UniDRM: Unified Data and Resource Management for Federated Vehicular Cloud Computing

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 where resources embedded in individual vehicles are organized...

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Autores principales:	Wiseborn M. Danquah, D. Turgay Altilar
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Vehicular cloud computing federated vehicular cloud resource management resource-based clustering resource ranking divisible load partitioning Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/3e9c33151f1440b18e855b9ade12a696
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spelling	oai:doaj.org-article:3e9c33151f1440b18e855b9ade12a6962021-12-02T00:00:54ZUniDRM: Unified Data and Resource Management for Federated Vehicular Cloud Computing2169-353610.1109/ACCESS.2021.3127521https://doaj.org/article/3e9c33151f1440b18e855b9ade12a6962021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9626776/https://doaj.org/toc/2169-3536The 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 where resources embedded in individual vehicles are organized as a single unit to provide cloud services, is considered as an emerging alternative to the conventional cloud platforms for the execution of 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, leading to challenges in data and resource management. To address these challenges, we propose UniDRM, a unified data and resource management framework for the federated vehicular cloud. The UniDRM organizes vehicles on the road into clusters based on their mobility and resource characteristics, such as resource cost, resource credibility 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 data partitioning and scheduling schemes: time-aware, cost-aware, and reliability-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.Wiseborn M. DanquahD. Turgay AltilarIEEEarticleVehicular cloud computingfederated vehicular cloudresource managementresource-based clusteringresource rankingdivisible load partitioningElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 157052-157067 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Vehicular cloud computing federated vehicular cloud resource management resource-based clustering resource ranking divisible load partitioning Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Vehicular cloud computing federated vehicular cloud resource management resource-based clustering resource ranking divisible load partitioning Electrical engineering. Electronics. Nuclear engineering TK1-9971 Wiseborn M. Danquah D. Turgay Altilar UniDRM: Unified Data and Resource Management for Federated Vehicular Cloud Computing
description	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 where resources embedded in individual vehicles are organized as a single unit to provide cloud services, is considered as an emerging alternative to the conventional cloud platforms for the execution of 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, leading to challenges in data and resource management. To address these challenges, we propose UniDRM, a unified data and resource management framework for the federated vehicular cloud. The UniDRM organizes vehicles on the road into clusters based on their mobility and resource characteristics, such as resource cost, resource credibility 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 data partitioning and scheduling schemes: time-aware, cost-aware, and reliability-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.
format	article
author	Wiseborn M. Danquah D. Turgay Altilar
author_facet	Wiseborn M. Danquah D. Turgay Altilar
author_sort	Wiseborn M. Danquah
title	UniDRM: Unified Data and Resource Management for Federated Vehicular Cloud Computing
title_short	UniDRM: Unified Data and Resource Management for Federated Vehicular Cloud Computing
title_full	UniDRM: Unified Data and Resource Management for Federated Vehicular Cloud Computing
title_fullStr	UniDRM: Unified Data and Resource Management for Federated Vehicular Cloud Computing
title_full_unstemmed	UniDRM: Unified Data and Resource Management for Federated Vehicular Cloud Computing
title_sort	unidrm: unified data and resource management for federated vehicular cloud computing
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/3e9c33151f1440b18e855b9ade12a696
work_keys_str_mv	AT wisebornmdanquah unidrmunifieddataandresourcemanagementforfederatedvehicularcloudcomputing AT dturgayaltilar unidrmunifieddataandresourcemanagementforfederatedvehicularcloudcomputing
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UniDRM: Unified Data and Resource Management for Federated Vehicular Cloud Computing

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