ID	原文	译文
4333	在星地协同网络中引入移动边缘计算（MEC）技术可有效提高用户体验质量和减少网络冗余流量，同时也带来了一些挑战。	The introduction of mobile edge computing (MEC) technology in satellite-terrestrial networks can effectivelyimprove the quality of user experience and reduce network redundant traffic, but also brings some challenges.
4334	首先介绍了星地协同网络和 MEC 技术的基本架构，并讨论了在星地协同网络中引入 MEC 技术的动机和 MEC 的部署问题；	Firstly, thebasic architecture of satellite-terrestrial networks and MEC technology was introduced. Moreover, the motivation of in-troducing MEC into satellite-terrestrial networks and the deployment of MEC were discussed.
4335	然后提出了融合 MEC 的星地协同网络架构，并对其关键技术及典型应用进行了概述和分析；	Then, the architecture ofMEC enabled satellite-terrestrial networks was proposed, and the key techniques and typical applications were summa-rized and analyzed.
4336	最后总结归纳了融合网络架构中的任务调度、移动性管理等关键挑战和一些开放性研究问题，期望对该领域的后续研究提出可供借鉴的新思路。	Finally, the key challenges such as task scheduling and mobility management and some open researchissues in integrated networks were summarized. It hopes to provide new ideas for future research in this field.
4337	网络流量的自相似特性会导致网络中数据的突发状态持续，为有效降低网络流量突发引起的队列排队时延和分组丢失率，提高不同优先级业务的传输能力，保障业务服务质量需求，提出了一种基于网络流量自相似特性的队列调度算法——P-DWRR。	Self-similarity characteristic of network traffic will lead to the continuous burstness of data in the network. In order to effectively reduce the queue delay and packet loss rate caused by network traffic burst, improve the transmissioncapacity of different priority services, and guarantee the service quality requirements, a queue scheduling algorithmP-DWRR based on the self-similarity of network traffic was proposed.
4338	该算法设计了基于自相似流量水平分级预测结果的动态权值分配方法及服务量子更新方法，并根据业务优先级和队列等待时间确定队列的服务次序，以减小数据分组排队时延，降低分组丢失率。	A dynamic weight allocation method and a servicequantum update method based on the self-similar traffic level grading prediction results were designed, and the service order of the queue according was determined to the service priority and queue waiting time, so as to reduce the queuing delay and packet loss rate.
4339	仿真结果表明，P-DWRR 算法在满足网络不同业务优先级要求的基础上，降低了数据分组的排队时延、时延抖动和分组丢失率，性能优于 DWRR 和 VDWRR。	The simulation results show that the P-DWRR algorithm can reduce the queueing delay, delayjitter and packet loss rate on the basis of satisfying the different service priority requirements of the network, and its per-formance is better than that of DWRR and VDWRR.
4340	针对低轨多波束卫星星座网络中空间段卫星对地覆盖不均匀导致某些区域相对密集，造成严重的波束间干扰与不必要的波束资源开销等问题，提出了在满足覆盖等要求下的波束关闭算法。	Aiming at the problems of the relatively dense coverage of the satellites in the space segment of the low earthorbit (LEO) multibeam satellite constellation network, which resulted in relatively dense areas in some regions, causing severe inter-beam interference and unnecessary beam resource overhead, a beam shut-off algorithm was proposed withglobal coverage requirements.
4341	以多波束低轨星座网络为研究对象，分析并建立了低轨星座网络波束关闭的最优化问题，进而分析并论证了该问题的 NP 完全属性，给出了探索式求解方法。	The dynamic beam shut-off (DBSO) optimization problem was formulated in LEO multi-beam satellite constellation network. Then, the problem was proved to be NP-complete and a heuristic DBSO algorithmwas proposed.
4342	以共计 3 168 个波束的铱星星座网络为仿真场景，仿真分析了所提出的探索式波束关闭算法。仿真结果表明，所提算法仅需要 1 913 个波束即可实现对全球区域的连续覆盖，降低了 39.61 %的波束资源开销。	Simulation scenario considers the Iridium constellation network scenario with total 3 168 beams, and itshows that the number of required activated beams is only 1 913 with 39.61% beam resource reduction.