Seshadri Sekhar G.

摘要

Wireless Sensor Networks (WSNs), in most cases, are prone to congestion when subjected to high traffic, which results in the loss of packets, high delay, and heavy energy consumption. The current congestion control techniques have a hard time providing efficient routing, energy conservation, and data protection intermittently. To overcome these challenges, the paper suggests OptiConNet, a combined congestion control and energy-efficient WSNs framework. OptiConNet starts with grouping sensor nodes; cluster heads (CH) are chosen with Hive Path Optimizer (HPO), and various sink nodes are posted to distribute the data load and avoid bottlenecks. The compression and security of data packets are achieved with AES-aided Huffman Coding (AES-HuffShield) to decrease the load of transmission and energy consumption and ensure confidentiality. Firefly-Ant Colony Optimization (FACO) algorithm is a hybrid algorithm that selectively forwards data to sink nodes and is efficient in reducing congestion and network energy consumption. Additional security is also achieved through a lightweight authentication scheme, SVM-Guard, to ward off unauthorized access. Monitoring at the cluster level makes sure the congestion is controlled and that anomalies are detected. Simulation findings reveal that OptiConNet provides 20% more throughput, 18% less packet loss, and 15% less energy consumption than state-of-the-art models, which provide reliable and secure WSN communication.