ID	原文	译文
3233	基于此，首先介绍了拟态调度算法技术和目标，然后从调度对象、调度数量及调度时机这 3 个方面对调度算法研究现状进行了分析总结，最后展望了拟态调度算法未来的研究方向与趋势。	Based on this, the principle and goal of mimic scheduling algorithm were firstly introduced. Then the state-of-the-art of mimic scheduling algorithms were analyzed and summarized from three aspects, such as scheduling object, scheduling quantity and scheduling timing. Finally, the future research direction and trend of mimic schedulingalgorithms were prospected.
3234	在能源互联网中引入无人机进行电力线路巡查，并借助移动边缘计算技术实现巡检任务的接入和处理，可降低服务成本，提高工作效率。	In order to reduce the cost and improve efficiency of power line inspection, UAV (unmanned aerial vehicle),which use mobile edge computing technology to access and process service data, are used to inspect power lines in theenergy internet.
3235	但是，由于无人机数据传输需求和地理位置的动态变化，易造成边缘服务器负载不均衡，致使巡检业务处理时延和网络能耗较高。	However, due to the dynamic changes of UAV data transmission demand and geographical location, theedge server load will be unbalanced, which causes higher service processing delay and network energy consumption.
3236	为解决以上问题，提出基于深度强化学习的能源互联网智能巡检任务分配机制。	Thus, an intelligent inspection task allocation mechanism for energy internet based on deep reinforcement learning wasproposed.
3237	首先，综合考虑无人机和边缘节点的运动轨迹、业务差异化的服务需求、边缘节点有限的服务能力等，建立面向时延、能耗等多目标联合优化的双层边缘网络任务卸载模型。	First, a two-layer edge network task offloading model was established to archive joint optimization of mul-ti-objectives, such as delay and energy consumption. It was designed by comprehensively considering the route of UAVand edge nodes, different demands of services and limited service capabilities of edge nodes.
3238	进而，基于 Lyapunov 优化理论和双时间尺度机制，采用近端策略优化的深度强化学习算法，对固定边缘汇聚层和移动边缘接入层边缘节点间的连接关系和卸载策略进行求解。	Furthermore, based onLyapunov optimization theory and dual-time-scaled mechanism, proximal policy optimization algorithm based deep re-inforcement learning was used to solve the connection relationship and offloading strategy of edge servers between fixededge sink layer and mobile edge access layer.
3239	仿真结果表明，所提机制能够在保证系统稳定的情况下降低服务时延和系统能耗。	The simulation results show that, the proposed mechanism can reduce theservice request delay and system energy consumption while ensuring the stability of system.
3240	针对电子健康档案（EHR）在分布式系统中的密钥管理及用户身份追溯问题，提出了一种基于区块链的分布式 EHR 细粒度可追溯方案。	Aiming at the key management of electronic health records (EHR) in a distributed system and user identitytracing issues, a distributed EHR fine-grained traceability scheme based on blockchain was proposed.
3241	结合变色龙哈希和零知识证明技术实现区块链上节点的注册与身份证明的生成，从而实现区块链上恶意用户的追溯。	Combining chame-leon hash and zero-knowledge proof technology, the registration of nodes on the blockchain and the generation of identitycertificates were realized, and the traceability of malicious users on the blockchain was realized.
3242	针对密钥管理的单点故障问题，设计了分布式密文策略的属性基加密方案实现安全细粒度的数据访问控制，设置多个解密机构区块链节点联合分发用户节点的属性私钥。	Besides, given the singlepoint of failure problem of key management, the attribute-based encryption scheme of distributed ciphertext strategy wasdesigned to achieve secure and fine-grained data access control, and multiple decryption agency blockchain nodes wereset up to jointly distribute the attribute private keys of user nodes.