TY - GEN
T1 - An Edge Network Orchestrator for Mobile Augmented Reality
AU - Liu, Qiang
AU - Huang, Siqi
AU - Opadere, Johnson
AU - Han, Tao
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/8
Y1 - 2018/10/8
N2 - Mobile augmented reality (MAR) involves high complexity computation which cannot be performed efficiently on resource limited mobile devices. The performance of MAR would be significantly improved by offloading the computation tasks to servers deployed with the close proximity to the users. In this paper, we design an edge network orchestrator to enable fast and accurate object analytics at the network edge for MAR. The measurement-based analytical models are built to characterize the tradeoff between the service latency and analytics accuracy in edge-based MAR systems. As a key component of the edge network orchestrator, a server assignment and frame resolution selection algorithm named FACT is proposed to mitigate the latency-accuracy tradeoff. Through network simulations, we evaluate the performance of the FACT algorithm and show the insights on optimizing the performance of edge-based MAR systems. We have implemented the edge network orchestrator and developed the corresponding communication protocol. Our experiments validate the performance of the proposed edge network orchestrator.
AB - Mobile augmented reality (MAR) involves high complexity computation which cannot be performed efficiently on resource limited mobile devices. The performance of MAR would be significantly improved by offloading the computation tasks to servers deployed with the close proximity to the users. In this paper, we design an edge network orchestrator to enable fast and accurate object analytics at the network edge for MAR. The measurement-based analytical models are built to characterize the tradeoff between the service latency and analytics accuracy in edge-based MAR systems. As a key component of the edge network orchestrator, a server assignment and frame resolution selection algorithm named FACT is proposed to mitigate the latency-accuracy tradeoff. Through network simulations, we evaluate the performance of the FACT algorithm and show the insights on optimizing the performance of edge-based MAR systems. We have implemented the edge network orchestrator and developed the corresponding communication protocol. Our experiments validate the performance of the proposed edge network orchestrator.
UR - http://www.scopus.com/inward/record.url?scp=85056190134&partnerID=8YFLogxK
U2 - 10.1109/INFOCOM.2018.8486241
DO - 10.1109/INFOCOM.2018.8486241
M3 - Conference Proceeding
AN - SCOPUS:85056190134
T3 - Proceedings - IEEE INFOCOM
SP - 756
EP - 764
BT - INFOCOM 2018 - IEEE Conference on Computer Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Conference on Computer Communications, INFOCOM 2018
Y2 - 15 April 2018 through 19 April 2018
ER -