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  •   Open Research
  • AUT Faculties
  • Faculty of Design and Creative Technologies (Te Ara Auaha)
  • School of Engineering, Computer and Mathematical Sciences - Te Kura Mātai Pūhanga, Rorohiko, Pāngarau
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Big Data Offloading using Smart Public Vehicles with Software Defined Connectivity

Munjal, R; Liu, W; Li, XJ; Gutierrez, J
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Conference Contribution (1.767Mb)
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http://hdl.handle.net/10292/13064
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Abstract
With the explosive increase in the number of mobile devices such as smartphones or laptops, the design of mobile applications becomes increasingly complex, power hungry and resource consuming. Therefore, conventional networks are facing serious problems such as traffic overload and energy consumption due to high traffic demands. As a result, network designers are looking for more options to accommodate numerous data requirements. Aiming to find a promising way to tackle this problem, we are investigating heterogeneous networking architectures, which utilize the existing public transport network as an alternative communication network along with infrastructure-based networks. We propose a heterogeneous network architecture called Software Defined Connectivity (SDC) that utilizes the flow of transport network such as buses, trains, and ferries to start the forwarding process from nearby parking/offloading spots to disseminate data along with conventional networks. Results show that the SDC architecture helps in data offloading over public transport vehicles as per the profiles of each user with significant savings of energy.
Keywords
Delay Tolerant Network; Smart Public Transport Vehicles; Big Data; Network Selection
Date
October 2019
Source
In 2019 IEEE Intelligent Transportation Systems Conference (ITSC) (pp. 3361-3366). IEEE.
Item Type
Conference Contribution
Publisher
IEEE
DOI
10.1109/itsc.2019.8917322
Publisher's Version
https://ieeexplore.ieee.org/document/8917322
Rights Statement
Copyright © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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