TY - GEN
T1 - On the Design of Resource Allocation Algorithms for Low-Latency Video Analytics
AU - Valls, Victor
AU - Kwon, Heesung
AU - Laporta, Tom
AU - Stein, Sebastian
AU - Tassiulas, Leandros
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85061434722&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85061434722&partnerID=8YFLogxK
U2 - 10.1109/MILCOM.2018.8599750
DO - 10.1109/MILCOM.2018.8599750
M3 - Conference contribution
AN - SCOPUS:85061434722
T3 - Proceedings - IEEE Military Communications Conference MILCOM
SP - 468
EP - 473
BT - 2018 IEEE Military Communications Conference, MILCOM 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Military Communications Conference, MILCOM 2018
Y2 - 29 October 2018 through 31 October 2018
ER -