Premium
A parallel approach for detecting OpenFlow rule anomalies based on a general formalism
Author(s) -
Aryan Ramtin,
Yazidi Anis,
Kure Øivind,
Einar Engelstad Paal
Publication year - 2020
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.5907
Subject(s) - openflow , computer science , troubleshooting , pace , data mining , anomaly detection , formalism (music) , process (computing) , distributed computing , set (abstract data type) , matching (statistics) , software defined networking , operating system , programming language , art , musical , statistics , mathematics , geodesy , visual arts , geography
Summary As the policies of a software‐defined networking (SDN) network can be updated dynamically and often at a high pace, conflicts between policies can easily occur. Due to the large number of switches and heterogeneous policies within a typical SDN network, detecting those conflicts is a laborious and challenging task. This article presents three main contributions. First, we devise an offline method for detecting unmatched OpenFlow rules, that is, rules that are never fired. In our taxonomy such anomalies can stem from either invalid or irrelevant unmatched rules. Second, we introduce a new set of definitions for the intraanomalies between rules in the same table, which might occur when using the multiaction feature of an OpenFlow rule. Third, our detection method has been enhanced to support parallel execution, which makes it a viable solution for troubleshooting large‐scale networks. We provide some comprehensive experimental results based on both synthetic and real‐life setup the synthetic set up is designed in such a way that the rule matching takes place in the last rules of the switch and thus putting more stress on the rule detection process. The parallel method is shown to outperform the single‐threaded checking method by order of magnitude up to 21.