Please use this identifier to cite or link to this item:
https://ruomo.lib.uom.gr/handle/7000/1412
Title: | An experimentation environment for SDN-based autonomous vehicles in smart cities |
Authors: | Papadakis, Athanasios Theodorou, Tryfon Mamatas, Lefteris Petridou, Sophia |
Subjects: | FRASCATI::Engineering and technology FRASCATI::Natural sciences::Computer and information sciences |
Keywords: | Internet Internet of Things software defined networking wireless sensor networks Protocols Smart cities Road side unit Routing Topology |
Issue Date: | 2021 |
First Page: | 391 |
Last Page: | 393 |
Volume Title: | 2021 17th International Conference on Network and Service Management (CNSM) |
Abstract: | The emerging Internet of Things (IoT) in conjunction with Autonomous Vehicles (AVs) have increased the complexity of network administration and control. In this context, recent proposals bring together Software-Defined Networks (SDNs) with AVs practices, i.e., introducing innovative network control strategies bespoke for smart city infrastructures. However, an experimentation environment that combines the realism of an AVs ecosystem with the SDN network paradigm is a necessity, facilitating the investigation of particular research issues, including efficient data management and routing, as well as security. In this demo, we introduce a relevant facility that builds-up on novel open environments for hands-on experimentation, namely: (i) CARLA, an open realistic urban-driving simulator; (ii) Cooja, a state-of-the-art emulator for Wireless Sensor Networks (WSNs); and (iii) SD-MIoT, a novel SDN solution for mobile IoT. Our experimentation exercise currently focuses on maintaining connectivity of AVs to the fixed infrastructure, e.g., Road Side Units (RSUs), with SDN strategies. We demonstrate the capabilities of the proposed experimentation environment with proof-of-concept results on packet delivery ratio and control overhead, quantifying the efficiency of the considered SDN approach to maintain AV connectivity, as well as with a video visualizing the outcome of our experiments. |
URI: | https://doi.org/10.23919/CNSM52442.2021.9615509 https://ruomo.lib.uom.gr/handle/7000/1412 |
ISBN: | 978-3-903176-36-2 |
Other Identifiers: | 10.23919/CNSM52442.2021.9615509 |
Appears in Collections: | Department of Applied Informatics |
Files in This Item:
File | Description | Size | Format | |
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CNSM_2021 (1).pdf | 745,74 kB | Adobe PDF | View/Open |
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