Leveraging AI, Mathematical optimization, fuzzy decision making, and software-defined networking in industrial internet of things (IIoT)

Submission Deadline: 01 April 2025 View: 179 Submit to Special Issue

Guest Editors

Dr. Jehad Ali

Email: jehadali@ajou.ac.kr

Affiliation: Department of AI Convergence Network, Ajou University, South Korea

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Research Interests: Software-Defined Networking, Extending it for 5G/6G issues, and improving QoS with SDN, Internet of Things, Wireless sensor networks, and applications of machine learning in Communication, Networking, and Healthcare.

Dr. Gaoyang Shan

Email: shanyang166@ajou.ac.kr

Affiliation: Department of Software and Computer Engineering, Ajou University, South Korea

Homepage: 

Research Interests: mobile wireless networks and Internet of Things

Dr. Sahib Khan

Email: sahib@uetmardan.edu.pk

Affiliation: Department of Telecommunication Engineering, University of Engineering and Technology Mardan, Pakistan 

Homepage:

Research Interests: Multimedia Forensics and Security, Image, Audio and Video Steganography, Watermarking

Summary

AI, mathematical optimization, fuzzy decision making, and software-defined networking (SDN) play crucial roles in enhancing the performance and efficiency of Industrial Internet of Things (IIoT) systems. Artificial Intelligence techniques, such as machine learning and deep learning, can enable IIoT systems to analyze and learn from vast amounts of data generated by industrial devices. By employing AI algorithms, IIoT can achieve predictive maintenance, anomaly detection, and optimized resource allocation. AI can also facilitate intelligent decision-making processes by uncovering patterns and correlations that humans might miss.

IIoT systems often involve complex resource allocation and scheduling challenges. Mathematical optimization techniques, such as linear programming, mixed-integer programming, and evolutionary algorithms, can optimize various aspects of IIoT operations. These techniques can optimize production planning, inventory management, energy consumption, and supply chain logistics. By formulating the problem mathematically and employing optimization algorithms, IIoT systems can minimize costs, maximize efficiency, and improve overall system performance.

Fuzzy logic-based decision-making models can handle uncertainty and imprecise information inherent in IIoT environments. Fuzzy decision-making techniques can consider multiple factors, each with varying degrees of importance, and make intelligent decisions based on fuzzy rules and linguistic variables. This approach allows IIoT systems to handle incomplete or uncertain data and adapt to changing conditions effectively. Fuzzy decision-making models can be particularly useful in scenarios where precise mathematical models are challenging to construct or when human expertise is valuable.

Software-Defined Networking (SDN) offers centralized control and programmability of network infrastructure in IIoT environments. By decoupling the control plane from the data plane, SDN allows dynamic reconfiguration of the network, efficient resource allocation, and intelligent traffic management. IIoT systems can leverage SDN to optimize network performance, ensure real-time data delivery, and enhance security. SDN enables seamless integration and management of heterogeneous IIoT devices, making it easier to scale and manage large-scale IIoT deployments.

In a nutshell, the combination of AI, mathematical optimization, fuzzy decision making, and SDN brings several benefits to IIoT. These technologies empower IIoT systems to make intelligent decisions, optimize resource allocation, handle uncertainty, and efficiently manage the underlying network infrastructure. By harnessing their capabilities, IIoT can achieve improved productivity, reduced costs, enhanced reliability, and better overall performance in industrial settings. This special issue invites potential papers related to but not limited to the following areas:

· SDN controller placement in the industrial internet of things (IIoTs)

· Securing the software defined IIoTs (SD-IIoT)

· Intrusion detection in SD-IIoT

· Fault resilience in SD-IIoT

· Route optimization in SD-IIoT

· Quality of service assurance in SD-IIoT

· DDoS attacks detection/prevention in SD-IIoT

· Intelligent Traffic engineering in SD-IIoT

· Network slicing in SD-IIoT

· Reliability assurance in SD-IIoT

· NFVs placement and deployment in SD-IIoT

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