On the Effective Parallelization and Near-Optimal Deployment of Service Function Chains

Network operators compose Service Function Chains (SFCs) by tying different network functions (e.g., packet inspection, flow shaping, network address translation) together and process traffic flows in the order the network functions are chained. Leveraging the technique of Network Function Virtualiz...

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Veröffentlicht in:	IEEE transactions on parallel and distributed systems Jg. 32; H. 5; S. 1238 - 1255
Hauptverfasser:	Luo, Jianzhen, Li, Jun, Jiao, Lei, Cai, Jun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.05.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Approximation algorithms Chains deployment Dynamic programming Hardware Heuristic algorithms Inspection Network function virtualization Network latency Operators (mathematics) Parallel processing parallelization Quality of service Servers service function chain Traffic congestion Traffic flow Virtual networks
ISSN:	1045-9219, 1558-2183
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Abstract	Network operators compose Service Function Chains (SFCs) by tying different network functions (e.g., packet inspection, flow shaping, network address translation) together and process traffic flows in the order the network functions are chained. Leveraging the technique of Network Function Virtualization (NFV), each network function can be "virtualized" and decoupled from its dedicated hardware, and therefore can be deployed flexibly for better performance at any appropriate location of the underlying network infrastructure. However, an SFC often incurs high latency as traffic goes through the virtual network functions one after another. In this article, we first design an algorithm that leverages virtual network function dependency to convert an original SFC into a parallelized SFC (p-SFC). Then, to deploy multiple p-SFCs over the network for serving a large number of users, we model the deployment problem as an Integer Linear Program and propose a heuristic, ParaSFC, based on the Viterbi dynamic programming algorithm to estimate each p-SFC's occupation of the bottleneck resources and adjust the processing order of the p-SFCs in order to approximate the optimal solution. Finally, we conduct extensive trace-driven evaluations and exhibit that, compared to the Greedy method and the state-of-the-art CoordVNF method, ParaSFC reduces the average service latency of all the deployed p-SFCs by about 15 percent through parallelization while accommodating more SFC deployment requests over resource-limited networks.
AbstractList	Network operators compose Service Function Chains (SFCs) by tying different network functions (e.g., packet inspection, flow shaping, network address translation) together and process traffic flows in the order the network functions are chained. Leveraging the technique of Network Function Virtualization (NFV), each network function can be “virtualized” and decoupled from its dedicated hardware, and therefore can be deployed flexibly for better performance at any appropriate location of the underlying network infrastructure. However, an SFC often incurs high latency as traffic goes through the virtual network functions one after another. In this article, we first design an algorithm that leverages virtual network function dependency to convert an original SFC into a parallelized SFC (p-SFC). Then, to deploy multiple p-SFCs over the network for serving a large number of users, we model the deployment problem as an Integer Linear Program and propose a heuristic, ParaSFC, based on the Viterbi dynamic programming algorithm to estimate each p-SFC’s occupation of the bottleneck resources and adjust the processing order of the p-SFCs in order to approximate the optimal solution. Finally, we conduct extensive trace-driven evaluations and exhibit that, compared to the Greedy method and the state-of-the-art CoordVNF method, ParaSFC reduces the average service latency of all the deployed p-SFCs by about 15 percent through parallelization while accommodating more SFC deployment requests over resource-limited networks.
Author	Li, Jun Luo, Jianzhen Jiao, Lei Cai, Jun
Author_xml	– sequence: 1 givenname: Jianzhen orcidid: 0000-0002-5123-1306 surname: Luo fullname: Luo, Jianzhen email: luojz@gpnu.edu.cn organization: School of Cyber Security, Guangdong Polytechnic Normal University, Guangzhou, China – sequence: 2 givenname: Jun orcidid: 0000-0002-5308-5672 surname: Li fullname: Li, Jun email: lijun@cs.uoregon.edu organization: Department of Computer and Information Science, University of Oregon, Eugene, OR, USA – sequence: 3 givenname: Lei orcidid: 0000-0002-3964-3172 surname: Jiao fullname: Jiao, Lei email: jiao@cs.uoregon.edu organization: Department of Computer and Information Science, University of Oregon, Eugene, OR, USA – sequence: 4 givenname: Jun orcidid: 0000-0003-1695-483X surname: Cai fullname: Cai, Jun email: caijun@gpnu.edu.cn organization: School of Cyber Security, Guangdong Polytechnic Normal University, Guangzhou, China
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SubjectTerms	Algorithms Approximation algorithms Chains deployment Dynamic programming Hardware Heuristic algorithms Inspection Network function virtualization Network latency Operators (mathematics) Parallel processing parallelization Quality of service Servers service function chain Traffic congestion Traffic flow Virtual networks
Title	On the Effective Parallelization and Near-Optimal Deployment of Service Function Chains
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