Nicolaescu, A-C;
Mastorakis, S;
Psaras, I;
(2021)
Store Edge Networked Data (SEND): A Data and Performance Driven Edge Storage Framework.
In:
Proceedings of IEEE INFOCOM 2021 - IEEE Conference on Computer Communications.
IEEE: Vancouver, Canada.
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Abstract
The number of devices that the edge of the Internet accommodates and the volume of the data these devices generate are expected to grow dramatically in the years to come. As a result, managing and processing such massive data amounts at the edge becomes a vital issue. This paper proposes "Store Edge Networked Data" (SEND), a novel framework for in-network storage management realized through data repositories deployed at the network edge. SEND considers different criteria (e.g., data popularity, data proximity from processing functions at the edge) to intelligently place different categories of raw and processed data at the edge based on system-wide identifiers of the data context, called labels. We implement a data repository prototype on top of the Google file system, which we evaluate based on real-world datasets of images and Internet of Things device measurements. To scale up our experiments, we perform a network simulation study based on synthetic and real-world datasets evaluating the performance and trade-offs of the SEND design as a whole. Our results demonstrate that SEND achieves data insertion times of 0.06ms-0.9ms, data lookup times of 0.5ms-5.3ms, and on-time completion of up to 92% of user requests for the retrieval of raw and processed data.
| Type: | Proceedings paper |
|---|---|
| Title: | Store Edge Networked Data (SEND): A Data and Performance Driven Edge Storage Framework |
| Event: | IEEE INFOCOM 2021 - IEEE Conference on Computer Communications |
| ISBN-13: | 978-1-6654-0325-2 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/INFOCOM42981.2021.9488804 |
| Publisher version: | https://doi.org/10.1109/INFOCOM42981.2021.9488804 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Edge computing, Internet of Things (IoT), Data storage at the edge, Data management |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10132960 |
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