An Architecture for Hierarchical Software-Defined Vehicular Networks

Correia, Sergio; Boukerche, Azzedine; Meneguette, Rodolfo I.

doi:10.1109/mcom.2017.1601105

Cited by 114 publications

(57 citation statements)

References 14 publications

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“…As mentioned above in Section 1, the literature has no publicly recognized integrated coastal city combining cognitive vehicular and maritime communications to provide a routing service for different users' demands. Therefore, we first evaluated our proposed scheme for V2V, S2S, and V2S communications in the integrated framework, one by one, and then chose to compare the V2V and S2S communications of our proposed scheme with the hierarchical software-defined VANET (HSDV) [24] routing protocol. To evaluate the impact of our proposed integrated scheme in the respective environments, we only compared V2V and S2S with their respective reference schemes.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

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An Integrated Cognitive Radio Network for Coastal Smart Cities

Ghafoor

Koo

2019

Applied Sciences

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The integration of different networks has attracted significant attention in academia. Both terrestrial and maritime communications systems have been attracting keen interest for ways to deal with various applications. As the environment of cognitive vehicular and maritime networks is extremely dynamic, these networks suffer with a long delay because of intermittent links while providing services for different applications. To this end, here we introduce the integration of cognitive vehicular and maritime networks to design a coastal smart city by utilizing software-defined networking, network function virtualization, and fog computing under the same infrastructure. This novel integrated cognitive coastal city fulfills the demand of each application user in a hybrid environment with a quicker response time. The idea is to combine vehicular and maritime communications to meet different user demands. Different virtual networks are launched by network function virtualization, and are managed and controlled by a software-defined networking controller. From the integration of software-defined networking, network function virtualization, and fog computing, both vehicular and marine users are provided with stable paths to meet each application's demands. Appl. Sci. 2019, 9, 3557 2 of 16 spectrums for automobile and maritime communication systems have been found to be insufficient due to an inevitable increase in the number of both vehicular and marine users and the demands of each of these applications [3,4]. The cognitive radio seems to be a corrective approach to overcome spectrum shortage issues in different networks. Consequently, to maintain stable networking and meet the increasing demands of mobile data traffic, network engineers are required to provide an effective solution to improve users' experiences. This means that citizens need an all-in-one framework to meet their growing needs in a more effective and efficient way.To cope with the inevitable increase in data traffic, integration of SDN and NFV seems to be a viable solution to launching and managing virtual networks (VNs) on demand and at greater speed, respectively. NFV is basically a transition from proprietary hardware-based solutions to multi-vendor open solutions. NFV is like a soft appliance that can be installed on demand, whereas SDN is smart plumbing that can be changed on command. The integration reduces provisioning time from months to minutes, reduces costs, improves service-request response times, reacts faster to changing services (allowing right-sized deployments to customers), and offers competitive services. Due to this integration, the changing needs of virtual network functions (VNFs) are now automatically followed by network configurations, and an authorized person is able to track the owner of a service and the reasons why these certain configurations are required. A VNF is the virtualization of a certain NF that should operate independently. NFs are actually services that are deployed by NFV. SDN is a critical component in the maj...

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Section: Simulation Results and Discussionmentioning

confidence: 99%

“…Reference scheme for S2S [24]+ [26] when P(H 0 ) = 0.7 (c) Figure 8. Performance comparison between the proposed S2S and the reference scheme for S2S in terms of (a) packet delivery ratio, (b) end-to-end delay, and (c) routing overhead ratio.…”

Section: Routing Overhead Ratiomentioning

confidence: 99%

An Integrated Cognitive Radio Network for Coastal Smart Cities

Ghafoor

Koo

2019

Applied Sciences

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“…The scientific community asserts that a multi-RAT (Radio Access Technologies) architecture, combining various access technologies (mainly DSRC and LTE/5G) will be considered to provide the network communication services that meet ITS services' requirements [1,19]. To this end, an SDN based architecture, combining the two complementary technologies, is proposed in the literature [12,17]. This enables the management of these networks through a unified model (e.g., OpenFlow-like protocol), also allows optimizing network resources utilization, thanks to the programmability and global vision provided by SDN.…”

Section: Introductionmentioning

confidence: 99%

“…The density and high mobility of vehicles make the design of this service a challenging task. Secondly, the connectivity between the vehicles and their controller is partly wireless [12]. In fact, vehicles can go through areas without network coverage, this could make the controller temporarily unreachable, which may impact network performance.…”

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confidence: 99%

Towards Dynamic Controller Placement in Software Defined Vehicular Networks

Toufga

Abdellatif

Assouane

et al. 2020

Sensors

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The emerging SDVN (Software Defined Vehicular Network) paradigm promises to bring flexibility and efficient resource utilization to vehicular networks, enabling the emergence of novel Intelligent Transportation Services. However, as it was initially designed with wired network in mind, applying the SDN paradigm to a vehicular context faces new challenges related to the peculiar characteristics of this network (high node mobility and node density, and the presence of wireless links). In this paper, we focus on one of the critical architectural elements of SDVN, namely, the SDN Controller Placement, and promote the use of dynamic placement methods that take into account the dynamicity of vehicular networks' topology. We also describe the different approaches towards a dynamic controller placement and also propose an ILP (Integer Linear Programming) based dynamic placement method that adaptively readjusts the number and placement of controllers according to road traffic fluctuations. The proposed method is evaluated using a realistic traffic trace from Luxembourg City. Simulation results show that our approach outperforms the static approach as proposed in the literature.Most existing research work have been elaborated on the opportunities that the SDVN concept could bring when applied to vehicular networks [10]. However, some challenges need to be addressed to reach these expected opportunities. Among these challenges, we mention firstly, the network topology discovery, which is a crucial service in the Software Defined Vehicular Netowrk (SDVN) system [11]. Its main goal is to build and maintain an up-to-date view of the underlying network. The density and high mobility of vehicles make the design of this service a challenging task. Secondly, the connectivity between the vehicles and their controller is partly wireless [12]. In fact, vehicles can go through areas without network coverage, this could make the controller temporarily unreachable, which may impact network performance. Thirdly, the mobility of vehicles can result in frequent changes of their attached SDN controller. This impacts the established sessions with the initial controller, as well as an increase of network overhead due to inter-controller vehicles information exchange. The SDN controller placement is a key architectural element that can help mitigating the above mentioned challenges. It consists of computing the number of SDN controllers to deploy and derive their placement in the network. This choice must be done appropriately given the critical role of an SDN controller in this architecture. First, wireless link connectivity and quality must be considered in order to minimize the connectivity losses between vehicles and their controllers. Second, the SDN Controller coverage should be defined carefully taking into account the density and mobility of vehicles. This helps avoiding SDN controllers' overload as well as improving the performance of vehicle-to-controller communications, and also, minimizing the number of changes in the set of deploy...

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“…In the last few years, integrating the emerging paradigm of software‐defined networking (SDN) in vehicular networks has gained considerable attention. Indeed, several works have shown that by physically separating the control plane features from that of the data plane and by enabling a logically centralized system control, SDN can facilitate the network management, exploit the vehicular resources more efficiently, and bring new services. Recently, the exponential increase in the number of connected vehicles and the growing explosive demand of infotainment bandwidth‐intensive application (eg, video‐on‐demand, video streaming, etc) are provoked an avalanche augmentation of vehicular mobile data traffic.…”

Section: Introductionmentioning

confidence: 99%

Incentive edge caching in software‐defined internet of vehicles: A Stackelberg game approach

Alioua

Senouci

Sedjelmaci

et al. 2018

Int J Communication

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In this paper, we investigate an incentive edge caching mechanism for an internet of vehicles (IoV) system based on the paradigm of software-defined networking (SDN). We start by proposing a distributed SDN-based IoV architecture. Then, based on this architecture, we focus on the economic side of caching by considering competitive cache-enablers market composed of one content provider (CP) and multiple mobile network operators (MNOs). Each MNO manages a set of cache-enabled small base stations (SBS). The CP incites the MNOs to store its popular contents in cache-enabled SBSs with highest access probability to enhance the satisfaction of its users. By leasing their cache-enabled SBSs, the MNOs aim to make more monetary profit. We formulate the interaction between the CP and the MNOs, using a Stackelberg game, where the CP acts first as the leader by announcing the popular content quantity that it which to cache and fixing the caching popularity threshold, a minimum access probability under it a content cannot be cached. Then, MNOs act subsequently as followers responding by the content quantity they accept to cache and the corresponding caching price. A noncooperative subgame is formulated to model the competition between the followers on the CP's limited content quantity.We analyze the leader and the follower's optimization problems, and we prove the Stackelberg equilibrium (SE). Simulation results show that our game-based incentive caching model achieves optimal utilities and outperforms other incentive caching mechanisms with monopoly cache-enablers whilst enhancing 30% of the user's satisfaction and reducing the caching cost. KEYWORDS incentive edge caching, internet of vehicle, software-defined networking, Stackelberg game INTRODUCTIONIn the last few years, Internet of Vehicles (IoV) has emerged as a promising technology for improving next-generation vehicular networks by advanced cloud/edge computing technologies. This rapid emergence has principally boosted by the vigorous development of wireless communication technologies, the explosive usage of in-vehicle mobile internet, and the appearance of the smart city concept. Internet of Vehicles is the instantiation of Internet of things (IoT) paradigm in vehicular scenarios to enable more intelligent and more connected vehicle with new IP-based applications. 1,2 Int J Commun Syst. 2019;32:e3787.wileyonlinelibrary.com/journal/dac

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An Architecture for Hierarchical Software-Defined Vehicular Networks

Cited by 114 publications

References 14 publications

An Integrated Cognitive Radio Network for Coastal Smart Cities

An Integrated Cognitive Radio Network for Coastal Smart Cities

Towards Dynamic Controller Placement in Software Defined Vehicular Networks

Incentive edge caching in software‐defined internet of vehicles: A Stackelberg game approach

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