CR-SDVN: A Cognitive Routing Protocol for Software-Defined Vehicular Networks

Ghafoor, Huma; Koo, Insoo

doi:10.1109/jsen.2017.2788014

Cited by 71 publications

(41 citation statements)

References 37 publications

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“…For simplicity, we used the fog cloud as a central controller for the proposed scheme, which provides service according to the users' demands by communicating with the corresponding VNF. Likewise, in our previous work [16], we simulated HSDV with a spectrum-sensing scheme for vehicular networks proposed by Abbassi et al [25] to make it cognitive HSDV, and referred to it as the reference scheme for V2V. Similarly, for cognitive maritime networks, we simulated HSDV with the spectrum selection scheme proposed by Tang et al [26] and named it as the reference scheme for S2S.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…where β is a weight factor, and as in our previous work [16], transmission delay, TD, is defined as:…”

Section: Integrated Cognitive Hybrid Communications For a Coastal Citymentioning

confidence: 99%

“…As in our previous works [16,17], we performed spectrum sensing in this integrated cognitive architecture to detect the presence of PU when vehicles are moving on roads and ships are moving either near the shore or in deep sea. The subsection describes in detail the way in which vehicles and ships find the idle spectrum by sensing the environment, and how they combine their individual sensing results with each other and with their corresponding LC.…”

Section: Belief Propagation-based Channel Selection Algorithmmentioning

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%

“…where β is a weight factor, and as in our previous work [16], transmission delay, TD, is defined as:…”

Section: Integrated Cognitive Hybrid Communications For a Coastal Citymentioning

confidence: 99%

Section: Belief Propagation-based Channel Selection Algorithmmentioning

confidence: 99%

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An Integrated Cognitive Radio Network for Coastal Smart Cities

Ghafoor

Koo

2019

Applied Sciences

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“…All prediction-based routing schemes [4] additional messages including status beacons, inner cluster messages, routing queries and replies and so on there are in SDVN. In particular, the application of trajectory prediction can reduce the number of status beacons while more routing queries can be generated locally in hybrid routing schemes [3] [5] [11] [14]. Scalability: This is defined by whether a routing scheme is scalable to the number of nodes in the network.…”

Section: Comparisonsmentioning

confidence: 99%

“…Quality of Route: This refers to whether or not the data message follows an optimal route with low latency and high delivery ratio. Central routing schemes [7] [8] [14] provide highly efficient routes if they consider the realtime status of the vehicles in the computation of routes. Most hybrid routing schemes could not provide high quality routes, but not for the case of vehicular neighbor group (VNG) [11].…”

Section: Comparisonsmentioning

confidence: 99%

Routing Schemes in Software-Defined Vehicular Networks: Design, Open Issues and Challenges

Zhao

Al‐Dubai

et al. 2021

IEEE Intell. Transport. Syst. Mag.

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Software-defined vehicular networks (SDVN) is a promising technology to overcome the limitations of current vehicular networking. However, existing vehicular routing schemes are not equipped to handle communication in SDVNs. In addition, routing schemes in SDVNs, in general, has been lightly addressed in the literature. To fill this gap, this article explores the potential of SDVNs from the aspect of routing and studies the design principles of routing schemes in SDVNs and classifies the current routing solutions based on different criteria. SDVN routing schemes are then compared through comprehensive analysis, and key open issues and opportunities for future research directions are discussed.

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Radio Resource Management in Internet‐of‐Vehicles

2021

Spectrum Sharing in Cognitive Radio Networks

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CR-SDVN: A Cognitive Routing Protocol for Software-Defined Vehicular Networks

Cited by 71 publications

References 37 publications

An Integrated Cognitive Radio Network for Coastal Smart Cities

An Integrated Cognitive Radio Network for Coastal Smart Cities

Routing Schemes in Software-Defined Vehicular Networks: Design, Open Issues and Challenges

Radio Resource Management in Internet‐of‐Vehicles

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