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New Alternatives to Optimize Policy Classifiers

Demianiuk, Vitalii and Nikolenko, Sergey and Chuprikov, Pavel and Kogan, Kirill (2020) New Alternatives to Optimize Policy Classifiers. [Journal Articles]

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Abstract

Growing expressiveness of services increases the size of a manageable state at the network data plane. A service policy is an ordered set of classification patterns (classes) with actions; the same class can appear in multiple policies. Previous studies mostly concentrated on efficient representations of a single policy instance. In this work, we study space efficiency of multiple policies, cutting down a classifier size by sharing instances of classes between policies that contain them. In this paper we identify conditions for such sharing, propose efficient algorithms and analyze them analytically. The proposed representations can be deployed transparently on existing packet processing engines. Our results are supported by extensive evaluations.

Item Type: Journal Articles
Uncontrolled Keywords: Heuristic algorithms, Complexity theory, Quality of service, Biological system modeling, Approximation algorithms, IEEE transactions, Economics.
Subjects: UNSPECIFIED
Divisions: UNSPECIFIED
Depositing User: Rebeca De Miguel
Date Deposited: 10 Nov 2020 13:57
Last Modified: 10 Nov 2020 13:57
URI: http://eprints.networks.imdea.org/id/eprint/2218

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