Next Article in Journal
Residual Motion Error Correction with Backprojection Multisquint Algorithm for Airborne Synthetic Aperture Radar Interferometry
Next Article in Special Issue
Slice Management for Quality of Service Differentiation in Wireless Network Slicing
Previous Article in Journal
Distance-Based Paper Device Combined with Headspace Extraction for Determination of Cyanide
Previous Article in Special Issue
A Hybrid Method for Mobile Agent Moving Trajectory Scheduling using ACO and PSO in WSNs
Article Menu
Issue 10 (May-2) cover image

Export Article

Open AccessArticle

Entry Aggregation and Early Match Using Hidden Markov Model of Flow Table in SDN

1
Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea
2
College of Software, Sungkyunkwan University, Suwon 16419, Korea
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(10), 2341; https://doi.org/10.3390/s19102341
Received: 3 April 2019 / Revised: 13 May 2019 / Accepted: 17 May 2019 / Published: 21 May 2019
  |  
PDF [3697 KB, uploaded 21 May 2019]
  |  

Abstract

The usage of multiple flow tables (MFT) has significantly extended the flexibility and applicability of software-defined networking (SDN). However, the size of MFT is usually limited due to the use of expensive ternary content addressable memory (TCAM). Moreover, the pipeline mechanism of MFT causes long flow processing time. In this paper a novel approach called Agg-ExTable is proposed to efficiently manage the MFT. Here the flow entries in MFT are periodically aggregated by applying pruning and the Quine–Mccluskey algorithm. Utilizing the memory space saved by the aggregation, a front-end ExTable is constructed, keeping popular flow entries for early match. Popular entries are decided by the Hidden Markov model based on the match frequency and match probability. Computer simulation reveals that the proposed scheme is able to save about 45% of space of MFT, and efficiently decrease the flow processing time compared to the existing schemes. View Full-Text
Keywords: SDN; entry aggregation; Quine–McCluskey Algorithm; match frequency and probability; Hidden Markov Model SDN; entry aggregation; Quine–McCluskey Algorithm; match frequency and probability; Hidden Markov Model
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Wang, C.; Youn, H.Y. Entry Aggregation and Early Match Using Hidden Markov Model of Flow Table in SDN. Sensors 2019, 19, 2341.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top