A policy conflict detection mechanism for multi-controller software-defined networks. (May 2019)

• Record Type: Journal Article
• Authors: Lu, You; Fu, Qiming; Xi, Xuefeng; Chen, Zhenping; Zou, Encen; Fu, Baochuan
• Is Part Of: International journal of distributed sensor networks. Volume 15:Number 5(2019)
• Publication Date: 2019-05
• Subjects: Flow policy conflict detection -- multi-controller -- software-defined network; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147719844710
• Languages: English
• ISSNs: 1550-1329

Abstract

As the network environment expands and becomes more complex, the deficiencies of decision-making capabilities in the single-controller software-defined network architecture are increasingly exposed. Currently, software-defined networks have gradually adopted a multi-controller-based architecture. However, in this architecture, multiple controllers may cause conflicts in the flow policies, which may cause failures such as security and route conflicts. Most of the existing detection methods are only aimed at specific types of conflicts. Aiming at the above insufficiency, this article proposes a policy conflict detection mechanism for multi-controller software-defined network. First, it quantifies and classifies the software-defined policy conflict itself to provide the basis for detection mechanism; then, it proposes a conflict detection model and its deployment scheme for multi-controller software-defined networks; finally, based on the software-defined flow policy's structure, a multi-branch tree-based policy conflict detection algorithm is proposed to accurately detect the universal types of conflicts. The experimental results under the campus network environment prove that our method can effectively detect the conflict of flow policies existing in the multi-controller software-defined network and has advantages over the existing methods in the integrity, accuracy, and efficiency of the detection.