基于云网PoP的弹性边缘网络设计思路探讨

移动边缘云是公司“云+5G”双引擎战略的最佳契合点,边缘网络是发挥移动云“大云”产品和5G网络融合优势,实现云网统筹、构建运营商“连接+计算”核心能力的关键。运营商传统接入网存在云网割裂、分段入云和组网复杂等突出问题,难以适应边缘业务敏捷交付要求。本文通过深入分析边缘云业务特征和技术架构,对标业界主流云商建设实践,研究基于云网PoP网的边缘网络建设思路,创新性提出云网一体化规划设计和建设交付流程变革,基于云网POP统一网络和业务锚点,构建Overlay和Underlay融合双层加速网络架构,探索Spine-leaf化的新型城域接入网实现L3下沉和弹性扩容等方法,实现“云+网+应用”一体化敏捷交付的边缘网络能力。     

WSN低功耗低时延路径式协同计算方法

针对云计算应用于无线传感器网络(Wireless Sensor Network,WSN)时延敏感型业务时存在的高传输时延问题,提出了一种WSN低功耗低时延路径式协同计算方法。该方法基于一种云雾网络架构开展研究,该架构利用汇聚节点组成雾计算层;在数据传输过程中基于雾计算层的计算能力分步骤完成任务计算,降低任务处理时延;由于汇聚节点计算能力较弱,时延降低将导致能耗增加,WSN工作寿命减短,为此提出能耗约束下的任务映射策略,并利用离散二进制粒子群优化(Binary Particle Swarm Optimization,BPSO)算法解决能耗约束下的时延优化问题。仿真结果表明,在相同的能耗约束下,对比其他算法,基于BPSO算法得出的映射方案能有效降低业务处理时延,满足时延敏感型业务的需求。     

小微数据包高效无线传输技术的发展和趋势

5G-NR和B5G系统都需能高效地支持小微数据包(块)的传输,且在不同的无线传输技术(如宽带或超低时延)之间快速灵活地切换。系统梳理和比较和小微数据包(块)相关的多种无线传输技术,如两步RACH、预配置授权和公共资源竞争等,分析它们对3GPP各个系统和各个RAN协议的影响和复杂度优劣等,并进一步展望其未来发展和应用趋势。     

Clinical significance of contact lens related changes of ocular surface tissue observed on optical coherence images

PurposeTo investigate the relationship between the real contact lens imprint into the conjunctival tissue, observed by optical coherence tomography (OCT) and conjunctival staining and contact lens wearing comfort.Methods17 participants (mean age = 26.6 SD ± 3.6 years; 7 females) were fitted with three different contact lenses base curves of the same silicone hydrogel custom lens type (Visell 50; Hecht Contactlinsen, Au, Germany) in a randomised order. One lens was optimally fitted according to the manufacturer's recommendation, one fitted 0.4 mm flatter and one fitted 0.4 mm steeper. After 4 h of lens wear the contact lens edge in the area of the conjunctiva was imaged nasally and temporally using OCT (Optovue iVue SD-OCT). To correct the artefact due to optical distortion with OCT, the imprint of all worn lenses was measured on a glass plate afterwards. Conjunctival staining in the limbal region after 4 h of lens wear was classified using the CCLRU Grading Scale. Comfort scoring was based on visual analog scales from 0 (very poor) to 100 (excellent).ResultsThe mean conjunctival imprint of all contact lens edges was 32.0 ± 8.1 μm before and 7.3 ± 6.5 μm after distortion correction of the OCT images. The distortion corrected conjunctival imprint with the 0.4 mm steeper lens (11.5 ± 6.2 μm) was statistically significantly greater compared to the optimally fitted lens (6.5 ± 5.9 μm) (One-way ANOVA followed Tukey-test; p = 0.017) and greater compared to the 0.4 mm flatter lens (3.9 ± 5.3 μm) (p < 0.001). There was no statistically significant difference between the optimally fitted lens and the 0.4 mm flatter lens (p = 0.209). The nasally measured imprint (11.4 ± 9.0 μm) was significantly greater than the temporally measured (3.3 ± 7.6 μm) (p < 0.001). There was no statistically significant correlation between the amount of conjunctival imprint and the graded conjunctival staining (p = 0.346) or the wearer’s comfort (p = 0.735).ConclusionsContact lens edges imaged by OCT exhibited displacement artefacts. The observed conjunctival imprints are a combination of real conjunctival compression and artefacts. A deeper imprint of the contact lens into the conjunctiva caused by a steeper base curve was not related to clinically significant staining or changes in comfort after 4 h of lens wear. The observed differences between nasal and temporal imprint are likely to be caused by variations of conjunctival thickness and the shape of the underlying sclera.     

Determining robust reaction kinetics from limited data

Accurate chemical kinetics are essential for reactor design and operation. However, despite recent advances in “big data” approaches, availability of kinetic data is often limited in industrial practice. Herein, we present a comparative proof-of-concept study for kinetic parameter estimation from limited data. Cross-validation (CV) is implemented to nonlinear least-squares (LS) fitting and evaluated against Markov chain Monte Carlo (MCMC) and genetic algorithm (GA) routines using synthetic data generated from a simple model reaction. As expected, conventional LS is fastest but least accurate in predicting true kinetics. MCMC and GA are effective for larger data sets but tend to overfit to noise for limited data. LS-CV strongly outperforms these methods at much reduced computational cost, especially for significant noise. Our findings suggest that implementation of CV with conventional regression provides an efficient approach to kinetic parameter estimation with high accuracy, robustness against noise, and only minimal increase in complexity.     

基于QoE感知的星地一体化网络公平资源分配策略

星地一体化网络是卫星网络和地面网络互联，实现卫星网络和地面网络优势互补的一体化网络。随着无线通信的快速发展，卫星网络和地面网络的同频复用技术可有效提升资源利用效率，满足日益增长的无线数据业务需求。但由于无线数据业务类型的多样化和频谱资源的稀缺性，如何实现用户数据服务的服务体验质量（Quality of experience， QoE）和公平性提升也成为星地一体化网络亟待解决的关键问题。本文综合考虑信道时变性、服务体验多样性和服务公平性，提出了一种基于QoE感知的星地一体化网络资源分配策略。为此，将目标问题描述为基于时间平均的服务体验质量的网络公平效用最大化，并利用李雅普诺夫优化理论，将复杂的动态原始优化问题进一步转化并分解为3个瞬时优化子问题，每个子问题可以在每个时隙独立求解。同时，由于无线资源分配为典型的非凹混合组合优化问题，推导了一个低复杂度的两步算法来求解第三个资源分配子问题。仿真结果揭示了在不同的公平性参数下用户的长时QoE与公平性之间的折衷情况。     

基于Prophet人工智能算法的网络潮汐效应预测研究

本文使用Prophet人工智能算法研究与预测移动通信网络“潮汐效应”现象，探索网络“潮汐效应”在优化网络资源配置实现网络降本增效的作用。Prophet人工智能算法是一种简单、有效，且易于实现的人工智能算法。通过facebook的人工智能开源框架fbprophet，研究4G网络PRB利用率等网络资源指标的“潮汐效应”，并预测这些网络资源指标在未来的变化趋势，用来指导当前4G网络减容、扩容和4/5G节电节能等，实现优化网络资源配置达到降本增效的目的。