Cloud Computing in VANETs: Architecture, Taxonomy, and Challenges

Aliyu, Ahmed; Abdullah, Abdul Hanan; Kaiwartya, Omprakash; Cao, Yue; Usman, Mohammed; Kumar, Sushil; Lobiyal, D. K.; Raw, Ram Shringar

doi:10.1080/02564602.2017.1342572

Cited by 50 publications

(26 citation statements)

References 65 publications

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“…Virtualization of vehicular resources has been considered in the last years to improve performance, perception and context-awareness by using cloud architectures [11,12]. The research has passed from vehicles using cloud resources to real vehicular cloud computing, involving infrastructures and OBUs in the cloud, or even hybrid approaches.…”

Section: Related Workmentioning

confidence: 99%

SURROGATES: Virtual OBUs to Foster 5G Vehicular Services

et al. 2019

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Virtualization technologies are key enablers of softwarized 5G networks, and their usage in the vehicular domain can provide flexibility and reliability in real deployments, where mobility and processing needs may be an issue. Next-generation vehicular services, such as the ones in the area of urban mobility and, in general, those interconnecting on-board sensors, require continuous data gathering and processing, but current architectures are stratified in two-tier solutions in which data is collected by on-board units (OBU) and sent to cloud servers. In this line, intermediate cache and processing layers are needed in order to cover quasi-ubiquitous data-gathering needs of vehicles in scenarios of smart cities/roads considering vehicles as moving sensors. The SURROGATES solution presented in this paper proposes to virtualize vehicle OBUs and create a novel Multi-Access Edge Computing (MEC) layer with the aim of offloading processing from the vehicle and serving data-access requests. This deals with potential disconnection periods of vehicles, saves radio resources when accessing the physical OBU and improves data processing performance. A proof of concept has been implemented using OpenStack and Open Source MANO to virtualize resources and gather data from in-vehicle sensors, and a final traffic monitoring service has been implemented to validate the proposal. Performance results reveal a speedup of more than 50% in the data request resolution, with consequently great savings of network resources in the wireless segment. Thus, this work opens a novel path regarding the virtualization of end-devices in the Intelligent Transportation Systems (ITS) ecosystem.

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Section: Related Workmentioning

confidence: 99%

SURROGATES: Virtual OBUs to Foster 5G Vehicular Services

et al. 2019

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“…Data dissemination was one of most critical issues for vehicular traffic environments [28]. These real-time data applications required complex computations and brought challenges in implementing applications for vehicle devices [29,30]. Recently, many researches adopted clod computing to address these challenges for vehicle devices.…”

Section: Related Workmentioning

confidence: 99%

Analysis and Design of Functional Device for Vehicular Cloud Computing

Sha

Wang

et al. 2019

Electronics

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Relay technology application becomes prevalent nowadays, as it can effectively extend the communication distance, especially for vehicular networks with a limited communication range. Combined with vehicular cloud (VC), transmission efficiency can be improved by offloading partial data. Hence, designing a vehicle relay algorithm and implementation embedded vehicle device is critical. In this paper, VC is considered to deal with the complexity computation in our proposed system model. Without a loss of generality, an end-to-end vehicle communication with one assisted vehicle is analyzed firstly on a transmission link based on VC. Here, the signal-to-noise ratio (SNR) on the receiving end and link outage probability is obtained to enhance the link reliability. The VC computing helps us further simplify computational complexity. Subsequently, an embedded vehicle-enabled device is designed to achieve the optimal path relay selection in realistic vehicular environments. In the functional device framework, we display an optimal path relay selection algorithm according to the link quality. Finally, the performance of the transmission link on the outage probability related with SNR is verified in the simulation results. Meanwhile, the effect of the relay gain is also analyzed. The application of a vehicle-enabled embedded device could improve the performance of vehicular networks.

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“…But this type of service requires a lot of complex data processing and calculations. By acquiring the corresponding computing resources from the cloud computing center, the unmanned vehicle can realize advanced application services such as environment recognition and driving cooperation, and form a vehicle-mounted cloud computing VCC (Vehicular Cloud Computing) [1,2]. However, a large number of computing tasks and frequent data transmission may cause the cloud device to be overloaded, so that the calculation cannot be completed in time.…”

Section: Introductionmentioning

confidence: 99%

Reliability and capability based computation offloading strategy for vehicular ad hoc clouds

Peng

Hou

et al. 2019

J Cloud Comp

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In the Internet of Vehicles (IoV), with the increasing demand for intelligent technologies such as driverless driving, more and more in-vehicle applications have been put into autonomous driving. For the computationally intensive task, the vehicle self-organizing network uses other high-performance nodes in the vehicle driving environment to hand over tasks to these nodes for execution. In this way, the computational load of the cloud alleviated. However, due to the unreliability of the communication link and the dynamic changes of the vehicle environment, lengthy task completion time may lead to the increase of task failure rate. Although the flooding algorithm can improve the success rate of task completion, the offloading expend will be large. Aiming at this problem, we design the partial flooding algorithm, which is a comprehensive evaluation method based on system reliability in the vehicle computing environment without infrastructure. Using V2V link to select some nodes with better performance for partial flooding offloading to reduce the task complete time, improve system reliability and cut down the impact of vehicle mobility on offloading. The results show that the proposed offloading strategy can not only improve the utilization of computing resources, but also promote the offloading performance of the system.

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Cloud Computing in VANETs: Architecture, Taxonomy, and Challenges

Cited by 50 publications

References 65 publications

SURROGATES: Virtual OBUs to Foster 5G Vehicular Services

SURROGATES: Virtual OBUs to Foster 5G Vehicular Services

Analysis and Design of Functional Device for Vehicular Cloud Computing

Reliability and capability based computation offloading strategy for vehicular ad hoc clouds

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