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...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on parallel and distributed systems Vol. 32; no. 5; pp. 1238 - 1255
Main Authors: Luo, Jianzhen, Li, Jun, Jiao, Lei, Cai, Jun
Format: Journal Article
Language:English
Published: New York IEEE 01.05.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
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
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2020.3043768