logo EDITE Benjamin BARON
Identité
Benjamin BARON
État académique
Thèse soutenue le 2016-10-11
Sujet: Externalisation de grandes masses de données sur des nœuds mobiles banalisés
Direction de thèse:
Encadrement de thèse:
Laboratoire:
Voisinage
Ellipse bleue: doctorant, ellipse jaune: docteur, rectangle vert: permanent, rectangle jaune: HDR. Trait vert: encadrant de thèse, trait bleu: directeur de thèse, pointillé: jury d'évaluation à mi-parcours ou jury de thèse.
Productions scientifiques
oai:hal.archives-ouvertes.fr:hal-01074558
Software-Defined Vehicular Backhaul
International audience
The network of roads and highways is a promising candidate to help network operators offload their infrastructure and cope with the ever-growing amount of data exchanged on the Internet. By piggybacking data onto vehicles, roads can be turned into a large-capacity transmission system when considering the increasing number of journeys involving vehicles. The data to be transferred is opportunistically loaded on or off the vehicles at specific locations referred to as offloading spots. Two of the main challenges of such a system are how to assign the road paths matching the data transfer requirements and how much data to allocate to each flow of vehicles. We propose a centralized SDN-like architecture consisting of a central controller acting as a service broker and the offloading spots as SDN agents. The controller computes the road paths that accommodate the data transfer requirements and installs the corresponding forwarding states at each offloading spot along those paths. We describe our SDN-controlled offloading system and evaluate its performance using road traffic counts from France. Our numerical results show that the controller can achieve efficient and fair allocation of multiple data transfers between major cities of France. Each transfer successfully delivers over 10 PB of data within a week when considering that 10% of vehicles on the road are equipped with 1TB of storage.
Wireless Days 2014 http://hal.upmc.fr/hal-01074558 Wireless Days 2014, Nov 2014, Rio de Janeiro, BrazilARRAY(0x7f54726c2d20) 2014-11-12
oai:hal.archives-ouvertes.fr:hal-01148427
Étude de l'intermodalité pour le délestage des réseaux d'infrastructure
National audience
Nous proposons de tirer parti des déplacements des véhicules des particuliers sur les routes pour permettre aux réseaux d'infrastructure de délester une partie de leur trafic de manière opportuniste. Pour réaliser un tel service, les données sont réparties sur les véhicules équipés de disques durs. La sélection des véhicules se fait en fonction de leur itinéraire et ce afin de répondre aux contraintes qui caractérisent les données à transférer. L'allocation des transferts de données s'avère être un problème complexe pour un réseau routier à très grande l'échelle. Aussi, nous proposons un algorithme de réduction de l'infrastructure routière qui calcule un réseau de recouvrement dont les liens logiques agrègent plusieurs segments de route. Nous formulons alors le problème de l'allocation des transferts de données sous forme d'un modèle de programmation linéaire. Ce modèle définit une stratégie d'allocation des données qui maximise le débit total réalisé par les flots de véhicules impliqués dans ces transferts.
ALGOTEL 2015 — 17èmes Rencontres Francophones sur les Aspects Algorithmiques des Télécommunications https://hal.archives-ouvertes.fr/hal-01148427 ALGOTEL 2015 — 17èmes Rencontres Francophones sur les Aspects Algorithmiques des Télécommunications, Jun 2015, Beaune, FranceARRAY(0x7f54726c6278) 2015-06-02
oai:hal.archives-ouvertes.fr:hal-01247713
Offloading Massive Data onto Passenger Vehicles: Topology Simplification and Traffic Assignment
International audience
Offloading is a promising technique for alleviating the ever-growing traffic load from infrastructure-based networks such as the Internet. Offloading consists in using alternative methods of transmission as a cost-effective solution for network operators to extend their transport capacity. In this paper, we advocate the use of conventional vehicles equipped with storage devices as data carriers whilst being driven for daily routine journeys. The road network can be turned into a large-capacity transmission system to offload bulk transfers of delay-tolerant data from the Internet. The challenges we address include how to assign data to flows of vehicles and while coping with the complexity of the road network. We propose an embedding algorithm that computes an offloading overlay where each logical link spans over multiple stretches of road from the underlying road infrastructure. We then formulate the data transfer assignment problem as a novel linear programming model we solve to determine the optimal logical paths matching the performance requirements of a data transfer. We evaluate our road traffic allocation scheme using actual road traffic counts in France. The numerical results show that 20% of vehicles in circulation in France equipped with only one Terabyte of storage can offload Petabyte transfers in a week.
ISSN: 1063-6692 IEEE/ACM Transactions on Networking http://hal.upmc.fr/hal-01247713 IEEE/ACM Transactions on Networking, IEEE/ACM, 2015ARRAY(0x7f54726c3e70) 2015-12
oai:hal.archives-ouvertes.fr:hal-00994848
Vehicles as Big Data Carriers: Road Map Space Reduction and Efficient Data Assignment
International audience
We advocate the use of a data shuttle service model to offload bulk transfers of delay-tolerant data from the Internet onto standard vehicles equipped with data storage capabilities. We first propose an embedding algorithm that computes an offloading overlay on top of the road infrastructure. The goal is to simplify the representation of the road infrastructure as raw maps are too complex to handle. In this overlay, each logical link maps multiple stretches of road from the underlying road infrastructure. We formulate then the data transfer assignment problem as a novel linear programming model that determines the most appropriate logical paths in the offloading overlay for a data transfer request. We evaluate our proposal using actual road traffic counts in France. Numerical results show that we can satisfy weekly aggregate requests in the petabyte range while achieving cumulative bandwidth above 10 Gbps with a market share of 20% and only one terabyte of storage per vehicle.
VTC2014-Fall - IEEE 80th Vehicular Technology Conference http://hal.upmc.fr/hal-00994848 VTC2014-Fall - IEEE 80th Vehicular Technology Conference, Sep 2014, Vancouver, Canada. 2014ARRAY(0x7f54726c32a8) 2014-09-14
oai:hal.archives-ouvertes.fr:hal-01310430
Virtualizing vehicular node resources: Feasibility study of virtual machine migration
International audience
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.
Vehicular communication, Elsevier http://hal.upmc.fr/hal-01310430 Vehicular communication, Elsevier, 2016, <10.1016/j.vehcom.2016.04.001>ARRAY(0x7f54726cd800) 2016
Soutenance
Thèse: Transport intermodal de données massives pour le délestage des réseaux d'infrastructure
Soutenance: 2016-10-11
Rapporteurs: Sidi Mohammed SENOUCI    Marco FIORE