Neuro-Evolutionary Framework for Task Offloading in Blockchain-Edge Computing Systems: Integrating Neural Networks and Evolutionary Algorithms

One approach to addressing the security and scalability concerns in IoT and IIoT is the combination of blockchain technology with edge computing. This framework aims to enhance the task offloading process by merging Neural Networks and Evolutionary Algorithms. It looks to refine decisionmaking processes of the task offloading and optimizes resource usage with such clever frameworks. Most importantly, it aims at security and scalability in the blockchain-edge systems applied to the IoT/IIoT applications. This framework uses Neural Networks to predict the tasks and Evolutionary Algorithms to improve optimization methods. The purpose is to improve computational efficiency and reduce latency in blockchain-edge computing configurations. The proposed strategy outperforms any extant solutions by making them even more accurate while employing percentage assets much better, reducing the task offloading time intervals, and thus keeping it secure and scalable in dynamic IoT/IIoT. The neuro-evolutionary framework is an effective strategy to boost task offloading performance in blockchain-edge computing, strengthening functionality, security, and scalability in IoT/IIoT applications. It displays potential for additional scrutinization.