TY - GEN
T1 - DARTS
T2 - 2022 Workshop on Advanced Tools, Programming Languages, and PLatforms for Implementing and Evaluating Algorithms for Distributed Systems, ApPLIED 2022
AU - Gupta, Ragini
AU - Chen, Bo
AU - Liu, Shengzhong
AU - Wang, Tianshi
AU - Sandha, Sandeep Singh
AU - Souza, Abel
AU - Nahrstedt, Klara
AU - Abdelzaher, Tarek
AU - Srivastava, Mani
AU - Shenoy, Prashant
AU - Smith, Jeffrey
AU - Wigness, Maggie
AU - Suri, Niranjan
N1 - Funding Information:
Research reported in this paper was sponsored in part by the DEVCOM Army Research Laboratory under Cooperative Agreement W911NF-17-2-0196 (ARL IoBT CRA). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S.Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein. We thank Robert Brice, Erick Reynoso, Mark Spychala, Gordon MacDonald, Pieter Haines, Jeff Swanson, Ed Creegan, and Sean D Arcy for their help during the course of the DARTS design.
Funding Information:
Research reported in this paper was sponsored in part by the DEV-COM Army Research Laboratory under Cooperative Agreement W911NF-17-2-0196 (ARL IoBT CRA). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S.Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein. We thank Robert Brice, Erick Reynoso, Mark Spy-chala, Gordon MacDonald, Pieter Haines, Jeff Swanson, Ed Creegan, and Sean D’Arcy for their help during the course of the DARTS design.
Publisher Copyright:
© 2022 ACM.
PY - 2022/7/25
Y1 - 2022/7/25
N2 - IoT (Internet of Things) sensor devices are becoming ubiquitous in diverse smart environments, including smart homes, smart cities, smart laboratories, and others. To handle their IoT sensor data, distributed edge-cloud infrastructures are emerging to capture, distribute, and analyze them and deliver important services and utilities to different communities. However, there are several challenges for these IoT-edge-cloud infrastructures to provide efficient and effective services to users: (1) how to deliver real-time distributed services under diverse IoT devices, including cameras, meteorological and other sensors; (2) how to provide robustness and resilience of distributed services within the IoT-edge-cloud infrastructures to withstand failures or attacks; (3) how to handle AI workloads are in an efficient manner under constrained network conditions. To address these challenges, we present DARTS, which is composed of different IoT, edge, cloud services addressing application portability, real-time robust data transfer and AI-driven capabilities. We benchmark and evaluate these services to showcase the practical deployment of DARTS catering to application-specific constraints.
AB - IoT (Internet of Things) sensor devices are becoming ubiquitous in diverse smart environments, including smart homes, smart cities, smart laboratories, and others. To handle their IoT sensor data, distributed edge-cloud infrastructures are emerging to capture, distribute, and analyze them and deliver important services and utilities to different communities. However, there are several challenges for these IoT-edge-cloud infrastructures to provide efficient and effective services to users: (1) how to deliver real-time distributed services under diverse IoT devices, including cameras, meteorological and other sensors; (2) how to provide robustness and resilience of distributed services within the IoT-edge-cloud infrastructures to withstand failures or attacks; (3) how to handle AI workloads are in an efficient manner under constrained network conditions. To address these challenges, we present DARTS, which is composed of different IoT, edge, cloud services addressing application portability, real-time robust data transfer and AI-driven capabilities. We benchmark and evaluate these services to showcase the practical deployment of DARTS catering to application-specific constraints.
KW - IoT
KW - anomaly detection
KW - computational offloading
KW - distributed infrastructure
KW - real-time data transfer
KW - video compression
UR - http://www.scopus.com/inward/record.url?scp=85136186156&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85136186156&partnerID=8YFLogxK
U2 - 10.1145/3524053.3542742
DO - 10.1145/3524053.3542742
M3 - Conference contribution
AN - SCOPUS:85136186156
T3 - ApPLIED 2022 - Proceedings of the 2022 Workshop on Advanced Tools, Programming Languages, and PLatforms for Implementing and Evaluating Algorithms for Distributed Systems
SP - 15
EP - 23
BT - ApPLIED 2022 - Proceedings of the 2022 Workshop on Advanced Tools, Programming Languages, and PLatforms for Implementing and Evaluating Algorithms for Distributed Systems
PB - Association for Computing Machinery
Y2 - 25 July 2022
ER -