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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Thyagaraj, Shiva Prakash
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Computer Science & IT Engineering

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Congestion and throughput optimization protocol for providing better quality of service and experience VijayKumar, Sathya; Thyagaraj, Shiva Prakash
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp2364-2373

Abstract

Multimedia traffic in internet of things (IoT) applications is generated for various purposes and encompasses a wide range of multimedia data, including video streams, audio files, images, and sensor data. Network providers employ various strategies to handle multimedia traffic in IoT applications efficiently. But most of these methods have not considered optimizing the real-time streaming protocol (RTSP), real-time transport protocol (RTP), and real-time control protocol (RTCP) to improve the throughput and quality of service (QoS) of the IoT applications. Hence, in this congestion and throughput optimization protocol (CTOP) work, we present a model which optimizes the RTSP, RTP, and RTCP protocol to improve the throughput and QoS. The CTOP model outperforms the big packet protocol model in terms of average throughput, multimedia loss, delay, and energy consumption for both less and high-traffic scenarios. For less-level of traffic and high level of traffic, the CTOP model achieves a better average throughput, and average multimedia delay, reducing the average multimedia loss and average energy consumption in comparison to the existing big-packet-protocol (BBP) model. These results highlight the improved performance and efficiency of the CTOP model compared to the BBP model.
Co-Authors VijayKumar, Sathya