TY - JOUR
T1 - Revisiting Traffic Splitting for Software Switch in Datacenter
AU - Yoo, Yeonho
AU - Yang, Gyeongsik
AU - Shin, Changyong
AU - Cho, Hwiju
AU - Choi, Wonmi
AU - Niu, Zhixiong
AU - Yoo, Chuck
N1 - Publisher Copyright:
© 2025 Copyright held by the owner/author(s)
PY - 2025/5/29
Y1 - 2025/5/29
N2 - Datacenter network topology contains multiple paths between server machines, with each path assigned a weight. Software switches perform traffic splitting, an essential networking operation in datacenters. Previous studies leveraged software switches to distribute network connections across paths, under the assumption that the software switches accurately divide connections according to path weights. However, our experiments reveal that current traffic splitting techniques exhibit significant inaccuracy and resource inefficiency. Consequently, real-world datacenter services (e.g., data mining and deep learning) experience communication completion times that are ∼2.7× longer than the ideal. To address these problems, we propose VALO, a new traffic splitting technique for software switches, to accomplish two goals: high accuracy and resource-efficiency. For the goals, we introduce new concepts: score graph and VALO gravity. We implement VALO using the de-facto software switch, Open vSwitch, and evaluate it thoroughly. On average, VALO achieves 13.1× better accuracy and 25.4× better resource efficiency compared to existing techniques, with maximum improvements reaching up to 34.8× and 67.7×, respectively. As a result, VALO demonstrates 1.3×–2.5× faster average communication completion times for real-world datacenter services compared to existing techniques.
AB - Datacenter network topology contains multiple paths between server machines, with each path assigned a weight. Software switches perform traffic splitting, an essential networking operation in datacenters. Previous studies leveraged software switches to distribute network connections across paths, under the assumption that the software switches accurately divide connections according to path weights. However, our experiments reveal that current traffic splitting techniques exhibit significant inaccuracy and resource inefficiency. Consequently, real-world datacenter services (e.g., data mining and deep learning) experience communication completion times that are ∼2.7× longer than the ideal. To address these problems, we propose VALO, a new traffic splitting technique for software switches, to accomplish two goals: high accuracy and resource-efficiency. For the goals, we introduce new concepts: score graph and VALO gravity. We implement VALO using the de-facto software switch, Open vSwitch, and evaluate it thoroughly. On average, VALO achieves 13.1× better accuracy and 25.4× better resource efficiency compared to existing techniques, with maximum improvements reaching up to 34.8× and 67.7×, respectively. As a result, VALO demonstrates 1.3×–2.5× faster average communication completion times for real-world datacenter services compared to existing techniques.
KW - Cloud
KW - Datacenter
KW - Multipath routing
KW - Software switch
KW - Traffic splitting
UR - https://www.scopus.com/pages/publications/105007141775
U2 - 10.1145/3727131
DO - 10.1145/3727131
M3 - Article
AN - SCOPUS:105007141775
SN - 2476-1249
VL - 9
JO - Proceedings of the ACM on Measurement and Analysis of Computing Systems
JF - Proceedings of the ACM on Measurement and Analysis of Computing Systems
IS - 2
M1 - 39
ER -