2016 journal article

Virtualizing vehicular node resources: Feasibility study of virtual machine migration

VEHICULAR COMMUNICATIONS, 4, 39–46.

By: B. Baron, M. Campista*, P. Spathis, L. Costa*, M. Amorim*, O. Duarte*, G. Pujolle, Y. Viniotis n

author keywords: Vehicular network; Virtualization; Virtual machine migration
TL;DR: This paper uses the real traces of a bus transit system to simulate a vehicular network where virtual machines migrate via V2V communications between mobile nodes and shows that virtual machines of several hundreds of Megabytes can migrate between moving buses. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

With emerging geo-distributed services, there is a need to coordinate the use of resources offered by field-area networks. In the case of vehicular networks, such resources include the processing, sensing, and storage capabilities offered to service providers for urban sensing or intelligent transportation. In this paper, we propose to virtualize the resources embedded on the vehicular nodes to allow multiple tenants to coexist and deploy their services on the same underlying mobile substrate. Virtualization is the task of an infrastructure provider that controls the mobile substrate and allocates sliced resources to the tenants. A service results from a collection of virtual machines hosted on the mobile nodes allocated by the infrastructure provider. Efficient utilization of the node resources may trigger virtual machine migrations. We study the problem of virtual machine migrations through V2V communications between mobile nodes. To evaluate the impact of such migrations on the resource allocation process, we use the real traces of a bus transit system to simulate a vehicular network where virtual machines migrate via V2V communications. Our results show that virtual machines of several hundreds of Megabytes can migrate between moving buses. We then discuss design principles and research issues toward the full virtualization of opportunistic networks.