DQN based Blockchain Data Storage in Resource-constrained IoT System

Abstract

Applying blockchain technology in the Internet of Things (IoT) systems to realize massive data storage is a promising technology, which can eliminate the dependence of IoT on central servers and protect data security effectively. However, in legacy IoT systems, it is hardly to store a complete blockchain at all nodes due to the limited storage space. In order to securely store massive data in the resource-constrained IoT systems, we design a blockchain-assisted distributed storage mechanism, by which multiple nodes collaboratively store a complete blockchain. Meanwhile, we design a deep reinforcement learning (DRL) based algorithm to obtain the optimal block allocation strategy for the collaborative storage. The optimal strategy can maximize the number of storage blocks so as to maximize the utilization of the limited storage space under the premise of meeting the requirements of user query delay and reliability. The simulation results show that compared with the random search algorithm and the policy gradients algorithm, the proposed Deep Q Network algorithm can achieve the maximum number of storage blocks in the same storage space, and the fastest storage speed.