Coding-Assisted Broadcast Scheduling via Memetic Computing in SDN-Based Vehicular Networks

Li, Kai; Feng, Liang; Dai, Penglin; Lee, Victor C. S.; Son, Sang H.; Cao, Jiannong

doi:10.1109/tits.2017.2748381

Cited by 46 publications

(21 citation statements)

References 30 publications

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“…In [26], a solution to improve communication performance in dynamic vehicular networking environments using an SDN-based Medium Access Control (MAC) protocol is proposed. Moreover, another approach [27] that addressed the problem of enhancing the available bandwidth usage in an SDN-based service architecture for IoV by combining vehicular caching and network coding has been proposed.…”

Section: State-of-the-artmentioning

confidence: 99%

ARTNet: Ai-Based Resource Allocation and Task Offloading in a Reconfigurable Internet of Vehicular Networks

Akbar

Jan

et al. 2022

IEEE Trans. Netw. Sci. Eng.

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The convergence of Software-Defined Networking (SDN) and Internet of Vehicular (IoV) integrated with Fog Computing (FC), known as Software Defined Vehicular based FC (SDV-F), has recently been established to take advantage of both paradigms and efficiently control the wireless networks. SDV-F tackles numerous problems, such as scalability, load-balancing, energy consumption, and security. It lags, however, in providing a promising approach to enable ultra-reliable and delay-sensitive applications with high vehicle mobility over SDV-F. We propose ARTNet, an AI-based Vehicle-to-Everything (V2X) framework for resource distribution and optimized communication using the SDV-F architecture. ARTNet offers ultra-reliable and low-latency communications, particularly in highly dynamic environments, which is still a challenge in IoV. ARTNet is composed of intelligent agents/controllers, to make decisions intelligently about (i) maximizing resource utilization at the fog layer, and (ii) minimizing the average end-to-end delay of time-critical IoV applications. Moreover, ARTNet is designed to assign a task to fog nodes based on their states. Our experimental results show that considering a dynamic IoV environment, ARTNet can efficiently distribute the fog layer tasks while minimizing the delay.

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Section: State-of-the-artmentioning

confidence: 99%

ARTNet: Ai-Based Resource Allocation and Task Offloading in a Reconfigurable Internet of Vehicular Networks

Akbar

Jan

et al. 2022

IEEE Trans. Netw. Sci. Eng.

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“…However, previously proposed security solutions to vehicular networks have lack of trust management, fair information assessment, combined with SDN infrastructure. Existing researches provide security solutions on cooperative data dissemination [20] and coding assisted broadcast scheduling [21] in heterogeneous SDN-based vehicular networks, irrespective of what information should be delivered to which vehicle and how to incorporate trust management. Further, Arshad et al [22] proposed Beacon trust management system and fake data detection, collision avoidance [23], peer-to-peer vehicular network communication [24], and uncertainty detection using radio frequency identification [25].…”

Section: Related Workmentioning

confidence: 99%

Efficient data handover and intelligent information assessment in software‐defined vehicular social networks

Sohail

Wang

Ali

et al. 2019

IET Intelligent Transport Systems

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“…Central to this vision is a scalable and intelligent vehicular network which is responsible for efficient information exchange among vehicles and/or between vehicles, other road users and road side infrastructure (Vehicle-to-Everything (V2X) communications). As an instrumental enabler for Intelligent Transportation Systems (ITS), smart cities, and autonomous driving, vehicular networks have attracted significant research interests in recent years both from the academic and industrial communities [1]- [5]. So far, there are two major approaches for V2X communications: dedicated short range communications (DSRC) and cellular based vehicular communication [6], [7].…”

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confidence: 99%

“…V2X allows every vehicle to communicate with different types of communication entities, such as pedestrians, Road-Side Units (RSU), satellites, internet/cloud, and other vehicles. Both V2X techniques 1 have their respective advantages and limitations when adopted in a vehicular environments. As a result, an integration into heterogeneous vehicular networks has been suggested to exploit their unique benefits, while addressing their individual drawbacks.…”

mentioning

confidence: 99%

“…Dynamic Resource Allocation (RA) schemes are preferred as they give rise to significantly improved performance (compared to static RA schemes) by efficiently exploiting wireless channel and network variations in a number of dimensions [10]- [12]. 1 Besides IEEE 802.11p and 3GPP, the Internet Engineering Task Force (IETF) has been working on V2X related topics from a network and transport layer perspective, specially making necessary changes to make IPv6 more suitable for V2X communications [9]. This work is licensed under a Creative Commons Attribution 4.0 License.…”

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confidence: 99%

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A Survey on Resource Allocation in Vehicular Networks

Noor-A-Rahim

Liu

Lee

et al. 2022

IEEE Trans. Intell. Transport. Syst.

134

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Vehicular networks, an enabling technology for Intelligent Transportation System (ITS), smart cities, and autonomous driving, can deliver numerous on-board data services, e.g., road-safety, easy navigation, traffic efficiency, comfort driving, infotainment, etc. Providing satisfactory Quality of Service (QoS) in vehicular networks, however, is a challenging task due to a number of limiting factors such as erroneous and congested wireless channels (due to high mobility or uncoordinated channel-access), increasingly fragmented and congested spectrum, hardware imperfections, and anticipated growth of vehicular communication devices. Therefore, it will be critical to allocate and utilize the available wireless network resources in an ultra-efficient manner. In this paper, we present a comprehensive survey on resource allocation schemes for the two dominant vehicular network technologies, e.g. Dedicated Short Range Communications (DSRC) and cellular based vehicular networks. We discuss the challenges and opportunities for resource allocations in modern vehicular networks and outline a number of promising future research directions.

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Coding-Assisted Broadcast Scheduling via Memetic Computing in SDN-Based Vehicular Networks

Cited by 46 publications

References 30 publications

ARTNet: Ai-Based Resource Allocation and Task Offloading in a Reconfigurable Internet of Vehicular Networks

ARTNet: Ai-Based Resource Allocation and Task Offloading in a Reconfigurable Internet of Vehicular Networks

Efficient data handover and intelligent information assessment in software‐defined vehicular social networks

A Survey on Resource Allocation in Vehicular Networks

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