TY - GEN
T1 - MECaNIC
T2 - 30th IEEE International Conference on Network Protocols, ICNP 2022
AU - Park, Taejune
AU - You, Myoungsung
AU - Cui, Jian
AU - Jin, Youngjin
AU - Lee, Kilho
AU - Shin, Seungwon
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Multi-access edge computing (MEC) providing server capabilities at near end-users is introduced to enable Ultra Reliable Low Latency Communication (URLLC) for mission-critical and time-sensitive networked services. However, the current MEC simply shortens the physical travel distance of traffic but does not include any architectural approach for supporting URLLC. As a result, MEC implicates resource contention issues, and important packets can be easily delayed or lost, resulting in critical flaws for those services. To address these problems, we introduce MECaNIC, which extends the data plane of MEC to SmartNIC and assists URLLC of MEC. It provides i) precise packet scheduling that handles traffic priorities into two dimensions of reliability and latency, and ii) task offloading that accelerates MEC applications, including payload matching and response caching. The prototype implemented using NetFPGA shows that MECaNIC reduces the average latency of the high-priority traffic from 2,883 mu s to 397 mu s while ensuring packet delivery, even when the traffic competes with other lower priority traffic. Also, task offloading improves a MEC's payload processing 4-fold and reduces file downloading time and video random access time by 44% and 17%, respectively.
AB - Multi-access edge computing (MEC) providing server capabilities at near end-users is introduced to enable Ultra Reliable Low Latency Communication (URLLC) for mission-critical and time-sensitive networked services. However, the current MEC simply shortens the physical travel distance of traffic but does not include any architectural approach for supporting URLLC. As a result, MEC implicates resource contention issues, and important packets can be easily delayed or lost, resulting in critical flaws for those services. To address these problems, we introduce MECaNIC, which extends the data plane of MEC to SmartNIC and assists URLLC of MEC. It provides i) precise packet scheduling that handles traffic priorities into two dimensions of reliability and latency, and ii) task offloading that accelerates MEC applications, including payload matching and response caching. The prototype implemented using NetFPGA shows that MECaNIC reduces the average latency of the high-priority traffic from 2,883 mu s to 397 mu s while ensuring packet delivery, even when the traffic competes with other lower priority traffic. Also, task offloading improves a MEC's payload processing 4-fold and reduces file downloading time and video random access time by 44% and 17%, respectively.
KW - Edge computing
KW - SmartNIC
KW - URLLC
UR - https://www.scopus.com/pages/publications/85142668448
U2 - 10.1109/ICNP55882.2022.9940263
DO - 10.1109/ICNP55882.2022.9940263
M3 - Conference contribution
AN - SCOPUS:85142668448
T3 - Proceedings - International Conference on Network Protocols, ICNP
BT - 2022 IEEE 30th International Conference on Network Protocols, ICNP 2022
PB - IEEE Computer Society
Y2 - 30 October 2022 through 2 November 2022
ER -