Mobile Fog Computing by Using SDN/NFV on 5G Edge Nodes

Fog computing provides quality of service for cloud infrastructure. As the data computation intensifies, edge computing becomes difficult. Therefore, mobile fog computing is used for reducing traffic and the time for data computation in the network. In previous studies, software-defined networking (SDN) and network functions virtualization (NFV) were used separately in edge computing. Current industrial and academic research is tackling to integrate SDN and NFV in different environments to address the challenges in performance, reliability, and scalability. SDN/NFV is still in development. The traditional Internet of things (IoT) data analysis system is only based on a linear and time-variant system that needs an IoT data system with a high-precision model. This paper proposes a combined architecture of SDN and NFV on an edge node server for IoT devices to reduce the computational complexity in cloud-based fog computing. SDN provides a generalization structure of the forwarding plane, which is separated from the control plane. Meanwhile, NFV concentrates on virtualization by combining the forwarding model with virtual network functions (VNFs) as a single or chain of VNFs, which leads to interoperability and consistency. The orchestrator layer in the proposed software-defined NFV is responsible for handling real-time tasks by using an edge node server through the SDN controller via four actions: task creation, modification, operation, and completion. Our proposed architecture is simulated on the EstiNet simulator, and total time delay, reliability, and satisfaction are used as evaluation parameters. The simulation results are compared with the results of existing architectures, such as software-defined unified virtual monitoring function and ASTP, to analyze the performance of the proposed architecture. The analysis results indicate that our proposed architecture achieves better performance in terms of total time delay (1800 s for 200 IoT devices), reliability (90%), and satisfaction (90%).     

基于软件定义网络的触觉互联网端到端系统

针对现有蜂窝系统无法满足触觉互联网延迟问题,提出一种基于软件定义网络的触觉互联网端到端系统。首先给出了触觉互联框架;然后提出一种基于软件定义网络（SDN）的多层触觉互联网端到端体系结构,该结构基于5G蜂窝系统,将硬件和软件分离,并提供API以便于系统的控制和管理,网络核心采用SDN并启用网络功能虚拟化（NFV）,系统在多级云单元中使用移动边缘计算（MEC）,减少通信过程中涉及中间节点的数量,从而减少延迟。实验结果表明该架构在5G高速率下能够得到毫秒级延迟,说明所提框架的可行性和有效性。     

Edge Computing Platform with Efficient Migration Scheme for 5G/6G Networks

Next-generation cellular networks are expected to provide users with innovative gigabits and terabits per second speeds and achieve ultra-high reliability, availability, and ultra-low latency. The requirements of such networks are the main challenges that can be handled using a range of recent technologies, including multi-access edge computing (MEC), artificial intelligence (AI), millimeter-wave communications (mmWave), and software-defined networking. Many aspects and design challenges associated with the MEC-based 5G/6G networks should be solved to ensure the required quality of service (QoS). This article considers developing a complex MEC structure for fifth and sixth-generation (5G/6G) cellular networks. Furthermore, we propose a seamless migration technique for complex edge computing structures. The developed migration scheme enables services to adapt to the required load on the radio channels. The proposed algorithm is analyzed for various use cases, and a test bench has been developed to emulate the operator’s infrastructure. The obtained results are introduced and discussed.     

SoftAir: A software defined networking architecture for 5G wireless systems

One of the main building blocks and major challenges for 5G cellular systems is the design of flexible network architectures which can be realized by the software defined networking paradigm. Existing commercial cellular systems rely on closed and inflexible hardware-based architectures both at the radio frontend and in the core network. These problems significantly delay the adoption and deployment of new standards, impose significant challenges in implementing and innovation of new techniques to maximize the network capacity and accordingly the coverage, and prevent provisioning of truly- differentiated services which are able to adapt to growing and uneven and highly variable traffic patterns. In this paper, a new software-defined architecture, called SoftAir, for next generation (5G) wireless systems, is introduced. Specifically, the novel ideas of network function cloudification and network virtualization are exploited to provide a scalable, flexible and resilient network architecture. Moreover, the essential enabling technologies to support and manage the proposed architecture are discussed in details, including fine-grained base station decomposition, seamless incorporation of Openflow, mobility- aware control traffic balancing, resource-efficient network virtualization, and distributed and collaborative traffic classification. Furthermore, the major benefits of SoftAir architecture with its enabling technologies are showcased by introducing software- defined traffic engineering solutions. The challenging issues for realizing SoftAir are also discussed in details.     

网络功能虚拟化下服务功能链的资源管理研究综述

伴随着云计算,软件定义网络和网络功能虚拟化等网络新技术的出现,未来网络运维向着虚拟化、智能化的方向不断迈进.网络功能虚拟化提供了一种服务节点虚拟化的方法,它采用通用服务器替代传统网络中的专用中间件,可以大大降低网络运营商的建设和运营成本,提升网络管理的灵活性和可扩展性.由于网络端到端服务通常需要不同的服务功能,采用虚拟化技术构建网络服务功能链,进行资源的合理分配和调度成为一个重要的研究课题,引起了学术界和工业界的广泛关注.从网络功能虚拟化的技术背景出发,介绍了网络功能虚拟化下服务功能链资源管理的基础架构、技术基础和应用场景.而后基于服务功能链编排的不同阶段,将现有理论研究划分为4个部分:组链、部署、调度和按需缩放分别展开论述,从问题出发介绍和分析了研究现状.最后,针对现有存在问题,提出了一些拟解决方案,并对未来的研究方向进行了展望.     

算力网络研究进展综述

摘 要：随着新型网络业务和应用的不断发展与成熟,云计算、边缘计算、智能终端设备得到了快速发展,计算资源呈现出泛在部署的趋势,如何高效协同地利用这些泛在计算资源成为当前网络领域研究的一项重要新课题。在此背景下,算力网络（CFN,compute first networking）的概念被提出,并引起了广泛的关注,其基本思想是将算力和网络深度融合,协同分布式的计算资源,提升计算资源的利用率,同时改善用户的网络服务体验。首先分析了算力网络的提出背景和研究现状,然后介绍算力网络的基本架构、工作流程,以及算力网络的关键技术,最后对算力网络发展方向以及面临挑战进行分析。     

A virtual service placement approach based on improved quantum genetic algorithm

Despite the critical role that middleboxes play in introducing new network functionality, management and innovation of them are still severe challenges for network operators, since traditional middleboxes based on hardware lack service flexibility and scalability. Recently, though new networking technologies, such as network function virtualization (NFV) and software-defined networking (SDN), are considered as very promising drivers to design cost-efficient middlebox service architectures, how to guarantee transmission efficiency has drawn little attention under the condition of adding virtual service process for traffic. Therefore, we focus on the service deployment problem to reduce the transport delay in the network with a combination of NFV and SDN. First, a framework is designed for service placement decision, and an integer linear programming model is proposed to resolve the service placement and minimize the network transport delay. Then a heuristic solution is designed based on the improved quantum genetic algorithm. Experimental results show that our proposed method can calculate automatically the optimal placement schemes. Our scheme can achieve lower overall transport delay for a network compared with other schemes and reduce 30% of the average traffic transport delay compared with the random placement scheme.     

基于马尔可夫过程的5G网络功能信任预测机制

第五代移动通信网络(The 5th generation mobile network,5G)已成为全球新一轮科技革命和产业革命的重要驱动力量,服务功能日益完善,面临的安全挑战更加复杂多样。传统防御方法主要通过创建网络边界保护网络内部安全,所应用的网络形态较为单一。基于软件定义网络和虚拟化技术的5G网络愈加开放灵活,网络边界逐渐消失,需要新的安全理念。零信任理论适用于开放性网络的数据安全防护,5G核心网络是由网络功能组成的动态系统,网络功能通信行为可抽象为马尔可夫过程,网络功能信任模型是实现5G零信任安全的重要技术手段。针对此问题,本文提出了基于马尔可夫过程的5G网络功能信任预测机制(Markov Network Function Trust Prediction,MNFTP),此机制包含网络功能信任评估和信任预测。信任评估机制依据行为方式将网络功能分类为合法、伪装、非法,层次分析访问请求安全威胁性并得出信任评分,采用k-means++算法将信任评分归类为五种信任状态。信任预测机制基于马尔可夫过程构建网络功能访问请求信任状态链,结合时间因子和自适应奖惩因子计算马尔可夫状态转移矩阵,通过求解转移矩阵平稳分布得出预测信任状态。最后,网络功能基于预测信任状态抵御不可信的访问请求。实验表明,MNFTP机制相对于现有信任预测机制对伪装网络功能和非法网络功能有更好的抑制效果和信任状态分类能力。     

A Termination Detection Protocol for Use in Mobile Ad Hoc Networks

As devices become smaller and wireless networking technologies improve, the popularity of mobile computing continues to rise. In today's world, many consider devices such as cell phones, PDAs, and laptops as essential tools. As these and other devices become increasingly independent of the wired infrastructure, new kinds of applications that assume an ad hoc network infrastructure are being deployed. Their development forces software engineers to revisit well understood problems in a setting in which existing solutions are no longer working. This paper illustrates one such attempt by focusing on an important problem in distributed computing, termination detection in diffusing computations, in an ad hoc network environment. We formulate an algorithmic solution amenable to usage in mobile ad hoc networks. Along the way, we highlight several important software engineering concerns one must address and design strategies one might employ in a mobile setting.     

\upmu \mathrm{DC}^2: unified data collection for data centers

Modern data centers are playing an important role in a world full of information and communication technologies (ICTs). Many efforts have been paid to build a more efficient, cleaner data center for economic, social, and environmental benefits. This objective is being enabled by emerging technologies such as cloud computing and software-defined networking (SDN). However, a data center is inherently heterogeneous, consisting of servers, networking devices, cooling devices, power supply devices, etc., resulting in daunting challenges in its management and control. Previous approaches typically focus on only a single domain, for example, traditional cloud computing for server resource (e.g., computing resource and storage resource) management and SDN for network management. In a similar context of networking device heterogeneity, network function virtualization has been proposed to offer a standard abstract interface to manage all networking devices. In this research, we take the challenge of building a suit of unified middleware to monitor and control the three intrinsic subsystems in a data centre, including ICT, power, and cooling. Specifically, we present \(\upmu \mathrm{DC}^2\) , a unified scalable IP-based data collection system for data center management with elevated extensibility, as an initial step to offer a unified platform for data center operations. Our system consists of three main parts, i.e., data-source adapters for information collection over various subsystems in a data center, a unified message bus for data transferring, and a high-performance database for persistent data storage. We have conducted performance benchmark for the key building components, namely messaging server and database, confirming that our system is scalable for a data center with high device density and real-time management requirements. Key features, such as configuration files, dynamical module loading, and data compression, enhance our implementation with high extensibility and performance. The effectiveness of our proposed data collection system is verified by sample applications, such as, traffic flow migration for load balancing, VM migration for resource reservation, and server power management for hardware safety. This research lays out a foundation for a unified data centre management in future.     

网络存储的统一与虚拟化

存储资源共享是网络存储的最基本的任务，为了给用户提供有效的存储资源共享，网络存储的统一化和虚拟化采取了不同的方法：统一化的侧重点在于存储技术、存储资源的整合和存储管理的研究，虚拟化侧重于如何为用户提供更方便的应用环境。统一虚拟存储体系结构则结合了两者的优点，代表着网络存储的将采。本文对网络存储的统一化和虚拟化的现状和存在问题进行了探讨，分析了阻碍统一虚拟存储体系结构实现的不利因素，针对这些存在的问题，本文给出了一个基于自主式存储中介的网络存储系统，该系统结合了网络存储的统一化和存储虚拟化技术，可以看作统一的虚拟存储网络的一个实现。     

基于强化学习的边缘计算网络资源在线分配方法

针对边缘计算应用对实时性的要求,引入软件定义网络和网络功能虚拟化技术对边缘计算网络进行重构.基于此,考虑以最大化长期平均实时任务处理成功率为目标的计算和通信资源在线分配问题.通过建立马尔可夫决策过程模型,提出基于Q学习的资源在线分配方法.Q学习在状态动作空间较大时内存占用大且会发生维度灾难,鉴于此,进一步提出基于DQN的资源在线分配方法.实验结果表明,所提出算法能够较快收敛,且DQN算法相较于Q学习和其他基准方法能够获得更高的实时任务处理成功率.     

CloudSimSDN-NFV: Modeling and simulation of network function virtualization and service function chaining in edge computing environments

Software-defined networking (SDN) has evolved and brought an innovative paradigm shift in computer networks by utilizing a programmable software controller with open protocols. Network functions, previously served on dedicated hardware, have shifted to network function virtualization (NFV) that enabled functions to be virtualized and provisioned dynamically upon generic hardware. In addition to NFV, edge computing utilizes the edge resources close to end-users, which can reduce the end-to-end service delay and the network traffic volume. Although these innovative technologies gained significant attention from both academia and industry, there are limited tools and simulation frameworks for the effectiveness evaluation in a repeatable and controllable manner. Furthermore, large-scale experimental infrastructures are expensive to setup and difficult to maintain. Even if they are created, they are not available or accessible for the majority of researchers throughout the world. In this paper, we propose a framework for simulating NFV functionalities in both edge and cloud computing environments. In addition to the basic network functionalities supported by SDN in CloudSimSDN, we added new NFV features, such as virtualized network functions allocation, migration, and autoscaling with the support of corresponding network functionalities, such as flow load balancing, rerouting, and service function chaining (SFC) maintenance. We evaluated our simulation framework with autoscaling and placement policies for SFC in the integrated edge and cloud computing environments. The results demonstrate its effectiveness in measuring and evaluating the end-to-end delay, response time, resource utilization, network traffic, and power consumption with different algorithms in each scenario.     

基于无线局域网的移动计算网络解决方案

针对移动计算中的无缝连接问题 ,讨论了最受关注的无线网络技术和移动网络方案 ,针对一个具体应用实例 ,重点介绍了基于无线局域网 (WL AN)的解决方案     

Packet aggregation based network I/O virtualization for cloud computing

Virtualization is a key technology to enable cloud computing. Driver domain based model for network virtualization offers isolation and high levels of flexibility. However, it suffers from poor performance and lacks scalability. In this paper, we evaluate networking performance of virtual machines within Xen. The I/O channel transferring packets between the driver domain and the virtual machines is shown to be the bottleneck. To overcome this limitation, we proposed a packet aggregation based mechanism to transfer packets from the driver domain to the virtual machines. Packet aggregation, combined with an efficient core allocation, allows virtual machines throughput to scale up by 700%, while minimizing both memory and CPU consumption. Besides, aggregation impact on packets delay and jitter remains acceptable. Hence, the proposed I/O virtualization model satisfies infrastructure providers to offer Cloud computing services.     

多租户模式的业务平台云安全体系设计与实现

云计算技术目前已成为实现业务平台基础设施的可选方式之一。基于云计算技术,可以提供规模弹性、应用快速部署、资源按需分配与动念管理的业务平台云。但是在发展初期,云资源池主要以能力建设为主,对于安全体系的考虑尚不充分。通过对云资源池网络安全、应用安全及虚拟化安全等方面的分析和研究,给出了一种基于多租户模式的业务平台云安全体系,该方案已经广泛运用于中国电信业务平台云资源池,取得了显著的效果。     

边缘计算中任务卸载研究综述

近年来,随着移动智能设备的普及以及5G等无线通信技术的发展,边缘计算作为一种新兴的计算模式被提出,作为传统的云计算模式的扩展与补充。边缘计算的基本思想是将移动设备上产生的计算任务从卸载到云端转变为卸载到网络边缘端,从而满足实时在线游戏、增强现实等计算密集型应用对低延迟的要求。边缘计算中的计算任务卸载是一个关键的研究问题,即计算任务应在本地执行还是卸载到边缘节点或云端。不同的任务卸载方案对任务完成时延和移动设备能耗都有着较大的影响。文中首先介绍了边缘计算的基本概念,归纳了边缘计算的几种系统架构。随后,详细阐述了边缘计算中的计算任务卸载问题。基于对任务卸载方案研究的必要性与挑战的分析,对现有的相关研究工作进行了全面的综述和总结,并对未来的研究方向进行了展望。     

云计算主机内核虚拟化技术框架及其性能分析

近些年来,云计算已经成为了互联网领域的一个重要基础设施,越来越多的应用被部署到云计算平台上提供在线或者离线的服务.而虚拟化技术则是云计算的关键技术,提供包括计算、存储和网络在内的资源,一直是云计算技术研究领域的热点问题.从内核虚拟化技术-KVM出现,成为了目前主机虚拟化的主流技术之一.本文对KVM虚拟化技术的架构进行了详细地研究和分析.详细介绍了KVM架构以及环境的构建过程,对于KVM架构中包含的模块以及工作流程进行了详细深入的分析,并对KVM的性能进行测试,得到了有效的对比信息,可作为相关研究和工程技术的参考,具有较高的技术价值.     

面向5G/Beyond 5G的移动边缘缓存优化技术综述

随着移动设备和新兴移动应用的广泛使用,移动网络中流量的指数级增长所引发的网络拥塞、时延较大、用户体验质量差等问题无法满足移动用户的需求。边缘缓存技术通过对网络热点内容的复用,能极大缓解无线网络的传输压力;同时,该技术减少用户请求的网络时延,进而改善用户的网络体验,已经成为面向5G/Beyond 5G的移动边缘计算（MEC）中的关键性技术之一。围绕移动边缘缓存技术,首先介绍了移动边缘缓存的应用场景、主要特性、执行过程和评价指标;其次,对以低时延高能效、低时延高命中率及最大化收益为优化目标的边缘缓存策略进行了分析和对比,并总结出各自的关键研究点;然后,阐述了支持5G的MEC服务器的部署,并在此基础上分析了5G网络中的绿色移动感知缓存策略和5G异构蜂窝网络中的缓存策略;最后,从安全、移动感知缓存、基于强化学习的边缘缓存、基于联邦学习的边缘缓存以及Beyond 5G/6G网络的边缘缓存等几个方面讨论了边缘缓存策略的研究挑战和未来发展方向。     

A stochastic reward net-based assessment of reliability,availability and operational cost for a software-defined network infrastructure

The Journal of Supercomputing - The networking infrastructure of a software-defined network (SDN) requires further study to achieve continuity and high availability of data transactions for cloud...