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Journal articles
Centrally-Controlled Mass Data Offloading Using Vehicular Traffic
Abstract : With over 300 billion vehicle trips made in the USA and 64 billion in France per year, network operators have the opportunity to utilize the existing road and highway network as an alternative data network to offload large amounts of delay-tolerant traffic. To enable the road network as a large-capacity transmission system, we exploit the existing mobility of vehicles equipped with wireless and storage capacities together with a collection of offloading spots. An offloading spot is a data storage equipment located where vehicles usually park. Data is transloaded from a conventional data network to the closest offloading spot and then shipped by vehicles along their line of travel. The subsequent offloading spots act as data relay boxes where vehicles can drop off data for later pickups by other vehicles, depending on their direction of travel. The main challenges of this offloading system are how to compute the road path matching the performance requirements of a data transfer and how to configure the sequence of offloading spots involved in the transfer. We propose a scalable and adaptive centralized architecture built on SDN that maximizes the utilization of the flow of vehicles connecting consecutive offloading spots. We simulate the performance of our system using real roads traffic counts for France. Results show that the centralized controlled offloading architecture can achieve an efficient and fair allocation of concurrent data transfers between major cities in France.
Cited literature [36 references]
https://hal.sorbonne-universite.fr/hal-01495055
Contributor : Benjamin Baron <>
Submitted on : Friday, March 24, 2017 - 2:49:52 PM
Last modification on : Wednesday, July 8, 2020 - 12:43:54 PM
Document(s) archivé(s) le : Sunday, June 25, 2017 - 1:20:56 PM
Contributor : Benjamin Baron <>
Submitted on : Friday, March 24, 2017 - 2:49:52 PM
Last modification on : Wednesday, July 8, 2020 - 12:43:54 PM
Document(s) archivé(s) le : Sunday, June 25, 2017 - 1:20:56 PM
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