چکیده

With the advancement of human society and information and communication technology the Internet of Things(IoT) has penetrated various aspects of people s daily lives and industries. Emerging blockchain technology has become a viable solution to IoT security due to its inherent characteristics such as distribution security immutability and traceability. However IoT and blockchain integration have challenges such as latency throughput device power limitation and scalability. Recent research has focused on the role of artificial intelligence methods in improving IoT performance in the blockchain. According to the studies there are few effects on improving IoT devices performance with limited power. In this study a conceptual model for improving blockchain throughput in IoT devices with limited power by deep reinforcement learning proposes. In this model to improve the throughput and select mining method by the miner a recommender agent based on deep reinforcement learning located in the mobile edge computing layer is used.

کليدواژه ها

IoT blockchain deep reinforcement learning

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, 1400 , Provision of a recommender model for blockchain-based Internet of Things with deep reinforcement learning approach , پنجمين دوره كنفرانس بین‌المللی اينترنت اشيا و كاربردها