An efficient congestion control in multimedia streaming using adaptive BRR and fuzzy butterfly optimization

Abstract

Recently, various video streaming platforms such as YouTube, Netflix and so forth have achieved great growth in the media industry. However, uncertain dynamic activities such as low bandwidth, packet loss and rapid fluctuations, quality, and interrupted flow are still creating several complications in multimedia streaming applications and it is necessary to provide enhanced throughput and minimum frame delivery delay. Therefore, the significant objective of this article is to attain enhanced bandwidth allocation as well as a high packet scheduling rate. In this article, an adaptive BBR technique is proposed for transmitting real‐time video with minimum transmission delay and packet loss. The adaptive BBR mainly uses the pacing gain update mechanism to maintain different flow rates and minimal data in the bottleneck queue. Also, a fuzzy butterfly optimization (FBO) with a ranking strategy is proposed to attain optimal bandwidth allocation. The FBO algorithm with ranking strategy computes the minimal bandwidth needed by the model to satisfy the service requirement of every queue in a particular round. Then, the packet scheduling is done by employing an intelligent time slice‐based round‐robin (ITSBRR) technique. The ITSBRR algorithm is employed to enhance the throughput and end‐to‐end delay by implementing the time quantum‐based scheduling mechanism. Finally, the experimental analysis is carried out for various parameters namely single path transmission delay, packet loss; frame delay is computed for various techniques to compute the efficiency of the proposed system.