SDN驱动的车载网络中异构数据传输的经济效益优化

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本文主要探讨了"软件定义的车载网络中具有成本效益的异构数据传输"这一主题。随着智能交通系统的发展，车辆网络被视为未来智慧城市的关键支撑技术。当前的车辆通信大多依赖单一网络架构，如IEEE 802.11p无线局域网和蜂窝网络，但这种单一的网络实例或跨网络的数据传输方式可能无法满足日益增长的车辆网络应用需求，特别是那些对性能、效率和安全性有高要求的应用。为了克服这一挑战，作者们引入了软件定义网络（SDN）的概念。SDN的核心理念是通过软件控制平面与硬件转发平面的分离，实现了网络资源的集中管理和灵活配置。在车载网络环境中，采用SDN可以实现异构网络资源的统一抽象管理，打破传统网络的界限，提高网络的灵活性和可扩展性。论文中提出的创新点在于，提出了一种基于SDN的无线通信解决方案，该方案旨在解决异构车载网络中的数据传输问题。它可能包括对不同类型的无线连接（如Wi-Fi、蓝牙、蜂窝网络等）进行协调和优化，以实现更高效的数据交换，同时降低整体网络部署和维护的成本。此外，SDN的优势还包括能够动态调整带宽分配、流量调度和安全策略，以适应不断变化的车辆动态环境和实时应用场景。为了实现这一目标，作者Zongjian He和Daqiang Zhang来自同济大学软件工程学院，他们可能讨论了如何设计和实现SDN控制器，以及如何与现有的车载硬件设备和协议栈无缝集成。同时，Junbin Liang来自广西大学计算机与电子信息学院的贡献可能涉及对无线链路性能分析和优化算法的研究，以确保在成本效益上达到最优。这篇研究论文深入探究了如何利用SDN技术提升车载网络的性能、降低成本，并有效支持异构数据传输，为未来的智能交通系统提供了关键的理论和技术支持。这将有助于推动车联网技术的进一步发展，为用户提供更加智能、安全、高效的出行体验。

Cost-efﬁcient Heterogeneous Data Transmission in

Software Deﬁned Vehicular Networks

Zongjian He, Daqiang Zhang

School of Software Engineering

Tongji University

Shanghai, China

E-mail: {hezongjian, dqzhang}@tongji.edu.cn

Junbin Liang

School of Computer and Electronic Information

Guangxi University

Nanning, Guangxi, China

E-mail: liangjb@gxu.edu.cn

Abstract—Vehicular networks have been regarded as the key

enabling technology of the future smart vehicles. Existing vehic-

ular communications mainly rely on a single network instance

or utilize data ofﬂoading over two networks (e.g., IEEE 802.11p

and cellular network). However, today’s vehicular network imple-

mentations are highly heterogeneous. Conventional homogeneous

communication and data ofﬂoading may not be able to satisfy the

requirement of the emerging vehicular networking applications.

In this research, we apply software deﬁned network (SDN)

to the heterogeneous vehicular networks to bridge the gap.

With SDN, heterogeneous network resources can be managed

with uniﬁed abstraction. Moreover, we propose an SDN-based

wireless communication solution, which can schedule different

network resources to minimize communication cost. The problem

is formulated as an optimization problem, and two different

solutions have been designed to adapt divergent application

scenarios. We evaluate the proposed approaches using trafﬁc

traces. The effectiveness and efﬁciency are validated by the

results.

Index Terms—Handoff, VANET, Software deﬁned network,

SDN, optimization

I. INTRODUCTION

With the advancement of information communication and

technology, more and more things in people’s daily lives are

becoming smart. Smart phones, smart TVs and smart watches

are growing rapidly and have signiﬁcantly changed people’s

life style. Besides, vehicles have been considered to be the next

impactful smart thing that can also potentially exert inﬂuence

on everyone [1]. To enable a smart vehicles, it is essential for

a vehicle to access Internet and communicate with ambient

neighbors through wireless communication. Thus, vehicular

networks are fundamentally important and have attracted much

attention from both industry and academy in recent years.

Vehicular network aims to connect vehicles to the cloud,

roadside units (RSU), and ambient vehicles using wireless

communications. Compared with smartphone based or smart

TV based networks, the smart vehicle based wireless networks

are more complicated and heterogeneous. Currently, many

vehicles have already be able to access Internet via cellular

networks like GPRS / EDGE / UMTS / LTE. Meanwhile,

IEEE has released standard 802.11p [2] for vehicular ad-

hoc network (VANET) that can establish vehicle-to-vehicle

(V2V) and vehicle-to-infrastructure (V2I) connections using

dedicated spectrum. In addition, other wireless technologies

like IEEE 802.11 ac/ad, ZigBee [3], Bluetooth [4], RFID

[5] and WiMAX [6], have also been applied as alternative

technologies for vehicular communication. What is more, it is

quite often for a vehicle to be equipped with multiple wireless

interfaces simultaneously (e.g., Cellular network and DSRC).

Communication over such a heterogeneous network poses

a number of challenges that need to be properly consid-

ered. First, the heterogeneity of these wireless technologies

makes the interconnection and interoperation an intractable

task, which leads to network fragmentation and inefﬁciency

of network resource utilization. Moreover, different wireless

technologies have different performance and communication

cost, and applications also have a variety of requirements for

network resources. Selecting one or more arbitrary network

interfaces for communication may not be able to satisfy

the requirement of application. Instead, the requirement and

network resources must be mapped carefully. In summary, two

problems are caused by the heterogeneity: 1) interoperability.

2) resource provisioning and utilization.

Researchers have already proposed many vehicular network-

ing applications, which range from safety related ones to

those aiming at improving driving efﬁciency. Most of these

applications only rely on a single type of wireless network.

For example, safety applications usually utilize IEEE 802.11p

for V2V communications, and infotainment applications often

access the Internet via cellular networks. In order to improve

the network performance and reduce the communication cost,

mobile data ofﬂoading [7] has been employed to vehicular

communication. In these scenarios, WLAN or other metro-

scale networks are generally used as a complementary network

to deliver data that originally leverage cellular networks [8]

[9]. Additionally, handoff among homogeneous network [10]

and heterogeneous network [11] [12] have also been proposed

to improve the network availability. These researches have

remarkably thrived the evolution of vehicular networks. How-

ever, imperfections remain for vehicular network to support

a wide range of real world applications. Foremost, statically

assigned data ofﬂoading and handoff are not ﬂexible enough,

especially when the vehicles are moving fast and the external

environment changes rapidly. Moreover, current approaches

are also lack of uniﬁed abstractions. Consequently, existing

approaches may not be able to fully leverage the underlying

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