Manuscript Topics

Internet of Things (IoT) has been one of the most important technologies that simplify new trends among smart devices and intelligent applications to enhance the quality of human life. IoT device needs to select only safe and secure IoT service providers before service selection and recommendation are performed in cloud-edge computing. Therefore, security, reliability and privacy issues are needed because not all smart devices will be secured and some IoT devices may behave maliciously to disrupt the cloud service (e.g., an adversary) or just for their gain to provide requested services based on Service Level Agreement (SLA). Also, as the IoT devices in human life capture and process sensitive personal information, the devices and their associated communications should be much reliable and secured to protect the user’s privacy. Du to heterogeneity and impotence of sensitive and critical information in IoT applications, collecting, processing and transmitting them are essential to the IoT environment from potential attacks with decreasing power generation and energy consumption. On the other hand, Artificial Intelligence (AI) is an emerging technology that has proven to have great potential to solve NP-hard problems in IoT ecosystems, cloud-edge computing, big data, and performance optimization. Also, AI-based performance evaluation techniques include data mining, machine learning, meta-heuristic algorithms, fuzzy logic, evolutionary methods, and many others. Due to the heterogeneity and variability of cloud-edge computing, it should be evaluated using AI-based modeling, simulation and testing methods to ensure their dependability, correctness and safety.

However, the evaluation of the functional and non-functional aspects of cloud-edge computing, using AI-based modeling, simulation and testing methods are challenging and many techniques have been investigated to improve the accuracy and correctness of optimal solutions. To this point, AI-based modeling and simulation of cloud-edge computing in IoT environments has emerging efforts and high potential to evaluate the critical points and safety conditions.

The goal of this special issue is to highlight the latest research focusing on AI-based modeling and simulation of cloud-edge computing to address the challenges and critical points produced by the IoT environments. This special issue invites researchers to publish selected original articles presenting intelligent trends to solve new challenges of new problems. We are also interested in review articles as the state-of-the-art of this topic, showing recent major advances and discoveries, significant gaps in the research and new future issues.

Topics:
• AI-based performance evaluation methods for security and privacy in IoT
• Meta-heuristic algorithms for evaluation energy consumption in IoT systems
• Fuzzy and optimization techniques fir medical and healthcare technologies in IoT
• AI-based techniques and fuzzy set methods for energy harvesting approaches on IoT smart grid
• Evolutionary methods and fuzzy logic for solving Could-edge resource management in IoT
• Machine learning for industrial equipment and smart manufacturing in IoT
• AI-based modeling reliability and availability issues for IoT ecosystems
• Deep learning for smart cities and home-care problems in IoT systems
• AI-based solutions for smart agriculture and farming in IoT environments
• AI-based performance evaluation methods for Robotics, bio-robotics, and control systems in IoT
• Evolutionary algorithms and fuzzy logic for Blockchain technology in IoT communications

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