<p>In a wireless sensor network (WSN), each node comprises multiple sensors that collect environmental data. Given the limited energy resources of these nodes, it is crucial to optimize routing protocols to minimize energy consumption. High energy usage by sensor nodes can lead to decreased network efficiency and shortened lifespan. Consequently, identifying routes that require minimal energy for packet transmission is essential. Large-scale WSN demands effective energy management and robust Quality of Service (QoS) security. This paper introduces an <b>Energy-Efficient Optimization and Trust-Based Secure Routing (EEOTSR)</b> protocol. EEOTSR integrates energy-efficient routing with trust-based security mechanisms using Ant Colony Optimization (ACO). This bio-inspired algorithm mimics the pheromone trails laid by ants to select optimal routing paths dynamically. The protocol enhances network security by establishing secure transmission routes and improving energy efficiency. It employs a distributed trust model to detect and isolate malfunctioning or malicious nodes. The simulations show that EEOTSR increases network lifetime by 23%, improves the packet delivery ratio by 17%, and reduces average latency by 14% compared to existing protocols. Additionally, EEOTSR demonstrates strong resilience against blackhole attacks, maintaining a packet delivery ratio above 90%, even with 30% of nodes compromised. This unique combination of features sets EEOTSR apart as a robust solution for enhancing the performance and reliability of WSN in industrial contexts.</p>

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Resilient wireless sensor networks in industrial contexts via energy-efficient optimization and trust-based secure routing

  • Avaneesh Singh,
  • Atul Raj,
  • Preeti Rani,
  • Ali Khatibi,
  • Horiya Aldeeb,
  • Piyush Kumar Shukla,
  • Ayman Sabry,
  • Mohamed M. Hassan

摘要

In a wireless sensor network (WSN), each node comprises multiple sensors that collect environmental data. Given the limited energy resources of these nodes, it is crucial to optimize routing protocols to minimize energy consumption. High energy usage by sensor nodes can lead to decreased network efficiency and shortened lifespan. Consequently, identifying routes that require minimal energy for packet transmission is essential. Large-scale WSN demands effective energy management and robust Quality of Service (QoS) security. This paper introduces an Energy-Efficient Optimization and Trust-Based Secure Routing (EEOTSR) protocol. EEOTSR integrates energy-efficient routing with trust-based security mechanisms using Ant Colony Optimization (ACO). This bio-inspired algorithm mimics the pheromone trails laid by ants to select optimal routing paths dynamically. The protocol enhances network security by establishing secure transmission routes and improving energy efficiency. It employs a distributed trust model to detect and isolate malfunctioning or malicious nodes. The simulations show that EEOTSR increases network lifetime by 23%, improves the packet delivery ratio by 17%, and reduces average latency by 14% compared to existing protocols. Additionally, EEOTSR demonstrates strong resilience against blackhole attacks, maintaining a packet delivery ratio above 90%, even with 30% of nodes compromised. This unique combination of features sets EEOTSR apart as a robust solution for enhancing the performance and reliability of WSN in industrial contexts.