TY - GEN
T1 - Tutti
T2 - 28th ACM Annual International Conference on Mobile Computing and Networking, MobiCom 2022
AU - Xu, Dongzhu
AU - Zhou, Anfu
AU - Wang, Guixian
AU - Zhang, Huanhuan
AU - Li, Xiangyu
AU - Pei, Jialiang
AU - Ma, Huadong
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/10/14
Y1 - 2022/10/14
N2 - Mobile edge computing (MEC), as a key ingredient of the 5G ecosystem, is envisioned to support demanding applications with stringent latency requirements. The basic idea is to deploy servers close to end-users, e.g., on the network edge-side instead of the remote cloud. While conceptually reasonable, we find that the operational 5G is not coordinated with MEC and thus suffers from intolerable long response latency. In this work, we propose Tutti, which couples 5G RAN and MEC at the user space to assure the performance of latency-critical video analytics. To enable such capacity, Tutti precisely customizes the application service demand by fusing instantaneous wireless dynamics from the 5G RAN and application-layer content changes from edge servers. Tutti then enforces a deadline-sensitive resource provision for meeting the application service demand by real-Time interaction between 5G RAN and edge servers in a lightweight and standard-compatible way. We prototype and evaluate Tutti on a software-defined platform, which shows that Tutti reduces the response latency by an average of 61.69% compared with the existing 5G MEC system, as well as negligible interaction costs.
AB - Mobile edge computing (MEC), as a key ingredient of the 5G ecosystem, is envisioned to support demanding applications with stringent latency requirements. The basic idea is to deploy servers close to end-users, e.g., on the network edge-side instead of the remote cloud. While conceptually reasonable, we find that the operational 5G is not coordinated with MEC and thus suffers from intolerable long response latency. In this work, we propose Tutti, which couples 5G RAN and MEC at the user space to assure the performance of latency-critical video analytics. To enable such capacity, Tutti precisely customizes the application service demand by fusing instantaneous wireless dynamics from the 5G RAN and application-layer content changes from edge servers. Tutti then enforces a deadline-sensitive resource provision for meeting the application service demand by real-Time interaction between 5G RAN and edge servers in a lightweight and standard-compatible way. We prototype and evaluate Tutti on a software-defined platform, which shows that Tutti reduces the response latency by an average of 61.69% compared with the existing 5G MEC system, as well as negligible interaction costs.
KW - 5G
KW - cross-layer performance optimization
KW - latency-critical video analytics
KW - mobile edge computing
KW - proactive resource provision
UR - https://www.scopus.com/pages/publications/85140900300
U2 - 10.1145/3495243.3560538
DO - 10.1145/3495243.3560538
M3 - 会议稿件
AN - SCOPUS:85140900300
T3 - Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM
SP - 729
EP - 742
BT - ACM MobiCom 2022 - Proceedings of the 2022 28th Annual International Conference on Mobile Computing and Networking
PB - Association for Computing Machinery
Y2 - 17 October 2202 through 21 October 2202
ER -