AVARAC: An Availability-Based Resource Allocation Scheme for Vehicular Cloud

Intelligent transportation systems (ITSs) are comprised of multiple technologies that are applied to improve the quality of transport, offering services and applications that will monitor, manage the transportation systems, and increase the level of comfort and safety for passengers and drivers. ITS...

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Bibliographic Details
Published in:IEEE transactions on intelligent transportation systems 2019-10, Vol.20 (10), p.3688-3699
Main Authors: Meneguette, Rodolfo I., Boukerche, Azzedine, Pimenta, Adinovam H. M.
Format: Article
Language:English
Subjects:
adaptive resource management
Agglomeration
Aggregates
Cloud computing
Computer architecture
Computer science
Drivers
Infrastructure
intelligent transport system
Intelligent transportation systems
Iterative algorithms
Markov processes
Passenger comfort
Passenger safety
Quality of service architectures
Resource allocation
Resource management
Transportation
Vehicular cloud computing
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Summary:Intelligent transportation systems (ITSs) are comprised of multiple technologies that are applied to improve the quality of transport, offering services and applications that will monitor, manage the transportation systems, and increase the level of comfort and safety for passengers and drivers. ITSs services are available for vehicular users through the infrastructure, based on the vehicular network. Furthermore, they can use a vehicular cloud to take advantage of all the resources that a cloud can provide. To achieve this, the ITSs require a mechanism that will aggregate and manage all the available resources provided by the vehicles. Moreover, the aggregation and allocation resource schemes must address the characteristics of the vehicular network to attempt all the quality of service requirements. Therefore, one of the greatest challenges lies in managing the allocation and aggregation of vehicle resources when there is no external infrastructure that will support the system. Hence, we propose an aggregate and allocate resource approach to maximize the availability of service. For this, we formulate the problem through the semi-Markov decision process (SMDP) that will provide an optimal solution for the aggregation and allocation problem. Moreover, we use an average reward function and iterative algorithm to solve the SMDP. The results show that the proposed approach showed stable behavior regardless of the frequency of receiving requests for service. Furthermore, the proposed solution has high average reward when compared to other work in the paper.
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2018.2880298