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Modelling multi-cell edge video analytics
KTH, Skolan för elektroteknik och datavetenskap (EECS).
KTH, Skolan för elektroteknik och datavetenskap (EECS).ORCID-id: 0000-0002-2764-8099
2022 (engelsk)Inngår i: IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2022), Institute of Electrical and Electronics Engineers Inc. , 2022, s. 1665-1671Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Edge intelligence is a scalable solution for analyzing distributed data, but it cannot provide reliable services in large-scale cellular networks unless the inherent aspects of fading and interference are also taken into consideration. In this paper, we present the first mathematical framework for modelling edge video analytics in multi-cell cellular systems. We derive the expressions for the coverage probability, the ergodic capacity, the probability of successfully completing the video analytics within a target delay requirement, and the effective frame rate. We also analyze the effect of the system parameters on the accuracy of the detection algorithm, the supported frame rate at the edge server, and the system fairness.

sted, utgiver, år, opplag, sider
Institute of Electrical and Electronics Engineers Inc. , 2022. s. 1665-1671
Serie
IEEE International Conference on Communications, ISSN 1550-3607
Emneord [en]
Edge intelligence, stochastic geometry, queuing theory, edge computing
HSV kategori
Identifikatorer
URN: urn:nbn:se:kth:diva-322432DOI: 10.1109/ICC45855.2022.9838556ISI: 000864709901164Scopus ID: 2-s2.0-85137263272OAI: oai:DiVA.org:kth-322432DiVA, id: diva2:1719376
Konferanse
IEEE International Conference on Communications (ICC), MAY 16-20, 2022, Seoul, SOUTH KOREA
Merknad

Part of proceedings: ISBN 978-1-5386-8347-7

QC 20221215

Tilgjengelig fra: 2022-12-15 Laget: 2022-12-15 Sist oppdatert: 2022-12-15bibliografisk kontrollert

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Peris, Jaume AngueraFodor, Viktória

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