TY - GEN
T1 - Store edge networked data (SEND)
T2 - 40th IEEE Conference on Computer Communications, INFOCOM 2021
AU - Nicolaescu, Adrian Cristian
AU - Mastorakis, Spyridon
AU - Psaras, Ioannis
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/5/10
Y1 - 2021/5/10
N2 - 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.
AB - 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.
KW - Data management
KW - Data storage at the edge
KW - Edge computing
KW - Internet of Things (IoT)
UR - http://www.scopus.com/inward/record.url?scp=85106563436&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85106563436&partnerID=8YFLogxK
U2 - 10.1109/INFOCOM42981.2021.9488804
DO - 10.1109/INFOCOM42981.2021.9488804
M3 - Conference contribution
AN - SCOPUS:85106563436
T3 - Proceedings - IEEE INFOCOM
BT - INFOCOM 2021 - IEEE Conference on Computer Communications
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 10 May 2021 through 13 May 2021
ER -