Autonomous framework simulation tools for real-time multimedia streaming over wireless ad-hoc networks. (February 2020)

• Record Type: Journal Article
• Authors: Ahmed, Adel A; Barukab, Omar
• Is Part Of: Simulation. Volume 96:Number 2(2020)
• Page Start: 185
• Page End: 197
• Publication Date: 2020-02
• Subjects: Autonomous simulation tool -- quality of service -- peak signal-to-noise ratio; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/0037549719859065
• Languages: English
• ISSNs: 0037-5497

Abstract

Real-time video communication has become one of the most significant applications extensively used by homogeneous/heterogeneous wireless network technologies, such as Wi-Fi, the Internet of things, the wireless sensor network (WSN), 5G, etc. This leads to enhanced deployment of multimedia streaming applications over wireless network technologies. In order to accomplish the optimal performance of real-time multimedia streaming applications over the homogeneous/heterogeneous wireless network, it is therefore necessary to develop a simulation tool-set that effectively measures the quality of service (QoS) for different multimedia streaming applications over transport layer protocols. This paper proposes an autonomous simulation tool (AST) that is entirely independent from the source code of transport layer protocols. Furthermore, the AST is integrated into NS-2 to evaluate the QoS of real-time video streaming over numerous transport layer protocols and it uses new QoS measurement tools to test the video delivery quality based on I-frames to speeds up the assessment of multimedia streaming quality and ensure high accuracy of performance metrics. The simulation results show that using the AST to simulate real-time multimedia stream results in between 13% and 36% higher delivery ratio and 150–250% less cumulative jitter delay compared with using baseline simulation tools. Also, the AST guarantees an optimal QoS performance measurements in terms of the peak signal-to-noise Ratio and visual quality of the received video.