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Status已发表Published
TitleCompiling Service Function Chains via Fine-Grained Composition in the Programmable Data Plane
Creator
Date Issued2023-07-01
Source PublicationIEEE Transactions on Services Computing
ISSN1939-1374
Volume16Issue:4Pages:2490-2502
Abstract

Service function chains (SFCs) are fundamental services in today's datacenters and ISP networks. Explosive volume of network traffic creates high demands for low latency and high performance. The emergence of programmable data planes has offered a new way to overcome the problem. However, limited by pipeline constraints in hardware architecture, implementing multiple network functions on programmable data planes is challenging. Besides, considering various types of network functions, e.g., stateful network functions, a general model is essential for abstracting distinct network functions. In this article, we propose pSFC which provides a fine-grained SFCs deployment scheme in programmable data planes. Control flow graph (CFG) is proposed to abstract and analyze various network functions. Then we model pipeline constraints in the hardware architecture using an ILP (Integer Linear Programming), and model the SFCs deployment in the substrate network as a one big switch (OBS) problem. To reduce deployment cost, pSFC first composes multiple SFCs to a compound CFG for eliminating redundant logics within SFCs, further decomposes the compound CFG based on the resource limitation per stage, and finally maps the OBS into the substrate network. We have implemented pSFC in both bmv2 software switch and P4 hardware switch (i.e., Intel Tofino ASIC). Evaluation results show that pSFC reduces switch costs by 45.7% and decreases average latency by 22% without compromising throughput.

Keywordone big switch P4 programmable data plane service function chains
DOI10.1109/TSC.2023.3242072
URLView source
Indexed BySCIE
Language英语English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering
WOS IDWOS:001045785600014
Scopus ID2-s2.0-85149408157
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/10782
CollectionFaculty of Science and Technology
Corresponding AuthorCui, Lin
Affiliation
1.Jinan University,Guangdong Provincial Key Laboratory of Data Security and Privacy Protection,Department of Computer Science,Guangzhou,510632,China
2.Loughborough University,Department of Computer Science,Loughborough,LE11 3TU,United Kingdom
3.Beijing Normal University (BNU Zhuhai),BNU-UIC Institute of Artificial Intelligence and Future Networks,Zhuhai,519088,China
4.BNU-HKBU United International College,Zhuhai,519088,China
Recommended Citation
GB/T 7714
Zhang, Xiaoquan,Cui, Lin,Tso, Fung Poet al. Compiling Service Function Chains via Fine-Grained Composition in the Programmable Data Plane[J]. IEEE Transactions on Services Computing, 2023, 16(4): 2490-2502.
APA Zhang, Xiaoquan, Cui, Lin, Tso, Fung Po, & Jia, Weijia. (2023). Compiling Service Function Chains via Fine-Grained Composition in the Programmable Data Plane. IEEE Transactions on Services Computing, 16(4), 2490-2502.
MLA Zhang, Xiaoquan,et al."Compiling Service Function Chains via Fine-Grained Composition in the Programmable Data Plane". IEEE Transactions on Services Computing 16.4(2023): 2490-2502.
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