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<p>Physical nodes and communication lines inside an Internet of Things (IoT) network are perpetually susceptible to a multitude of failure scenarios. These uncertainties may expose active Business Processes (BPs) to a greater risk of data loss. This paper addresses these challenges by proposing a hybrid framework that integrates energy-efficient algorithms with fault-resilient mechanisms. Additionally, this paper presents Well-Being Analysis (WBA), which integrates probabilistic and deterministic reliability evaluation techniques to instill fault resilience in every virtual service on the IoT network. The proposed model incorporates the risk of data loss into its objective function, along with the total energy consumption and average traffic latency. We utilize a probability tree to generate various scenarios of single contingency occurrences, integrating both probabilistic and deterministic reliability evaluations. Fault-resilient service embedding is a non-linear optimization problem that is addressed by implementing a Genetic Algorithm (GA) method. Numerical studies, focusing on smart buildings within university campuses featuring 24 bidirectional wireless communication links and 10 nodes, validate the model<i>’</i>s effectiveness. Simulation results indicate that the permissible probability of data losses is less than 0.0095. Comparative analysis with Full Redundancy Node Resilience (FRNR), and Splitting-based Traffic Resilience (STR) models demonstrates the proposed model is the most energy-efficient, effectively reducing power consumption while maintaining fault resilience, which is crucial for IoT networks, especially in power-constrained environments.</p>

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Improving the network efficiency of IoT using embedded fault-resilient services

  • 期刊论文

  • 发表日期：

    2025年11月11日

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  • Mohana Farzin,
  • Azadeh Alsadat Emrani Zarandi

摘要

Physical nodes and communication lines inside an Internet of Things (IoT) network are perpetually susceptible to a multitude of failure scenarios. These uncertainties may expose active Business Processes (BPs) to a greater risk of data loss. This paper addresses these challenges by proposing a hybrid framework that integrates energy-efficient algorithms with fault-resilient mechanisms. Additionally, this paper presents Well-Being Analysis (WBA), which integrates probabilistic and deterministic reliability evaluation techniques to instill fault resilience in every virtual service on the IoT network. The proposed model incorporates the risk of data loss into its objective function, along with the total energy consumption and average traffic latency. We utilize a probability tree to generate various scenarios of single contingency occurrences, integrating both probabilistic and deterministic reliability evaluations. Fault-resilient service embedding is a non-linear optimization problem that is addressed by implementing a Genetic Algorithm (GA) method. Numerical studies, focusing on smart buildings within university campuses featuring 24 bidirectional wireless communication links and 10 nodes, validate the model’s effectiveness. Simulation results indicate that the permissible probability of data losses is less than 0.0095. Comparative analysis with Full Redundancy Node Resilience (FRNR), and Splitting-based Traffic Resilience (STR) models demonstrates the proposed model is the most energy-efficient, effectively reducing power consumption while maintaining fault resilience, which is crucial for IoT networks, especially in power-constrained environments.