SDN在车载网中的应用综述

随着车载应用、移动设备和物联网的快速发展,开发处理车载网大数据的高效架构已成为未来智慧城市关注的重要问题。然而,车载网复杂且不灵活的架构面临一系列挑战,如高移动性、间歇性连接、应用程序的异构性。在这种背景下,软件定义网络(Software Defined Network,SDN)可编程和灵活的网络架构,在有线网络管理和异构无线通信中受到学术界和工业界的广泛关注。在车载网中应用SDN可以提高灵活性、可靠性、可编程性和可扩展性,增强车载网提供应用和服务的能力,提高用户服务质量。文中首先描述了SDN的体系结构,然后从架构和数据传播角度出发概括了软件定义车载网络(Software Defined Vehicular Networks,SDVN)的研究进展,随后概述了结合移动边缘计算(Mobile Edge Computing,MEC)的SDVN研究现状,接着讨论了SDVN存在的问题和挑战,最后介绍了SDVN的应用前景。     

NCTUns tool for wireless vehicular communication network researches

Several goals such as improving road safety and increasing transport efficiency are being pursued in intelligent transportation systems (ITS). Wireless vehicular communication is one technology to achieve these goals. Conducting vehicular experiments on the roads is an approach to studying the effectiveness of wireless vehicular communication. However, such an approach is costly, hard-to-control (repeat), dangerous, and infeasible when many vehicles and people are involved in the field trial. In contrast, the simulation approach does not have these problems. It is a very useful approach and complements the field trial approach. This paper presents NCTUns, an open source integrated simulation platform, for wireless vehicular communication network researches. This tool tightly integrates network and traffic simulations and provides a fast feedback loop between them. Therefore, a simulated vehicle can quickly change its driving behavior such as moving speed and direction when it receives a message from the wireless vehicular communication network. This capability is required by several novel ITS applications such as active collision avoidance systems. In this paper, we present the design, implementation, validation, and performance of this tool.     

软件定义车联网中缓存辅助的NOMA功率分配方案研究

由于对丰富多媒体服务的需求日益增长,车联网需要提供海量的设备连接以满足高频谱效率和低延迟的需求。软件定义网络（SDN）、缓存和非正交多址接入（NOMA）被认为是有效解决这些关键挑战的潜在技术。针对软件定义车联网,提出了一种缓存辅助的NOMA功率分配方案。首先,针对车联网中车辆总是处于高速运动状态的特点,提出了一种新的簇头选择算法,到达的道路交通将借助SDN进行预测,实现自适应车辆分簇。其次,引入了缓存辅助的NOMA方案,每个车辆在文件缓存阶段使用NOMA原理缓存和请求文件。再次,针对双Nakagami-m衰落条件下的两个簇头车辆通信场景,提出了一种最优功率分配策略,将优化问题公式化为找到每辆车的最佳功率曲线,从而最大化地在每辆车上成功解码目标文件的概率。最后,数值仿真和理论分析表明,所提缓存辅助NOMA功率分配方案,性能明显优于传统的NOMA和缓存辅助的OMA。     

Edge-centric trust management in vehicular networks

A major objective of vehicular networking is to improve road safety and reduce traffic congestion. The experience of individual vehicles on traffic conditions and travel situations can be shared with other vehicles for improving their route planning and driving decisions. Nevertheless, the frequent occurrence of adversary vehicles in the network may affect the overall network performance and safety. These vehicles may behave intelligently to avoid detection. To effectively control and monitor such security threats, an efficient Trust Management system should be employed to identify the trustworthiness of individual vehicles and detect malicious drivers which is the major focus of this work. We propose a hybrid solution, which integrates Edge Computing and Multi-agent modeling in a Trust Management system for vehicular networks. The proposed solution also aims to overcome the limitations of the two commonly utilized approaches in this context: cloud computing and Peer-to-Peer (P2P) networking. Our framework has a set of features that make it an efficient platform to address the major security challenges in vehicular networks including latency, scalability, uncertainty, data accessibility, and malicious behavior detection. Performance of the approach is evaluated by simulating a realistic environment. Experimental results show that the proposed approach outperforms similar approaches from literature for various performance indicators.     

车载自组织网络中基于停车骨干网络的数据传输

车载自组织网络(vehicular ad hoc networks,简称VANETs)具有网络间歇连通、节点高速移动及动态的网络拓扑结构等特性,如何有效地实现车辆间的数据传输,成为VANETs的重大挑战.现有研究工作基于历史交通流量或历史延迟预测路段当前交通状况的方法并不可靠.此外,要实现高效的数据路由传输,配置大量路边基础设施节点(deploying roadside unit,简称RSU)是一种可行方案,但通常需要额外开销.基于城市区域长时间拥有大量地上停放车辆这一事实,提出了基于停车骨干网络的数据传输策略PBBD(parking backbone based data delivery),不需要配置任何地面基础设施,而是把地面的停放车辆组成一个虚拟的停车覆盖网络,通过该停车覆盖网实现数据的传输.为此,首先,对于每一条道路,把路边和非路边停放车辆组成一个尽可能长的停车簇,并基于这些停车簇组织城市停车骨干网络.其次,设计基于停车覆盖网络的全新数据传输算法来实现车辆间的有效数据传输.基于真实城市地图和交通数据的模拟实验结果表明,与现有的几种数据传输算法相比,PBBD能够以较低的网络传输开销和较小的传输延迟获得较高的数据传输成功率.     

Exploiting blockchain for dependable services in zero-trust vehicular networks

The sixth-generation (6G) wireless communication system is envisioned be cable of providing highly dependable services by integrating with native reliable and trustworthy functionalities. Zero-trust vehicular networks is one of the typical scenarios for 6G dependable services. Under the technical framework of vehicle-and-roadside collaboration, more and more on-board devices and roadside infrastructures will communicate for information exchange. The reliability and security of the vehicle-and-roadside collaboration will directly affect the transportation safety. Considering a zero-trust vehicular environment, to prevent malicious vehicles from uploading false or invalid information, we propose a malicious vehicle identity disclosure approach based on the Shamir secret sharing scheme. Meanwhile, a two-layer consortium blockchain architecture and smart contracts are designed to protect the identity and privacy of benign vehicles as well as the security of their private data. After that, in order to improve the efficiency of vehicle identity disclosure, we present an inspection policy based on zero-sum game theory and a roadside unit incentive mechanism jointly using contract theory and subjective logic model. We verify the performance of the entire zero-trust solution through extensive simulation experiments. On the premise of protecting the vehicle privacy, our solution is demonstrated to significantly improve the reliability and security of 6G vehicular networks.     

COVE: Co-operative Virtual Network Embedding for Network Virtualization

Network virtualization provides a promising solution for next-generation network management by allowing multiple isolated and heterogeneous virtual networks to coexist and run on a shared substrate network. A long-standing challenge in network virtualization is how to effectively and efficiently map these virtual nodes and links of heterogeneous virtual networks onto specific nodes and links of the shared substrate network, known as the Virtual Network Embedding (VNE) problem. Existing centralized VNE algorithms and distributed VNE algorithms both have advantages and disadvantages. In this paper, a novel cooperative VNE algorithm is proposed to coordinate centralized and distributed algorithms and unite their respective advantages and specialties. By leveraging the learning technology and topology decomposition, autonomous substrate nodes entrusted with detailed mapping solutions cooperate closely with the central controller with a global view and in charge of general management to achieve a successful embedding process. Besides a topology-aware resource evaluation mechanism and customized mapping management policies, Bloom filter is elaborately introduced to synchronize the mapping information within the substrate network, instead of flooding which generates massive communication overhead. Extensive simulations demonstrate that the proposed cooperative algorithm has acceptable and even better performance in terms of long-term average revenue and acceptance ratio than previous algorithms.     

Routing using reinforcement learning in vehicular ad hoc networks

In vehicular ad hoc networks (VANETs), the frequent change in vehicle mobility creates dynamic changes in communication link and topology of the network. Hence, the key challenge is to address and resolve longer transmission delays and reduced transmission stability. During the establishment of routing path, the focus of entire research is on traffic detection and road selection with high traffic density for increased packet transmission. This reduces the transmission delays and avoids carry-and-forward scenarios; however, these techniques fail in obtaining accurate traffic density in real-time scenario due to rapid change in traffic density. Thus, it is necessary to create a model that efficiently monitors the traffic density and assist VANETs in route selection in an automated way with increased accuracy. In this article, a novel machine learning architecture using deep reinforcement learning (DRL) model is proposed to monitor and estimate the data essential for the routing protocol. In this model, the roadside unit maintains the traffic information on roads using DRL. The DRL predicts the movement of the vehicle and makes a suitable routing path for transmitting the packets with improved transmission capacity. It further uses predicted transmission delays and the destination location to choose the forwarding directions between two road safety units (RSUs). The application of DRL over VANETs yields increased network performance, which provides on-demand routing information. The simulation results show that the DRL-based routing is effective in routing the data packets between the source and destination vehicles than other existing method.     

车载自组织网络中节点合作行为的博弈研究

在车载自组织网络中使用公共品博弈理论促进节点合作的研究表明车辆密集区域的节点会呈现不合作状态.本文通过模拟实验得知当节点平均度数较低时,节点更容易产生合作行为.为了提高车辆密集区域中合作节点的比例,本文提出了博弈度数与博弈拓扑的概念,并在此基础上构建了一种能够更改网络博弈拓扑,降低节点博弈度数的分组博弈理论模型.实验结果表明,在车辆密集区域使用该博弈模型能够显著提高网络中合作节点的比例.     

Enhancing the performance of futurewireless networks with software-defined networking

To provide ubiquitous Internet access under the explosive increase of applications and data traffic, the current network architecture has become highly heterogeneous and complex, making network management a challenging task. To this end, software-defined networking (SDN) has been proposed as a promising solution. In the SDN architecture, the control plane and the data plane are decoupled, and the network infrastructures are abstracted and managed by a centralized controller. With SDN, efficient and flexible network control can be achieved, which potentially enhances network performance. To harvest the benefits of SDN in wireless networks, the software-defined wireless network (SDWN) architecture has been recently considered. In this paper, we first analyze the applications of SDN to different types of wireless networks. We then discuss several important technical aspects of performance enhancement in SDN-based wireless networks. Finally, we present possible future research directions of SDWN.     

Location-Based IPv6 Address Configuration for Vehicular Networks

Due to long latency and considerable packet loss, stateful and stateless address configuration standards cannot efficiently work in vehicular networks, so this paper proposes an IPv6 address configuration scheme for vehicular networks based on location information. This scheme combines a stateless address configuration mechanism with a stateful one. In the stateless algorithm, duplicate address detection is performed within a road domain instead of a network. A random ID is introduced to reduce the address conflict rate, so the address configuration cost and delay are reduced. In the stateful algorithm, a vehicle acquires a unique address from a neighbor vehicle without recording the address allocation states, so the address configuration task is distributed around all vehicles and the distributed address configuration is achieved. This paper evaluates the performance of this scheme, and the data results show that this scheme reduces the addressing costs and delays.     

基于VxLAN和SDN 的电子政务云

电子政务云属于大规模私有云,其整体架构可采用软件定义数据中心（SDDC）架构。围绕软件定义网络的问 题,本文介绍了电子政务云的主要特征以及对于网络提出的挑战,提出基于VxLAN和SDN的网络解决思路;针对电子政务云 的特点,提出了网络Overlay 的具体组网方案,并对其优点进行了总结;最后,本文提出了SDN控制器与异构云管理平台的对 接方案,并以Openstack为例,描述了SDN控制器与云管理平台的配置流程。     

Semi‐decentralized nonlinear cooperative control strategies for a network of heterogeneous autonomous underwater vehicles

In this paper, we develop nonlinear distributed or semi‐decentralized cooperative control schemes for a team of heterogeneous autonomous underwater vehicles (AUVs). The objective is to have the network of AUVs follow a desired trajectory, while the agents maintain a desired formation when there is a virtual leader whose position information is only available and known to a very small subset of the agents. The virtual leader does not receive any feedback and information from the other agents and the agents only communicate with their nearest neighboring agents. It is assumed that the model parameters associated with each vehicle/agent is different, although the order of the agents is the same. The developed and proposed nonlinear distributed cooperative control schemes are based on the dynamic surface control methodology for a network of heterogeneous autonomous vehicles with uncertainties. The development and investigation of the dynamic surface control methodology for a team of cooperative heterogenous multi‐agent nonlinear systems is accomplished for the first time in the literature. Simulation results corresponding to a team of six AUVs are provided to demonstrate and illustrate the advantages and superiority of our proposed cooperative control strategies as compared to the methods that are available in the literature. Copyright © 2016 John Wiley & Sons, Ltd.     

一种支持细粒度并行的SDN虚拟化编程框架

软件定义网络(software defined network,简称SDN)通过集中式的控制器提高了网络的可编程性,成为近年来网络领域非常热门的话题。以Openflow网络为代表的软件定义网络将逻辑控制与数据转发相隔离,为网络虚拟化技术提供了良好的平台。集中式的抽象与控制使得SDN虚拟化框架的处理效率成为主要瓶颈。现有的SDN虚拟化框架由于缺乏对细粒度并行的支持,为编程人员充分利用多核/众核资源、控制更大规模的网络带来了极大的挑战。为了提高SDN虚拟化框架的处理效率,提出一种新的SDN虚拟化编程框架,通过新颖的API和运行时,在框架内部支持细粒度的并行处理。该框架通过对网络中流和网络资源进行抽象,使开发人员可以直接通过划分流空间来定义不同的虚拟网络,利用无锁的编程方式对共享的网络资源和流进行操作。实验结果表明,该框架在逻辑控制的执行效率方面具有良好的可扩展性,可以创建出更大规模的虚拟网络,并对其进行更为复杂的控制。     

A Scalable Privacy Preserving Scheme in Vehicular Network

Vehicles enlisted with computing, sensing and communicating devices can create vehicular networks, a subset of cooperative systems in heterogeneous environments, aiming at improving safety and entertainment in traffic. In vehicular networks, a vehicle＇s identity is associated to its owner＇s identity as a unique linkage. Therefore, it is of importance to protect privacy of vehicles from being possibly tracked. Obviously, the privacy protection must be scalable because of the high mobility and large population of vehicles. In this work, we take a non-trivial step towards protecting privacy of vehicles. As privacy draws public concerns, we firstly present privacy implications of operational challenges from the public policy perspective. Additionally, we envision vehicular networks as geographically partitioned subnetworks （cells）. Each subnetwork maintains a list of pseudonyms. Each pseudonym includes the cell＇s geographic id and a random number as host id. Before starting communication, vehicles need to request a pseudonym on demand from pseudonym server. In order to improve utilization of pseudonyms, we address a stochastic model with time-varying arrival and departure rates. Our main contribution includes： 1） proposing a scalable and effective algorithm to protect privacy; 2） providing analytical results of probability, variance and expected number of requests on pseudonym servers. The empirical results confirm the accuracy of our analytical predictions.     

ViMediaNet: an emulation system for interactive multimedia based telepresence services

The telepresence service (TPS) leverages advanced communication, virtual reality, and cooperative web technologies to provide remote engaged users an immersive experience of being fully present, which are widely used in teleconferencing, remote surgery, and hazardous environment exploration. The common feature of TPS-based applications lies in that the users’ experiences heavily depend on the quality of interactive multimedia services, that is, most deliveries of multimedia contents are mission-critical, as well as time-critical, to ensure the control and operation accuracy for telerobots. Therefore, the delivery performance of multimedia contents over heterogeneous networks becomes the primary concern in the TPS system design, especially for those delay sensitive applications, like remote surgery and environment exploration. In this paper, we incorporate video processing tools with the network simulator to design and implement a joint emulation system, named as the virtual media network (ViMediaNet), through which, the TPS designer can readily deploy the TPS system over a heterogeneous network virtualized by the network emulator, investigate the critical network performance metrics in the multimedia content delivery, such as transmission delay and packet jitter, and observe control results in real time. To verify the capability of ViMediaNet in emulating the real-setting TPS system, we take a mobile device based vision navigation system as an example to evaluate performance impacts of the rate adaptation technology in the telerobot control. The experimental results reveal that the adaptive video streaming is a promising solution to significantly enhance the control accuracy of telerobots in TPS systems.     

An intelligent infotainment dissemination scheme for heterogeneous vehicular networks

In a vehicular network, applications are expected to be aware of network conditions and be adaptable to the varying environment in order to achieve the acceptable and predictable performance. Moreover, the establishment of vehicle infotainment system in a heterogeneous vehicular network needs to pay special attention to the distinctive network characteristic in wired/wireless networks, such as dynamic topology and less available bandwidth, and the exploitation of the underutilized peers’ resources to support large-scale services. This work thus proposes a service-oriented information dissemination scheme for vehicle infotainment system to ensure the possibility of heterogeneous vehicular communication and a framework for delivering real-time services over an IP-based network is provided to assure interoperability, roaming, and end-to-end session management. The main focus of this work is to implement an adaptive vehicle infotainment system, in which cache relay nodes ((Xiao, Zhuang, & Liu, 2005)) can be intelligently determined. Fuzzy logic inference system is employed to determine appropriate cache relay nodes to cache infotainment data streams and distribute them to different peers through service-oriented architecture. The experimental results demonstrate that effectiveness and practicability of the proposed work.     

5G MEC-enabled vehicle discovery service for streaming-based CAM applications

Cooperative perception represents an important technology to fulfil the higher automation levels of connected and automated mobility (CAM). In cooperative perception, the sensor data, either raw or processed, is shared among neighbour vehicles with the objective of enhancing or complementing the perception obtained by on-board sensors. The vehicle that requests this external perception data needs to have this data quickly. However, it first needs to discover the network address of the neighbour vehicle that wants to connect to. Specially in a dense urban area or in a congested radio channel, an inefficient method for neighbour vehicle discovery could prevent a timely start of the cooperative perception session. This paper describes a novel 5G multi-access edge computing (MEC) solution that that boosts the selection of interesting neighbour vehicles according to a geographical region of interest (ROI) after applying pertinent adjustments considering vehicles’ dynamics and network communication latencies. In contrast to broadcast-based methods, in the proposed method the vehicles are only sending their periodical position data to a MEC service, which centralises the vehicle discovery requests. The objective of this Vehicle Discovery Service (VDS) is to support the startup of Web Real-Time Communications (WebRTC)-based Extended Sensors CAM applications. The proposed VDS has been validated using a public vehicular traffic dataset evaluating geo-position accuracy. The WebRTC-based streaming pipeline has been validated testing its feasibility for a See-Through video streaming application.

     

Multi-layer Virtual Transport Network Design

Service overlay networks and network virtualization enable multiple overlay/virtual networks to run over a common physical network infrastructure. They are widely used to overcome deficiencies of the Internet (e.g., resiliency, security and QoS guarantees). However, most overlay/virtual networks are used for routing/tunneling purposes, and not for providing scoped transport flows (involving all mechanisms such as error and flow control, resource allocation, etc.), which can allow better network resource allocation and utilization. Most importantly, the design of overlay/virtual networks is mostly single-layered, and lacks dynamic scope management, which is important for application and network management. In response to these limitations, we propose a multi-layer approach to virtual transport network (VTN) design. This design is a key part of VTN-based network management, where network management is done via managing various VTNs over different scopes (i.e., ranges of operation). We explain the details of the multi-layer VTN design problem as well as our design algorithms, and focus on leveraging the VTN structure to partition the network into smaller scopes for better network performance. Our simulation and experimental results show that our multi-layer approach to VTN design can achieve better performance compared to the traditional single-layer design used for overlay/virtual networks.