Research Article
Energy-Aware Blockchain Resource Allocation Algorithm with Deep Reinforcement Learning for Trusted Authentication
@INPROCEEDINGS{10.1007/978-3-030-73562-3_8, author={Lifang Gao and Xiaotao Zhang and Tingfeng Liu and Huifeng Yang and Boxian Liao and Jing Guo}, title={Energy-Aware Blockchain Resource Allocation Algorithm with Deep Reinforcement Learning for Trusted Authentication}, proceedings={Smart Grid and Innovative Frontiers in Telecommunications. 5th EAI International Conference, SmartGIFT 2020, Chicago, USA, December 12, 2020, Proceedings}, proceedings_a={SMARTGIFT}, year={2021}, month={7}, keywords={Internet of things Edge-terminal collaborative Trusted authentication Task offloading}, doi={10.1007/978-3-030-73562-3_8} }- Lifang Gao
Xiaotao Zhang
Tingfeng Liu
Huifeng Yang
Boxian Liao
Jing Guo
Year: 2021
Energy-Aware Blockchain Resource Allocation Algorithm with Deep Reinforcement Learning for Trusted Authentication
SMARTGIFT
Springer
DOI: 10.1007/978-3-030-73562-3_8
Abstract
Internet of things (IoT) technology is in continuous development, and the access of the IoT power terminal is facing various security threats such as data tampering and malicious attacks. Thus, we propose a blockchain-based edge-terminal collaborative resource allocation architecture to solve these security problems, which places the terminal trusted authentication data on the blockchain to realize the security of the terminal authentication information. Since the mining process of the blockchain system will generate a large number of computing intensive tasks, this paper establishes an energy-oriented blockchain mining task offloading model, and proposes the energy-aware blockchain resource allocation (EABRA) algorithm with deep reinforcement learning (DRL) to jointly optimize the offloading decision and transmission power allocation decision. Finally, the simulation results show that the EABRA algorithm can save 68.87% energy consumption than the Random algorithm, which verifies the correctness and feasibility of the scheme.
