Title: An intelligent traffic engineering method for video surveillance systems over software defined networks using ant colony optimisation
Authors: Reza Mohammadi; Reza Javidan; Manijeh Keshtgari
Addresses: Department of Computer Engineering and Information Technology, Shiraz University of Technology, Shiraz, Iran ' Department of Computer Engineering and Information Technology, Shiraz University of Technology, Shiraz, Iran ' Department of Computer Engineering and Information Technology, Shiraz University of Technology, Shiraz, Iran
Abstract: Nowadays, software defined network (SDN) is an innovative technology for provisioning quality of service (QoS) requirements. SDN network management facilitated using software in which network administrator can perform desired traffic engineering techniques on different applications. Video streaming in video surveillance systems is a critical application which needs QoS requirements such as low packet loss and short delay. These requirements can be satisfied by using traffic engineering techniques over SDNs. In this paper, an intelligent traffic engineering technique for a video surveillance system over SDN is proposed. It is based on constrained shortest path (CSP) problem in which the packet loss and delay of video streaming data should be significantly reduced. Due to NP-completeness of the CSP problems, in this paper, ant colony optimisation algorithm is used to solve it. To the best of our knowledge, this is the first traffic engineering technique used ant colony for video streaming over SDN. Comparisons between the proposed method and prevalent methods such as OSPF routing protocol and LARAC optimisation algorithm demonstrated the effectiveness of the proposed method in terms of packet loss, delay and peak signal-to-noise ratio (PSNR). It was shown that using the proposed method will also ameliorate the traffic engineering for video surveillance systems.
Keywords: software defined network; SDN; ant colony; traffic engineering; video streaming.
International Journal of Bio-Inspired Computation, 2018 Vol.12 No.3, pp.173 - 185
Received: 03 Jul 2016
Accepted: 08 May 2017
Published online: 04 Sep 2018 *