Vehicular Ad Hoc Network (VANET): A Survey, Challenges, and Applications

Rasheed, Asim; Gillani, Saira; Ajmal, Sana; Qayyum, Amir

doi:10.1007/978-981-10-3503-6_4

Cited by 83 publications

(37 citation statements)

References 9 publications

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“…Thus, in the years ahead, VANET will be exploited to improve the experience of not only drivers but also the passengers who use interactive, storage, and computation-intensive applications. The VANETs can provide entertainment services including internet browsing, file transfer, mobile-e-commerce, and video-on-demand [7]. Similarly, any surrounding event captured by a vehicle can be of interest to other vehicles in its vicinity.…”

Section: Vehicular Networkmentioning

confidence: 99%

Services and simulation frameworks for vehicular cloud computing: a contemporary survey

Ahmed

Malik

Hafeez

et al. 2019

J Wireless Com Network

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Vehicular cloud is getting significant research attention due to the technological advancements in smart vehicles. In near future, vehicles are envisioned to become part of a grid network providing cloud services, such as computing, storage, network, and application as a service. Vehicular cloud computing is an emerging area, designed to support delay-sensitive applications. However, this integration of vehicular network and cloud computing introduces new challenges for the research community. New frameworks have been proposed to assimilate and efficiently manage this merger. In this survey paper, we present the recent advancements in vehicular cloud computing domain. The review is primarily focused on two areas. First, we discuss the frameworks designed to utilize the vehicles' onboard resources to provide cloud services and highlight the design issues and research challenges. Secondly, we focus on a detailed study of mobility generators, network, and vehicular ad hoc network simulators, as well as the available vehicular data sets. We thus provide an overarching view of the complete domain of vehicular cloud computing and identify areas for future research directions.

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Section: Vehicular Networkmentioning

confidence: 99%

Services and simulation frameworks for vehicular cloud computing: a contemporary survey

Ahmed

Malik

Hafeez

et al. 2019

J Wireless Com Network

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“…Low-priority service queue r 3 , ..., r i r 1 , ..., r 1 Figure 1: System model. input: data requests of vehicles within coverage (1) while R i 's service queues are not empty do (2) R i constructs the IDNC graph G(V, E) as described in Section 4.1; (3) R i calculates each vertex's weight according to a specific scheduling algorithm; (4) R i finds the maximum weighted clique C * in G; (5) R i generates the IDNC packet by XORing all the data items identified by the vertices in C * and multicast it to all vehicles; (6) Each vehicle decodes the IDNC packet and sends back a 1-bit message to R i , notifying the success/failure of receiving the requested data item; (7) R i updates the service queues and the vehicles' statuses based on the feedbacks. Wireless Communications and Mobile Computing where VH(d j ) is the set of vehicles that are requesting d j and dl min j represents the deadline of the most urgent request among all requests that are asking for item d j .…”

Section: Admission Controllermentioning

confidence: 99%

“…e original IDNCassisted algorithms without admission control are labeled as EDF, SIN, and PVDD, respectively. e algorithms with (1) If R i receives a newly arriving request r i then (2) Determine the priority of r i ; (3) if r i is high priority then (4) Admit r i and put r i into the high priority service queue; (5) else (6) Vectorize r i as rv ij , the mean vector of VE α as rv α , and the mean vector of VE β as rv β ; (7) Calculate rv α and rv β as described in Section 4.2.1; (8) Calculate the distance between rv ij and rv α , and the distance between rv ij and rv β , respectively; (9) Compare the distances (10) if dist(rv ij , rv α ) ≤ dist(rv ij , rv β ) then (11) Reject r i ; (12) Send a rejection message to the vehicle; (13) else (14) if dist(rv ij , rv α ) > dist(rv ij , rv β ) then (15) Admit r i and put r i into the low priority service queue; (16) end if (17) end if (18) end if (19) network coding-aware admission control are denoted as EDF_NCaAC, SIN_NCaAC, and PVDD_NCaAC. e results are obtained when the system is in a steady state and all data points are based on the average of over 5000 simulation runs.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…and the other is user-related application (entertainment, internet access, etc.). Generally speaking, safety-related applications have higher requirements for real-time performance and accuracy, which can significantly reduce the occurrence of traffic accidents, and are the most important compared with user-related applications [6]. For example, when an accident occurs on a road spot, the safetyrelated applications are expected to timely send the information to the follow-up vehicles so these vehicles can take appropriate actions to avoid traffic accidents, such as serial collision.…”

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confidence: 99%

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NCaAC: Network Coding-Aware Admission Control for Prioritized Data Dissemination in Vehicular Ad Hoc Networks

Wang

Zhang

2020

Wireless Communications and Mobile Computing

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Vehicular Ad hoc NETworks (VANETs) are becoming an important part of people’s daily life, as they support a wild range of applications and have great potential in critical fields such as accident warning, traffic control and management, infotainment, and value-added services. However, the harsh and stringent transmission environment in VANETs poses a great challenge to the efficient and effective data dissemination for VANETs, which is the essential in supporting and providing the desired applications. To resolve this issue, Instantly Decodable Network Coding (IDNC) technology is applied to stand up to the tough transmission conditions and to advance the performance. This paper proposes a novel admission control method that works well with any IDNC-assisted data dissemination algorithm, to achieve fast and reliable data dissemination in VANETs. Firstly, the proposed admission control strategy classifies the safety-related applications as high priority and the user-related applications as low priority. It then conducts different admission policies on these two prioritized applications’ data. An artfully designed network coding-aware admission policy is proposed to regulate the flow of low-priority data requests and to prevent the network from congestion, through comparing the vectorized distances between the data requests and the encoding packets. Moreover, the carefully planned admission strategy is benefit for maximizing the network coding opportunities by inclining to admit requests which can contribute more to the encoding clique, thus further enhancing the system performance. Simulation results approve that the proposed admission control method achieves clear advantages in terms of delay, deadline miss ratio, and download success ratio.

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“…These applications can generally be grouped into two categories: safety applications and non-safety applications as shown in Figure 2. We summarize the main applications of these categories in the next paragraphs [21], [22], [23], [24].…”

Section: Video Streaming Over Vehicular Networkmentioning

confidence: 99%

Survey on QoE/QoS Correlation Models for Video Streaming over Vehicular Ad-hoc Networks

2019

CIT. J. comput. inf. technol

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Vehicular Ad-hoc Networks (VANETs) are a new emerging technology which has attracted enormous interest over the last few years. It enables vehicles to communicate with each other and with roadside infrastructures for many applications. One of the promising applications is multimedia services for traffic safety or infotainment. The video service requires a good quality to satisfy the end-user known as the Quality of Experience (QoE). Several models have been suggested in the literature to measure or predict this metric. In this paper, we present an overview of interesting researches, which propose QoE models for video streaming over VANETs. The limits and deficiencies of these models are identified, which shed light on the challenges and real problems to overcome in the future.

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Vehicular Ad Hoc Network (VANET): A Survey, Challenges, and Applications

Cited by 83 publications

References 9 publications

Services and simulation frameworks for vehicular cloud computing: a contemporary survey

Services and simulation frameworks for vehicular cloud computing: a contemporary survey

NCaAC: Network Coding-Aware Admission Control for Prioritized Data Dissemination in Vehicular Ad Hoc Networks

Survey on QoE/QoS Correlation Models for Video Streaming over Vehicular Ad-hoc Networks

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