Offloading Algorithms for Maximizing Inference Accuracy on Edge Device in an Edge Intelligence System

With the emergence of edge computing, the problem of offloading jobs between an Edge Device (ED) and an Edge Server (ES) received significant attention in the past. Motivated by the fact that an increasing number of applications are using Machine Learning (ML) inference from the data samples collect...

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Vydané v:	IEEE transactions on parallel and distributed systems Ročník 34; číslo 7; s. 1 - 15
Hlavní autori:	Fresa, Andrea, Champati, Jaya Prakash
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.07.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Accuracy Algorithms Approximation algorithms Artificial neural networks Computational modeling Constraints Costs Data models Dynamic programming Edge computing Image classification Inference Inference algorithms Integer programming Linear programming Machine learning Maximization Optimization Polynomials Scheduling Servers
ISSN:	1045-9219, 1558-2183
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