Digital twin driven and intelligence enabled content delivery in end-edge-cloud collaborative 5G networks

The rapid development of 5G/6G and AI enables an environment of Internet of Everything(IoE)which can support millions of connected mobile devices and applications to operate smoothly at high speed and low delay.However,these massive devices will lead to explosive traffic growth,which in turn cause great burden for the data transmission and content delivery.This challenge can be eased by sinking some critical content from cloud to edge.In this case,how to determine the critical content,where to sink and how to access the content correctly and efficiently become new challenges.This work focuses on establishing a highly efficient content delivery framework in the IoE environment.In particular,the IoE environment is re-constructed as an end-edge-cloud collaborative system,in which the concept of digital twin is applied to promote the collaboration.Based on the digital asset obtained by digital twin from end users,a content popularity prediction scheme is firstly proposed to decide the critical content by using the Temporal Pattern Attention(TPA)enabled Long Short-Term Memory(LSTM)model.Then,the prediction results are input for the proposed caching scheme to decide where to sink the critical content by using the Reinforce Learning(RL)technology.Finally,a collaborative routing scheme is proposed to determine the way to access the content with the objective of minimizing overhead.The experimental results indicate that the proposed schemes outperform the state-of-the-art benchmarks in terms of the caching hit rate,the average throughput,the successful content delivery rate and the average routing overhead.

A Motivate Mechanism for Large-Scale P2P Content Delivery System

For lack of effective resource adjustment method, the supply-demand relationship of each resource in P2P content delivery system are often unbalanced. Especially after a popular content releasing, a burst of downloaders often can＇t find sufficient uploaders and their request may starve the upload capacity of server. Therefore the overall system QoS may be degraded. To tackle such issue, this paper proposes a download rate accelerate mechanism, called motivate mechanism. With it, the system can quickly find out the files becoming insufficient by monitoring the operating status of the files hourly, Then it promptly increase the number of copies of those files by using free rider nodes so that the whole system QoS is maintained and the system performance is improved. The experiment results on the practical operating system of Tencent demonstrated that the proposed mechanism increases the download rate, saves the traffic on the server and optimizes the system performance.

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.

Coded Multicasting for Content Delivery over Predictable Time-Varying Satellite Communication Networks

With the development of astronautic technology, communication satellites now have a tremendous gain in both quantity and quality, and have already shown their capability on multi-functional converged communication other than telecommunication. Under this circumstance, increasing the transmission efficiency of satellite communication network becomes a top priority. In this paper, we focus on content delivery service on satellite networks, where each ground station may have prefetched some file fragments. We cast this problem into a coded caching framework so as to exploit the coded multicast gain for minimizing the satellite communication load. We first propose an optimization-based coded multicast scheme by considering the special property that the satellite network topology is predictable and timevariant. Then, a greedy based fast algorithm is proposed, which can tremendously reduce the computation complexity with a small loss in optimality. Simulation experiments conducted on two Walker constellation satellite networks show that our proposed coded multicast method can efficiently reduce the communication load of satellite networks.

Layered Coded Cache Placement and Cooperative Delivery with Sharing Links in Satellite-Terrestrial Integrated Networks

Cooperative utilization of multidimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks(STINs) can provide a feasible approach for massive streaming media content delivery over the seamless global coverage area. However, the on-board supportable resources of a single satellite are extremely limited and lack of interaction with others. In this paper, we design a network model with two-layered cache deployment, i.e., satellite layer and ground base station layer, and two types of sharing links, i.e., terrestrial-satellite sharing(TSS) links and inter-satellite sharing(ISS) links, to enhance the capability of cooperative delivery over STINs. Thus, we use rateless codes for the content divided-packet transmission, and derive the total energy efficiency(EE) in the whole transmission procedure, which is defined as the ratio of traffic offloading and energy consumption. We formulate two optimization problems about maximizing EE in different sharing scenarios(only TSS and TSS-ISS),and propose two optimized algorithms to obtain the optimal content placement matrixes, respectively.Simulation results demonstrate that, enabling sharing links with optimized cache placement have more than 2 times improvement of EE performance than other traditional placement schemes. Particularly, TSS-ISS schemes have the higher EE performance than only TSS schemes under the conditions of enough number of satellites and smaller inter-satellite distances.

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.

The Outcome of Midwife-Mother Relationship in Delivery Room: A Qualitative Content Analysis

Effective communication and emotional support of parturient women improve the outcome of childbirth. Reduction in Duration of labor, cesarean rate, use of anesthesia, and 5 minute Apgar Score less than 7 can achieve. This study was a part of a large mixed method study during 2013-2014. In this qualitative study, in-depth interviews were conducted with 32 participants (16 mother and 16 midwife), using semi-structured interviews. Participants were recruited by pur-posive sampling with maximum diversity in terms of age, occupation, education and etc. Educational hospital of Arak University of Medical Sciences was considered as the setting. Each interview was conducted at a private and convenient location and took about 30 to 45 minutes. Interviews were audio taped and transcribed verbatim. Conventional content analysis was done for data analysis. Interviews continued until data saturation was obtained. Data were coded in MAXQDA software (version 11). The main category emerged as “outcome” of midwife-mother relationship. Facilitating childbirth, positive experience, mental health promotion and improvement in quality of life were derived as subcategories. Good midwife-mother relationship could promote positive outcome in labour. Results could assist midwives in providing holistic quality care to mothers during labour, thus providing positive consequence in child birth. Also, results could provide a framework and guidance for policymakers to create appropriate context for the midwife-mother relationship in maternity care.

Smart Caching for QoS-Guaranteed Device-to-Device Content Delivery

Caching at user equipment(UE) provides a feasible way for device-to-device(D2D) content delivery among proximal users without deploying additional infrastructures. To support D2D content delivery for mobile traffics with quality-of-service(QoS) requirements, smart caching problem is essential to be solved especially when there is no prior knowledge on demands of proximal users. In this paper, impacts of Qo S requirements and limited caching capacity on UE caching are analyzed, respectively, based on which a caching scheme is proposed. With the proposed caching scheme, UE can determine whether caching a content or not intelligently to guarantee a content request via D2D communications in the network. Simulation results are presented which verify the analyzed influencing factors on D2D caching and the proposed QoS-provisioning caching scheme.

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.

CACTSE:Cloudlet Aided Cooperative Terminals Service Environment for Mobile Proximity Content Delivery

Along with the rapid development of communications,the Internet,and smart terminals,mobile Internet has become a hot topic with both opportunities and challenges.In this article,a new perspective on edge content delivery service for mobile Internet is described,based on cooperating terminals.A mobile cloud architecture named Cloudlet Aided Cooperative Terminals Service Environment(CACTSE) is proposed as an edge network service environment.The Service Manager(SM),a cloudlet like module,is introduced into the local service domain in order to manage the in-domain terminals and help coordinate the content delivery requests for better bandwidth efficiency as well as user experience.The reference model is presented in this article with architecture and mechanism design.Moreover,the research progress and potential technology trends of CACTSE are analysed based on the related R&D directions.

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.

卫星内容分发网络安全威胁及安全机制分析

随着卫星互联网技术的发展,卫星内容分发网络(Content Delivery Network,CDN)成为卫星互联网最有潜力的应用场景之一,在提升信息访问体验和缓解地面互联网主干压力方面发挥着重要作用。然而,卫星CDN也面临着一系列安全威胁。通过对不同攻击模型在卫星CDN发生的可能性以及严重程度进行梳理,分析现有安全机制在卫星CDN安全场景适用程度及存在问题。在此基础上,总结卫星CDN安全威胁发生的根源以及可能的技术路径,展望了未来卫星CDN安全的研究方向。

西霞院水库场次洪水排沙规律及影响因素

西霞院水库作为小浪底水库的反调节水库,在调节小浪底水库下泄的不稳定流方面起着重要作用。西霞院水库自运行以来,水库呈持续淤积趋势,研究西霞院水库排沙能力对于减缓水库淤积具有重要意义。基于西霞院水库2011—2022年实测水沙资料,对西霞院水库的历年排沙过程以及排沙影响因素进行深入分析,结果表明:西霞院水库排沙受水库运用方式、来水来沙条件等多种因素影响;流量沿程变化系数、入库含沙量对水库排沙比影响较大,且排沙比与流量沿程变化系数显著正相关,与入库含沙量显著负相关;选取流量沿程变化系数、入库含沙量两个显著相关的参数,通过回归分析建立水库排沙比计算公式,决定系数为0.79,排沙比计算值与实测值拟合效果较好。

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。

媒介融合时代电视新闻制作技术创新策略

深入探讨当前电视新闻制作的现状,分析媒介融合时代电视新闻制作技术架构的特点。针对融媒体内容库、生产管理平台、新闻内容生产工具及互联网发布等电视新闻制作关键环节,提出一系列创新策略,旨在提高电视新闻制作的效率、质量和灵活性,进而适应新媒体时代观众对新闻信息的需求。

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。