Quality-Aware Massive Content Delivery in Digital Twin-Enabled Edge Networks

Massive content delivery will become one of the most prominent tasks of future B5G/6G communication.However,various multimedia applications possess huge differences in terms of object oriented(i.e.,machine or user)and corresponding quality evaluation metric,which will significantly impact the design of encoding or decoding within content delivery strategy.To get over this dilemma,we firstly integrate the digital twin into the edge networks to accurately and timely capture Quality-of-Decision(QoD)or Quality-of-Experience(QoE)for the guidance of content delivery.Then,in terms of machinecentric communication,a QoD-driven compression mechanism is designed for video analytics via temporally lightweight frame classification and spatially uneven quality assignment,which can achieve a balance among decision-making,delivered content,and encoding latency.Finally,in terms of user-centric communication,by fully leveraging haptic physical properties and semantic correlations of heterogeneous streams,we develop a QoE-driven video enhancement scheme to supply high data fidelity.Numerical results demonstrate the remarkable performance improvement of massive content delivery.

Cooperative Content Caching and Delivery in Vehicular Networks: A Deep Neural Network Approach

The growing demand for low delay vehicular content has put tremendous strain on the backbone network.As a promising alternative,cooperative content caching among different cache nodes can reduce content access delay.However,heterogeneous cache nodes have different communication modes and limited caching capacities.In addition,the high mobility of vehicles renders the more complicated caching environment.Therefore,performing efficient cooperative caching becomes a key issue.In this paper,we propose a cross-tier cooperative caching architecture for all contents,which allows the distributed cache nodes to cooperate.Then,we devise the communication link and content caching model to facilitate timely content delivery.Aiming at minimizing transmission delay and cache cost,an optimization problem is formulated.Furthermore,we use a multi-agent deep reinforcement learning(MADRL)approach to model the decision-making process for caching among heterogeneous cache nodes,where each agent interacts with the environment collectively,receives observations yet a common reward,and learns its own optimal policy.Extensive simulations validate that the MADRL approach can enhance hit ratio while reducing transmission delay and cache cost.

Proactive Content Delivery for Vehicles over Cellular Networks:the Fundamental Benefits of Computing and Caching

The emergence of self-driving technologies implies that a future vehicle will likely become an entertainment center that demands personalized multimedia contents with very high quality. The surge of vehicular content demand brings significant challenges for the fifth generation(5G) cellular communication network. To cope with the challenge of massive content delivery, previous studies suggested that the 5G mobile edge network should be designed to integrate communication, computing, and cache(3C) resources to enable advanced functionalities such as proactive content delivery and in-network caching. However, the fundamental benefits achievable by computing and caching in mobile communications networks are not yet properly understood. This paper proposes a novel theoretical framework to characterize the tradeoff among computing, cache, and communication resources required by the mobile edge network to fulfill the task of content delivery. Analytical and numerical results are obtained to characterize the 3C resource tradeoff curve. These results reveal key insights into the fundamental benefits of computing and caching in vehicular mobile content delivery networks.

算网融合CDN关键技术分析和研究

视频业务已经进入到产业视频时代,CDN不仅需要应对视频低时延传输的挑战,而且需要对多媒体算力和分发能力进行综合调度,以实现对各种泛视频业务的统一承载。文章以构建算网融合CDN为目标,介绍视联网、IPv6/SRv6、QUIC等热门技术的发展成果,并对其实现涉及的关键技术进行初步分析和研究。

MEC与CDN融合体系架构方案设计研究

MEC被广泛应用于CDN边缘下沉解决方案中,利用MEC实现CDN边缘部署,提升CDN应用的服务质量。首先,总结并分析了CDN技术演进历程及未来发展趋势;然后,提出了5G网络场景下MEC与CDN融合体系架构设计方案,所提方案具有MEC与CDN管理层解耦的特点,支持MEC-vCDN集群与传统CDN集群兼容并存;最后,搭建了MEC-vCDN模块及5G网络模块,测试了方案中各模块的功能。

浅析CDN技术在远程教育中的应用

随着互联网技术的飞速发展和普及,CDN(Content Delivery Network)技术以其高效、稳定、可靠的内容分发能力,为远程教育提供了强有力的技术支持。文章解析了CDN技术的工作原理,并从提高视频直播的流畅度和稳定性,保障资源的可用性与可靠性,增强在线互动体验,提升平台安全性与隐私保护,提升平台的可扩展性与灵活性五个方面阐述了CDN技术在远程教育中的积极作用。

基于CDN的广播电视流媒体传输质量优化方法

随着互联网技术的发展和普及,广播电视流媒体传输已经成为人们获取信息和娱乐的重要方式之一。然而由于网络环境的复杂性和不稳定性,如何保证流媒体传输的质量成一个重要的问题。内容分发网络(Content Distribution Network,CDN)作为一种有效的解决方案被广泛应用于流媒体传输。为优化传输质量、提高用户体验,探讨基于CDN的广播电视流媒体传输质量优化方法。

Contract-Based Content Delivery in 5G Converged Networks

Mobile broadcasting services provided by converged networks do aid in satisfying users' demands for popular multimedia content while unicasting services offer personalized experiences for users.We analyze hybrid broadcasting unicasting framework from the perspective of network economics,where content provider(CP) figures out the cooperation of broadcasting and unicasting services providers,as long as their pricing strategies.To this end,a contract-based content delivery scheme is proposed.The profit of CP depends on users' preference and satisfaction for unicasting and broadcasting transmission.CP provides different users with distinctive data packages.The intent is to maximize its own profit.By classifying users into different types,the optimal contract in close form is derived.Numerical results show that the proposed optimal contract is able to generate incentive for users to employ broadcasting transmission,which further benefits both the CP and users.

Caching Algorithm with a Novel Cost Model to Deliver Content and Its Interest over Content Centric Networks

Recently the content centric networks(CCNs) have been advocated as a new solution to design future networks. In the CCNs, content and its interest are delivered over the content store and pending interest table, respectively, where both have limited capacities. Therefore, how to design the corresponding algorithms to efficiently deliver content and inertest over them becomes an important issue. In this paper, based on the analysis of content distribution, status of content store, and pending interest, we propose a novel caching algorithm with which the resources of content store and pending interest table can be efficiently used. Simulation results prove that the proposal can outperform the conventional methods.

Algorithms to Calculate the Most Reliable Maximum Flow in Content Delivery Network

Calculating the most reliable maximum flow(MRMF)from the edge cache node to the requesting node can provide an important reference for selecting the best edge cache node in a content delivery network(CDN).However,SDBA,as the current state-of-the-art MRMF algorithm,is too complex to meet real-time computing needs.This paper proposes a set of MRMF algorithms:NWCD(Negative Weight Community Deletion),SCPDAT(Single-Cycle Preference Deletion Approximation algorithm with Time constraint)and SCPDAP(Single-Cycle Preference Deletion Approximation algorithm with Probability constraint).NWCD draws on the“flow-shifting”algorithm of minimum cost and maximum flow,and further defines the concept of negative weight community.This algorithm continuously deletes the negative weight communities,which can increase reliability while keeping the flow constant in the residual graph.It is proven that when all negative weight communities are deleted,the corresponding maximum flow is the MRMF.SCPDAT tries to approach the optimal solution to the greatest extent possible within the limited time,while SCPDAP tries to reach the probability threshold in the shortest amount of time.Both of these adopt the strategy of first deleting single-cycle communities(which contribute more to the reliability with lower time cost).Experiments show that,compared with SDBA,NWCD combined with the probabilistic pruning achieves an order of magnitude improvement in time cost,while SCPDAT and SCPDAP demonstrate better time performance and increased applicability.

浅析CDN技术及其在政务信息服务的应用实践——以自然资源部政务信息服务平台为例

随着互联网多媒体信息的快速发展,内容分发网络(CDN)技术的研究和应用已成为当前网络技术发展的重要领域之一。本文解析了CDN的工作原理及关键技术,结合自然资源部政务信息服务平台的实践应用,阐述了CDN的分布式架构部署和动静态分类加速策略,梳理总结了当前技术条件下超文本传输安全协议(HTTPS)安全加速策略的优势和劣势,指出了CDN在HTTPS安全加速方面存在的缺陷和隐患,提出了“双证书”的解决方案。通过实际应用数据监测对比,CDN在跨运营商数据传输、带宽资源拓展、访问速度提高、源站安全性增强方面具有明显技术优势,对提升自然资源政务信息服务水平和质量起到了积极作用。

CDN技术在远程教育中的应用

论述了CDN技术的基本原理及当前应用状况 ,结合远程教学过程的特点深入探讨了实现CDN的关键技术。

面向CDN网络的高效海量数据分发机制研究

针对CDN网络中海量数据分发的要求,设计了一种基于CDN服务器P2P服务的高效数据分发机制,通过对分割后的海量数据分别执行P2P数据分发,克服了现有CDN服务器P2P服务不能根据Internet网络带宽和CDN服务器负载动态变化自适应地调整数据分发过程的缺点。仿真结果表明,提出的海量数据分发机制提高了网络带宽波动对数据分发的性能,能够较好地满足实际CDN网络中海量数据分发的需求。

CDN技术及其在广电中的应用

介绍了CDN的发展状况、市场情况,分析了CDN所采用的关键技术,剖析了目前国内外研发CDN的主要厂商的实现方案,提出了CDN在广电中的几种应用。研究表明,CDN在广电中有着广泛的应用,对广电的发展起着至关重要的作用。

基于融合CDN构建未来智能内容管道

详细探讨了传统CDN向融合CDN的演进方案、融合CDN构建智能内容管道的方法及在管道中的作用。为了更好地支撑业务发展,融合CDN需要与承载网络相互渗透,具备网络感知、业务感知、用户感知三大能力。为了保障移动业务的更好体验,提出CDN的网络位置应该下移到无线网络中,并根据无线网络的特性进行适配和优化。

基于Stackelberg博弈的云CDN缓存资源分配算法

为提高云存储环境下内容分发网络(CDN)的分发效率,提出一种基于Stackelberg博弈的缓存资源分配与定价算法。将Web服务器和云CDN代理商建模成一个多主多从的Stackelberg博弈模型,并构建其各自的效用函数。证明在代理商价格确定的情况下存在Web服务器纳什均衡点,利用一种分布式迭代算法求解博弈模型,得到最优定价与该定价下的最优缓存分配结果。仿真结果表明,该算法可保证Web服务器缓存需求在代理商之间的高效分配,与用户服务质量优先算法相比,可使Web服务器获得更高的单位成本效益。

CDN网络中对象一致性算法研究

针对内容分发网络设计的基于请求的对象一致性算法ROCA,以对象的请求频度为依据,按照一定的刷新间隔TTR,从web服务器下载对象的最新版本.但ROCA算法存在着对象情况的滞后感知问题,本文提出了对象模糊聚类算法OFCA,并对ROCA进行了优化.OFCA算法以对象名称属性的概念分层为基础,通过模糊聚类找出同类对象修改的共同规律,并以此为依据修正TTR.基于轨迹驱动的仿真结果表明,算法获得的刷新时间符合对象的修改规律,模糊聚类算法对ROCA有明显的改进.

CDN技术在国土资源信息服务系统中的应用——以资源网为例

国土资源信息服务类网站信息服务覆盖广、浏览量大、易受到黑客和病毒的攻击。本文以资源网为例,主要介绍CDN技术在国土资源信息服务系统中的应用。CDN技术的引入,可以大规模多区域加速,保证用户的就近访问,隐藏源站服务器,对于提高国土资源信息服务类网站的响应速度,提高网站的安全性具有重大的现实意义。

基于CDN的电力数据通信网加速技术研究及实现

目前,CDN网络已经成为数据通信网加速和改善网络体验的必要手段之一。国家电网公司信息系统应用不断深化,用户数急剧增多,业务发展呈现复杂性、波动性、模糊性和不确定性,云计算、大数据、电力物联网等新业务都对网络提出了新的挑战。文章对电力信息业务的加速需求进行了深入剖析,结合电力数据通信网架构,提出了电力CDN的网络架构、部署原则以及网络带宽需求设计,同时进行了电力CDN管理平台功能架构整体设计。在北京、上海、天津三地的电力数据通信网部署了电力CDN网络,开展了Web、流媒体、文件下载等业务加速,并对加速性能进行了分析。电力CDN网络在页面加载、流媒体点播、文件下载三大业务上,实现了加速2倍以上,源站访问流量节约99%以上,极大地增强了用户网络体验,缓解了骨干网及源站访问流量压力。