Sporadic Cloud-Based Mobile Augmentation on the Top of a Virtualization Layer: A Case Study of Collaborative Downloads in VANETs

Author:

Ordóñez-Morales Esteban Fernando1ORCID,López-Nores Martín2ORCID,Blanco-Fernández Yolanda2ORCID,Reinoso-Mendoza Efren Patricio1,Bravo-Torres Jack Fernando1ORCID,Saiáns-Vázquez José Víctor2,Pazos-Arias José Juan2ORCID,Ramos-Cabrer Manuel2ORCID,Gil-Solla Alberto2ORCID

Affiliation:

1. Universidad Politécnica Salesiana, Calle Vieja 12-30 y Elia Liut, Cuenca, Ecuador

2. Atlantic Research Center for Information and Communication Technologies (AtlantTIC), University of Vigo, Spain

Abstract

Current approaches to Cloud-based Mobile Augmentation (CMA) leverage (cloud-based) resources to meet the requirements of rich mobile applications, so that a terminal (the so-called application node or AppN) can borrow resources lent by a set of collaborator nodes (CNs). In the most sophisticated approaches proposed for vehicular scenarios, the collaborators are nearby vehicles that must remain together near the application node because the augmentation service is interrupted when they move apart. This leads to disruption in the execution of the applications and consequently impoverishes the mobile users’ experience. This paper describes a CMA approach that is able to restore the augmentation service transparently when AppNs and CNs separate. The functioning is illustrated by a NaaS model where the AppNs access web contents that are collaboratively downloaded by a set of CNs, exploiting both roadside units and opportunistic networking. The performance of the resulting approach has been evaluated via simulations, achieving promising results in terms of number of downloads, average download times, and network overhead.

Funder

Atlantic Research Center for Information and Communication Technologies

Publisher

Hindawi Limited

Subject

Strategy and Management,Computer Science Applications,Mechanical Engineering,Economics and Econometrics,Automotive Engineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Survey of Vehicular Cloud Research: Trends, Applications and Challenges;IEEE Transactions on Intelligent Transportation Systems;2020-06

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