%0 Journal Article
%A 魏翼飞
%A 薛晨子
%A 张勇
%T <span class="fontstyle0">Performance optimization for smart grid blockchain integrated with fog computing using DDQN</span>
%D 2021
%R 10.19682/j.cnki.1005-8885.2021.1006
%J 中国邮电高校学报（英文）
%P 68-78
%V 28
%N 2
%X <span class="fontstyle0">In order to solve the energy crisis and pollution problems, smart grid is widely used. However, there are many<br>
challenges such as the management of distributed energy during the construction. Blockchain, as an emerging<br>
technology, can provide a secure and transparent solution to the decentralized network. Meanwhile, fog computing<br>
network is considered to avoid the high deployment cost. The edge servers have abundant computing and storage<br>
resources to perform as nodes in grid blockchain. In this paper, an innovative structure of smart grid blockchain<br>
integrated with fog computing are proposed. And a new consensus mechanism called scalable proof of cryptographic<br>
selection (SPoCS) is designed to adapt the hybrid networks. The mechanism not only includes a special index,<br>
contribution degree, to measure the loyalty of fog nodes and the probability of being a function node, but also has<br>
flexible block interval adjustment method. Meanwhile, the number of function nodes (validating nodes and ordering<br>
nodes) can also be adjusted. And a deep reinforcement learning (DRL) method is used to select the appropriate<br>
quantity to improve the performance under the strict constraints of security and decentralization. The simulation<br>
shows the scheme performs well in the throughput, cost and latency.</span> <br>
%U https://jcupt.bupt.edu.cn/CN/10.19682/j.cnki.1005-8885.2021.1006