Abstract
The demand for computational resources in vehicular environments has increased due to the deployment of numerous intelligent transportation systems in the last decade. The federated vehicular cloud, a variant of vehicular cloud computing, can be considered as an emerging alternative for executing computationally intensive and delay-sensitive applications. However, the federated vehicular cloud is beset with a capacity-constrained communication channel and limited resource capacity in individual vehicles, which lead to data and resource management challenges. Therefore, we propose UniDRM, a unified data and resource management framework for the federated vehicular cloud, to address these challenges. The UniDRM organizes vehicles on the road into clusters based on their mobility and resource characteristics, such as resource cost, resource security level, resource type, and available resource capacity. The data of computationally intensive tasks are then partitioned using our proposed analytical model and assigned to individual vehicles in the cluster for parallel execution. Three partitioning and scheduling schemes: time-aware, cost-aware, and security-aware are proposed in this study to execute time-critical tasks, low-cost tasks, and high-security tasks, respectively. Through realistic simulations, a comparative analysis of the proposed partitioning and scheduling schemes is presented.
Highlights
In the last two decades, Intelligent Transport System (ITS), which is the introduction of technology to make transportation safer and more efficient [1], has experienced many advancements
The Road Side Unit (RSU) organizes the vehicles that meet the resource capacity and credibility requirements into clusters based on the type of resource and the vehicle’s direction of travel
The cluster formation schemes proposed for the UniDRM cover the formation of storage as a service (StaaS) and computation as a service (CaaS) clusters, as described in Section IV, for simplicity, we considered the infrastructure-less CaaS clusters for implementation of the data management phase of the UniDRM framework
Summary
In the last two decades, Intelligent Transport System (ITS), which is the introduction of technology to make transportation safer and more efficient [1], has experienced many advancements. Danquah et al.: UniDRM: Unified Data and Resource Management for Federated Vehicular Cloud Computing access the cloud services on a pay-as-you-go basis. In order to efficiently provide the different cloud services, two main classes of vehicular cloud deployment models have been proposed in the literature: the peer-to-peer deployment model and the federated deployment model [12] This classification depends on the type of services provided, the form of service access, the number of vehicles involved in the service provision, and the resource management scheme used. In the federated deployment model, a centralized resource manager in a Region of Interest (RoI) of a road acquires resources from different vehicle owners and organizes them in the form of a pool to provide cloud services to clients as a single logical entity.
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