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Authors: Alireza Furutanpey and Schahram Dustdar

Affiliation: Distributed Systems Group, TU Wien, Argentinierstrasse 8, Vienna, Austria

Keyword(s): Edge Computing, Edge Intelligence, Dynamic Neural Networks, Split Computing.

Abstract: Deep Neural Networks (DNNs) are the backbone of virtually all complex, intelligent systems. However, networks which achieve state-of-the-art accuracy cannot execute inference tasks within a reasonable time on commodity hardware. Consequently, latency-sensitive mobile and Internet of Things (IoT) applications must compromise by executing a heavily compressed model locally or offloading their inference task to a remote server. Sacrificing accuracy is unacceptable for critical applications, such as anomaly detection. Offloading inference tasks requires ideal network conditions and harbours privacy risks. In this position paper, we introduce a series of planned research work with the overarching aim to provide a (close to) no compromise framework for accurate and fast inference. Specifically, we envision a composition of solutions that leverage the upsides of different computing paradigms while overcoming their downsides through collaboration and adaptive methods that maximise resource e fficiency. (More)

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Paper citation in several formats:
Furutanpey, A. and Dustdar, S. (2022). Adaptive and Collaborative Inference: Towards a No-compromise Framework for Distributed Intelligent Systems. In Proceedings of the 18th International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-758-613-2; ISSN 2184-3252, SciTePress, pages 144-151. DOI: 10.5220/0011547800003318

@conference{webist22,
author={Alireza Furutanpey. and Schahram Dustdar.},
title={Adaptive and Collaborative Inference: Towards a No-compromise Framework for Distributed Intelligent Systems},
booktitle={Proceedings of the 18th International Conference on Web Information Systems and Technologies - WEBIST},
year={2022},
pages={144-151},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011547800003318},
isbn={978-989-758-613-2},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 18th International Conference on Web Information Systems and Technologies - WEBIST
TI - Adaptive and Collaborative Inference: Towards a No-compromise Framework for Distributed Intelligent Systems
SN - 978-989-758-613-2
IS - 2184-3252
AU - Furutanpey, A.
AU - Dustdar, S.
PY - 2022
SP - 144
EP - 151
DO - 10.5220/0011547800003318
PB - SciTePress

- Science and Technology Publications, Lda.
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