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"Computational Intelligence Inspired Adaptive Opportunistic Clustering " by Premkumar Chithaluru, Fadi AL-Turjman et al.

The major issues and challenges of the Industrial Internet of Things (IIoT) include network resource management, self-organization; routing, mobility, scalability, security, and data aggregation. Resource management in IIoT is a challenging issue, starting from the deployment and design of sensor nodes, networking at cross-layer, networking software development, application types, environmental conditions, monitoring user decisions, querying process, etc. In this paper, computational intelligence (CI) and its computing, such as neural networks and fuzzy logic, are used to tackle the challenges of resource management in the IIoT. The incorporation of the neuro-fuzzy technique into the IIoT contributes to the self-managing intelligence systems’ self-organizing and self-sustaining capabilities, offering real-time computations and services in a pervasive networking environment. Most of the problems in IIoT are realtime based; they require fast computation, real-time optimal solutions, an ....

Industrial Internet , Clustering Algorithms , Computational Intelligence , Industrial Internet Of Things , Industrial Iot , Obile Node , Euro Fuzzy Technique , Eer To Peer Computing , Quality Of Service , Real Time Systems , Resource Management , Elf Managing , Self Organizing , Self Sustaining ,