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Áika: A Distributed Edge System for AI Inference.

Authors :
Alslie, Joakim Aalstad
Ovesen, Aril Bernhard
Nordmo, Tor-Arne Schmidt
Johansen, Håvard Dagenborg
Halvorsen, Pål
Riegler, Michael Alexander
Johansen, Dag
Source :
Big Data & Cognitive Computing; Jun2022, Vol. 6 Issue 2, p68-68, 19p
Publication Year :
2022

Abstract

Video monitoring and surveillance of commercial fisheries in world oceans has been proposed by the governing bodies of several nations as a response to crimes such as overfishing. Traditional video monitoring systems may not be suitable due to limitations in the offshore fishing environment, including low bandwidth, unstable satellite network connections and issues of preserving the privacy of crew members. In this paper, we present Áika, a robust system for executing distributed Artificial Intelligence (AI) applications on the edge. Áika provides engineers and researchers with several building blocks in the form of Agents, which enable the expression of computation pipelines and distributed applications with robustness and privacy guarantees. Agents are continuously monitored by dedicated monitoring nodes, and provide applications with a distributed checkpointing and replication scheme. Áika is designed for monitoring and surveillance in privacy-sensitive and unstable offshore environments, where flexible access policies at the storage level can provide privacy guarantees for data transfer and access. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
25042289
Volume :
6
Issue :
2
Database :
Complementary Index
Journal :
Big Data & Cognitive Computing
Publication Type :
Academic Journal
Accession number :
157662160
Full Text :
https://doi.org/10.3390/bdcc6020068