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AVARAC: An Availability-Based Resource Allocation Scheme for Vehicular Cloud
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DOI：10.1109/TITS.2018.2880298.png)
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Abstract
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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.
Keywords:
Vehicular cloud computing
adaptive resource management
intelligent transport system
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