Edge computing oriented virtual optical network mapping scheme based on fragmentation prediction

As edge computing services soar,the problem of resource fragmentation situation is greatly worsened in elastic optical networks(EON).Aimed to solve this problem,this article proposes the fragmentation prediction model that makes full use of the gate recurrent unit(GRU)algorithm.Based on the fragmentation prediction model,one virtual optical network mapping scheme is presented for edge computing driven EON.With the minimum of fragmentation degree all over the whole EON,the virtual network mapping can be successively conducted.Test results show that the proposed approach can reduce blocking rate,and the supporting ability for virtual optical network services is greatly improved.

Virtualization Technology in Cloud Computing Based Radio Access Networks:A Primer

Since virtualization technology enables the abstraction and sharing of resources in a flexible management way, the overall expenses of network deployment can be significantly reduced. Therefore, the technology has been widely applied in the core network. With the tremendous growth in mobile traffic and services, it is natural to extend virtualization technology to the cloud computing based radio access networks(CCRANs) for achieving high spectral efficiency with low cost.In this paper, the virtualization technologies in CC-RANs are surveyed, including the system architecture, key enabling techniques, challenges, and open issues. The enabling key technologies for virtualization in CC-RANs mainly including virtual resource allocation, radio access network(RAN) slicing, mobility management, and social-awareness have been comprehensively surveyed to satisfy the isolation, customization and high-efficiency utilization of radio resources. The challenges and open issues mainly focus on virtualization levels for CC-RANs, signaling design for CC-RAN virtualization, performance analysis for CC-RAN virtualization, and network security for virtualized CC-RANs.

A Review in the Core Technologies of 5G: Device-to-Device Communication, Multi-Access Edge Computing and Network Function Virtualization

5G is a new generation of mobile networking that aims to achieve unparalleled speed and performance. To accomplish this, three technologies, Device-to-Device communication (D2D), multi-access edge computing (MEC) and network function virtualization (NFV) with ClickOS, have been a significant part of 5G, and this paper mainly discusses them. D2D enables direct communication between devices without the relay of base station. In 5G, a two-tier cellular network composed of traditional cellular network system and D2D is an efficient method for realizing high-speed communication. MEC unloads work from end devices and clouds platforms to widespread nodes, and connects the nodes together with outside devices and third-party providers, in order to diminish the overloading effect on any device caused by enormous applications and improve users’ quality of experience (QoE). There is also a NFV method in order to fulfill the 5G requirements. In this part, an optimized virtual machine for middle-boxes named ClickOS is introduced, and it is evaluated in several aspects. Some middle boxes are being implemented in the ClickOS and proved to have outstanding performances.

Heuristic Scheduling Algorithms for Allocation of Virtualized Network and Computing Resources

Cloud computing technology facilitates computing-intensive applications by providing virtualized resources which can be dynamically provisioned. However, user’s requests are varied according to different applications’ computation ability needs. These applications can be presented as meta-job of user’s demand. The total processing time of these jobs may need data transmission time over the Internet as well as the completed time of jobs to execute on the virtual machine must be taken into account. In this paper, we presented V-heuristics scheduling algorithm for allocation of virtualized network and computing resources under user’s constraint which applied into a service-oriented resource broker for jobs scheduling. This scheduling algorithm takes into account both data transmission time and computation time that related to virtualized network and virtual machine. The simulation results are compared with three different types of heuristic algorithms under conventional network or virtual network conditions such as MCT, Min-Min and Max-Min. e evaluate these algorithms within a simulated cloud environment via an abilenenetwork topology which is real physical core network topology. These experimental results show that V-heuristic scheduling algorithm achieved significant performance gain for a variety of applications in terms of load balance, Makespan, average resource utilization and total processing time.

A New Reliable System For Managing Virtual Cloud Network

Virtual cloud network(VCN)usage is popular today among large and small organizations due to its safety and money-saving.Moreover,it makes all resources in the company work as one unit.VCN also facilitates sharing of files and applications without effort.However,cloud providers face many issues in managing the VCN on cloud computing including these issues:Power consumption,network failures,and data availability.These issues often occur due to overloaded and unbalanced load tasks.In this paper,we propose a new automatic system to manage VCN for executing the workflow.The new system calledMulti-User Hybrid Scheduling(MUSH)can solve running issues and save power during workflow execution.It consists of three phases:Initialization,virtual machine allocation,and task scheduling algorithms.The MUSH system focuses on the execution of the workflow with deadline constraints.Moreover,it considers the utilization of virtual machines.The new system can save makespan and increase the throughput of the execution operation.

The Network Architecture and Protocols for Distributed Virtual Environment

In this paper, the properties of distributed virtual environment (DVE) and the requirements on computer networks is briefly reviewed. A multicast protocol, called sender initiated grouping multicast protocol for DVE (SIGMP), is proposed. This new multicast protocol is based on a novel concept, multicast group (MG), which divides all participants in a DVE system into groups, among which there is a multicast group trustee (MGT) node to manage the group. The protocol provides unreliable/reliable, totally ordered and multiple to multiple multicast transmission service for DVE systems without sacrificing the communication efficiency heavily. At the same time, reliable unicast and one to multiple multicast transmission services are also supported. The performance analysis of the new protocols is also presented. Based on SIGMP, a simple demonstration of DVE system is designed and implemented. This demo system is running on several SGI workstations connected by a FDDI and Ethernet network.

Transforming Data into Actionable Insights with Cognitive Computing and AI

How organizations analyze and use data for decision-making has been changed by cognitive computing and artificial intelligence (AI). Cognitive computing solutions can translate enormous amounts of data into valuable insights by utilizing the power of cutting-edge algorithms and machine learning, empowering enterprises to make deft decisions quickly and efficiently. This article explores the idea of cognitive computing and AI in decision-making, emphasizing its function in converting unvalued data into valuable knowledge. It details the advantages of utilizing these technologies, such as greater productivity, accuracy, and efficiency. Businesses may use cognitive computing and AI to their advantage to obtain a competitive edge in today’s data-driven world by knowing their capabilities and possibilities [1].

计算机网络实验课程教学改革研究

在计算机网络技术高速发展和大学生科学能力培养目标的新形势下,针对当前计算机网络实践教学存在的问题,提出“三位一体”的计算机网络实验课改革方案。从通信、协议和应用三个方面,构建计算机网络实验模块内容体系,综合运用现场实验、线上虚拟环境和虚拟仿真教学手段,充分激发学生的学习兴趣,有效发挥其学习专长,在教学设施投入受限的情况下,积极开展计算机网络实践教学。

计算机网络拓扑结构对虚拟现实传输效果的影响分析

阐述星形、环形、总线型和网状不同网络拓扑结构对虚拟现实数据传输速度、延迟、带宽利用率及稳定性的影响。采用理论分析与实验模拟的方法,为虚拟现实系统的网络设计提供优化方案。

一种基于VNC的智能应用服务系统的设计和实现

VNC是网络计算领域的一个重要发展,适用于运行在“瘦客户端”甚至“极瘦客户端”的终端设备上。但VNC在网络安全、会话保持、信息管理、交互性和兼容性功能上的不足与缺陷,使之并不能够应用于应用服务系统。该文面向应用服务系统,基于VNC并针对VNC的不足之处,扩展了其协议,增加了安全层,以及对用户会话的管理机制,设计实现了一个智能应用服务系统。

基于强化学习的边缘计算智能电网资源调度算法

智能电网是一种能够进行智能管理和优化的电力网络。网络虚拟化技术可以有效提高智能电网的资源利用率和可靠性,从而满足不同用户的差异化需求。在资源有限的情况下,传统的虚拟网络嵌入算法无法根据电力系统的资源使用情况和用户需求来动态调整虚拟资源的分配和映射。为解决这一问题,将边缘计算和虚拟化技术相结合,引入了一种基于强化学习的虚拟网络资源调度算法。仿真结果表明,该虚拟网络资源调度算法在提高电网的可靠性和资源利用率方面优于其他3种调度算法。

面向虚拟CDN的5G与MEC融合平台设计与实现

随着元宇宙等概念的提出,视频流应用对网络带宽和时延的要求越来越苛刻。针对传统CDN容易出现节点内设备负载不均衡造成时延过长的问题,提出了一个面向虚拟CDN的5G和MEC融合平台设计方案,并依照设计方案完成了平台的搭建。最后,通过高并发推拉流实验证明了该融合平台拓展了虚拟CDN的高并发能力。

计算机网络安全中虚拟网络技术的应用

计算机网络安全在现代社会得到广泛重视,这也对线上、线下各类防护技术提出了高要求。以计算机网络安全中常用虚拟网络技术为切入点,分析其常见应用形式、具体应用方法,包括应用需求分析、技术选择、提升安全防护的鲁棒性等,最后结合虚拟实验,对计算机网络安全中虚拟网络技术的应用成效进行论证,服务未来工作。

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。

基于VNC的远程实验室

设计并实现了一种基于虚拟网络计算机(Virtual Network Computing,VNC)的远程实验室的建设方案。通过远程实验室的建设,使校内优质的教学资源实现了共享,在让更多学生受益的同时,探索出一条网络实验教学的新模式。

基于虚拟网络嵌入的异构算力网络资源管理

随着人工智能大模型引领的新应用和新需求的蓬勃兴起,算力规模和计算技术正经历着前所未有的快速演进与多元化创新。然而,在算力网络呈现集群化和异构化趋势的同时,算力需求迅猛增长与资源利用低效性之间的矛盾日益凸显。如何实现对异构算力的统一高效管控以提升资源利用率,已成为当前研究的重要课题。基于网络虚拟化(network virtualization,NV)技术,提出了一种基于虚拟网络嵌入(virtual network embedding,VNE)异构跨域算力资源分配方法。具体而言,构建了一个基于深度强化学习(deep reinforcement learning,DRL)模型的策略网络,负责精准计算候选算网节点与链路,以实现资源优化分配。通过一系列仿真实验,验证了该方法的有效性,为解决异构算力管理问题提供了新的思路和方法。

基于云边自动化的工业控制系统关键技术及前景展望

本文探讨了基于云边自动化的工业控制系统的关键技术和未来发展前景。随着网络技术和人工智能的发展,工业控制系统正在从传统的分层、封闭架构向开放、平台化架构转变。云边自动化结合了云计算和边缘计算,优化了通信效率、系统灵活性和资源利用率。本文还讨论了虚拟化技术、网算控互动机制、新一代通信技术等方面的挑战和解决方案。最后,本文展望了云边自动化在设计制造一体化、IT/OT融合等领域的应用前景。

可靠性感知的边缘计算VNF实例放置

为了解决日益增长的延迟敏感型应用程序和用户需求与计算资源受限的冲突,移动边缘计算(Mobile Edge Computing,MEC)已经成为一种很有前途的计算范式。服务提供商通过在边缘环境中部署虚拟化网络功能(Virtual Network Functions,VNF),为用户提供更加高效和可扩展性的服务供应链(Service Function Chain,SFC)来满足用户请求。若在提供服务过程中出现不可靠的服务或严重的服务失败,可能导致用户的巨大损失,所以网络服务提供商必须保证提供持续可靠的服务。针对该问题,考虑了边缘服务器的可靠性,利用计算统一设备架构(Computational Unified Device Architecture,CUDA)支持的门控循环单元(Gate Recurrent Unite,GRU)来预测VNF实例是否可用,通过预测结果,提前对VNF进行备份,避免了过度冗余备份造成的成本过高问题。考虑服务器的存储资源有限,提出了基于VNF实例可用性的放置(RVP)算法,优化服务提供商的成本。最后对提出的算法进行了性能评估,实验结果验证了RVP算法的优越性。

人工智能技术在高校计算机网络教育中的应用

文中概述了人工智能技术及高校计算机网络教育的现状,详细分析了个性化教学资源推荐、自动化评估与反馈、虚拟助教、智能课堂教学等具体应用场景,并通过案例验证了其实效性。文中还剖析了人工智能技术在高校计算机网络教育中面临的挑战,如技术更新、教师培训、学生接受度等问题,并提出了相应的对策建议,同时展望了人工智能技术在高校计算机网络教育中的未来应用前景,为高校计算机网络教育的创新提供了理论支持,为实践操作提供了有益的参考。

移动感知的混合服务功能链部署策略研究

针对支持网络功能虚拟化的移动边缘计算网络中,移动用户的数据流请求通常需要经过由前向和后向服务功能链(Service Function Chain,SFC)共同组成的混合服务功能链(Hybrid SFC,H-SFC)进行处理.首先联合考虑移动用户的位置逗留概率及网络资源约束,以最大化网络吞吐量为目标定义了移动用户的H-SFC部署问题,利用整数线性规划对该问题建模.然后设计了一个动态辅助边权图,以保证H-SFC的顺序需求,部署最少的H-SFC覆盖最多的移动逗留位置为目标,提出了由H-SFC预部署和H-SFC调整两个子算法构成的移动感知混合服务功能链部署算法(Mobility-Aware H-SFC Deployment Algorithm,MA-HSFC-DA)对原问题进行求解.仿真结果表明,与其它算法相比,MA-HSFC-DA可以显著提高网络资源的利用率,获得更高的流接受率和网络吞吐量.