On the Design of Resource Allocation Algorithms for Low-Latency Video Analytics

Victor Valls, Heesung Kwon, Thomas F. La Porta, Sebastian Stein, Leandros Tassiulas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we study how to design resource allocation algorithms for data analytics services that are computationally intensive and have low-latency requirements. As a paradigm application, we consider a video surveillance service where video streams are analyzed in the cloud with deep-learning algorithms (i.e., object detection and image classification). We present a network model that allows data analytics tasks to be processed in multiple stages, and propose an algorithm that provides low congestion when the arrival rate is constant over time. The algorithm also allows other types of data analytics to be carried out in the cloud in order to maximize resource utilization. The performance of the proposed algorithm is evaluated using simulation, and our results show that it is possible to obtain low-delay while maximizing the use of network resources.

Original languageEnglish (US)
Title of host publication2018 IEEE Military Communications Conference, MILCOM 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages468-473
Number of pages6
ISBN (Electronic)9781538671856
DOIs
StatePublished - Jan 2 2019
Event2018 IEEE Military Communications Conference, MILCOM 2018 - Los Angeles, United States
Duration: Oct 29 2018Oct 31 2018

Publication series

NameProceedings - IEEE Military Communications Conference MILCOM
Volume2019-October

Conference

Conference2018 IEEE Military Communications Conference, MILCOM 2018
CountryUnited States
CityLos Angeles
Period10/29/1810/31/18

Fingerprint

Resource allocation
Image classification
Learning algorithms

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Valls, V., Kwon, H., La Porta, T. F., Stein, S., & Tassiulas, L. (2019). On the Design of Resource Allocation Algorithms for Low-Latency Video Analytics. In 2018 IEEE Military Communications Conference, MILCOM 2018 (pp. 468-473). [8599750] (Proceedings - IEEE Military Communications Conference MILCOM; Vol. 2019-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MILCOM.2018.8599750
Valls, Victor ; Kwon, Heesung ; La Porta, Thomas F. ; Stein, Sebastian ; Tassiulas, Leandros. / On the Design of Resource Allocation Algorithms for Low-Latency Video Analytics. 2018 IEEE Military Communications Conference, MILCOM 2018. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 468-473 (Proceedings - IEEE Military Communications Conference MILCOM).
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Valls, V, Kwon, H, La Porta, TF, Stein, S & Tassiulas, L 2019, On the Design of Resource Allocation Algorithms for Low-Latency Video Analytics. in 2018 IEEE Military Communications Conference, MILCOM 2018., 8599750, Proceedings - IEEE Military Communications Conference MILCOM, vol. 2019-October, Institute of Electrical and Electronics Engineers Inc., pp. 468-473, 2018 IEEE Military Communications Conference, MILCOM 2018, Los Angeles, United States, 10/29/18. https://doi.org/10.1109/MILCOM.2018.8599750

On the Design of Resource Allocation Algorithms for Low-Latency Video Analytics. / Valls, Victor; Kwon, Heesung; La Porta, Thomas F.; Stein, Sebastian; Tassiulas, Leandros.

2018 IEEE Military Communications Conference, MILCOM 2018. Institute of Electrical and Electronics Engineers Inc., 2019. p. 468-473 8599750 (Proceedings - IEEE Military Communications Conference MILCOM; Vol. 2019-October).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Valls V, Kwon H, La Porta TF, Stein S, Tassiulas L. On the Design of Resource Allocation Algorithms for Low-Latency Video Analytics. In 2018 IEEE Military Communications Conference, MILCOM 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 468-473. 8599750. (Proceedings - IEEE Military Communications Conference MILCOM). https://doi.org/10.1109/MILCOM.2018.8599750