LAVEA: Latency-Aware Video Analytics on Edge Computing Platform

We present LAVEA, a system built for edge computing, which offloads computation tasks between clients and edge nodes, collaborates nearby edge nodes, to provide low-latency video analytics at places closer to the users. We have utilized an edge-first design to minimize the response time, and compare...

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Vydáno v:Proceedings of the International Conference on Distributed Computing Systems s. 2573 - 2574
Hlavní autoři: Shanhe Yi, Zijiang Hao, Qingyang Zhang, Quan Zhang, Weisong Shi, Qun Li
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.06.2017
Témata:
Bandwidth
Cloud computing
Collaboration
computation offloading
Containers
Edge computing
fog computing
Servers
Time factors
ISSN:1063-6927
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Popis
Shrnutí:We present LAVEA, a system built for edge computing, which offloads computation tasks between clients and edge nodes, collaborates nearby edge nodes, to provide low-latency video analytics at places closer to the users. We have utilized an edge-first design to minimize the response time, and compared various task placement schemes tailed for inter-edge collaboration. Our results reveal that the client-edge configuration has task speedup against local or client-cloud configurations.
ISSN:1063-6927
DOI:10.1109/ICDCS.2017.182