Skip to Main content Skip to Navigation
Conference papers

Labeled Network Stack: A Co-designed Stack for Low Tail-Latency and High Concurrency in Datacenter Services

Abstract : Many Internet, mobile Internet, and IoT services require both low tail-latency and high concurrency in datacenters. The current protocol stack design pays more attention to throughput and average performance, considering little on tail latency and priority. We address this question by proposing a hardware-software co-designed Labeled Network Stack (LNS) for future datacenters. The key innovation is a payload labeling mechanism that distinguishes data packets in a TCP link across the full network stack, including the application, the TCP/IP and the Ethernet layer. This design enables prioritized data packets processing and forwarding along the full data path, to reduce the tail latency of critical requests. We built a prototype datacenter server to evaluate the LNS design against a standard Linux kernel stack and the mTCP research, using IoT kernel benchmark MCC. Experiment results show that the LNS design can provide an order of magnitude improvement on tail latency and concurrency.
Document type :
Conference papers
Complete list of metadata

Cited literature [7 references]  Display  Hide  Download

https://hal.inria.fr/hal-02279543
Contributor : Hal Ifip <>
Submitted on : Thursday, September 5, 2019 - 1:30:42 PM
Last modification on : Thursday, September 5, 2019 - 1:35:36 PM
Long-term archiving on: : Thursday, February 6, 2020 - 5:20:48 AM

File

477597_1_En_12_Chapter.pdf
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Wenli Zhang, Ke Liu, Hui Song, Lan Yu, Mingyu Chen. Labeled Network Stack: A Co-designed Stack for Low Tail-Latency and High Concurrency in Datacenter Services. 15th IFIP International Conference on Network and Parallel Computing (NPC), Nov 2018, Muroran, Japan. pp.132-136, ⟨10.1007/978-3-030-05677-3_12⟩. ⟨hal-02279543⟩

Share

Metrics

Record views

46

Files downloads

18