An adaptive type-2 fuzzy traffic engineering method for video surveillance systems over software defined networks

Abstract

Software Defined Network (SDN) is a new network technology which allows network providers to afford predefined Quality of Service (QoS) for video streaming applications. Network administrators can develop desired traffic engineering techniques over SDN and support Quality of Experience (QoE) and QoS for their customers. One of the most important issues in traffic engineering is to find favorable links for routing between source and destination. The fitness of each link in the network depends on the end users QoE and the applications they are used. In this paper to achieve optimal routes, the fitness of each link is determined by type-2 fuzzy sets. Then, an adaptive traffic engineering method is proposed to find the best routes between source cameras and monitoring center in a video surveillance system. The proposed method is based on Constraint Shortest Path (CSP) problem and calculates minimum cost path which satisfies delay constraint. Due to NP-completeness of the CSP problems, LARAC algorithm is used to solve it. To the best of our knowledge, this is the first proposed traffic engineering technique which is based on type-2 fuzzy set for video streaming applications over SDN. The contribution of the proposed method regarding to the related works, is to apply type-2 and type-1 fuzzy logic for calculating the costs of network links based on QoE for providing QoS in a video surveillance system. In addition, this paper models the provisioning of QoS in a real scenario and emulates them in a network emulator. Many comparisons carried out between the proposed method and other well-known methods to show the effectiveness of the proposed method in terms of packet loss, delay and PSNR.