International Journal of Computer Networks and Applications

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Dynamic Path Selection Based Video Transmission in User Preference Assisted Adaptive Rate Control in 5G Multi-RAT Network


Affiliations
1 Department of Computer Science and Engineering, JNT University, Anantapuram, Andhra Pradesh, India
2 Department of Computer Science and Engineering, G. Pulla Reddy Engineering College Kurnool, Andhra Pradesh, India
 

5G mobile users consume a large amount of video content. Providing high-quality video to mobile users via a single path is a challenging task. It takes much time to transmit the video. In this paper, we proposed dynamic path selection-based video transmission is proposed for a 5G multi-RAT network. In our proposed system has four consecutive processes, which are discussed as follows: (1) Optimal access point selection which is done by Red Deer Algorithm (RDA) that selects optimal access point by considering data rate, Signal to Inference Noise Ratio (SINR) and Received Signal Strength Indicator(RSSI) to achieve better Quality of Experience (QoE). (2) Adaptive Video Encoding, for this purpose, we useH.265 encoding algorithm, which encodes the video packets in order to reduce transmission time and bandwidth consumption, here bit rate is adaptively controlled using the SARSA reinforcement algorithm, by considering the network environment factors ( bit error rate, attenuation, bandwidth, throughput, and SNR) and user preference factors (high/low quality and processing speed). In this stage, the SWARA decision-making algorithm is used to select optimal QP parameters for each video packet, which considers three parameters: distortion, previous QP value, and CSI, which improves the quality of the video. (3). Dynamic path selection is made using the Deng-based Type 2 Fuzzy algorithm (Deng-T2F), which selects the optimal path between source and destination based on the following parameters: the number of hops, link stability, and buffer size increases high throughput and reduce transmission delay. (4). Adaptive Buffer Management is proposed for reducing latency during video transmission. The Adaptive Pre-order Deficit Round Robin (ADPDRR) algorithm is used to evaluate the parameters of layer information, deadline, packet size, and arrival time to reduce packet loss and packet waiting time during video transmission. The proposed APDRR algorithm maintains three queues based on the packet priority, and then the prioritized packets are transmitted adaptively to reduce the packet waiting time. Finally, simulation is conducted using an NS-3.26 network simulator that evaluates the performance based on the following metrics: PSNR, MoS, bandwidth utilization, jitter, Throughput, Delay, Packet drop rate, and Goodput.

Keywords

Dynamic Path Selection, 5G-Multi-RAT, Red Deer Algorithm, SARSA, SWARA Decision Making, Adaptive Buffer Management.
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  • Dynamic Path Selection Based Video Transmission in User Preference Assisted Adaptive Rate Control in 5G Multi-RAT Network

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Authors

M. Muni Babu
Department of Computer Science and Engineering, JNT University, Anantapuram, Andhra Pradesh, India
R. Praveen Sam
Department of Computer Science and Engineering, G. Pulla Reddy Engineering College Kurnool, Andhra Pradesh, India
P. Chenna Reddy
Department of Computer Science and Engineering, JNT University, Anantapuram, Andhra Pradesh, India

Abstract


5G mobile users consume a large amount of video content. Providing high-quality video to mobile users via a single path is a challenging task. It takes much time to transmit the video. In this paper, we proposed dynamic path selection-based video transmission is proposed for a 5G multi-RAT network. In our proposed system has four consecutive processes, which are discussed as follows: (1) Optimal access point selection which is done by Red Deer Algorithm (RDA) that selects optimal access point by considering data rate, Signal to Inference Noise Ratio (SINR) and Received Signal Strength Indicator(RSSI) to achieve better Quality of Experience (QoE). (2) Adaptive Video Encoding, for this purpose, we useH.265 encoding algorithm, which encodes the video packets in order to reduce transmission time and bandwidth consumption, here bit rate is adaptively controlled using the SARSA reinforcement algorithm, by considering the network environment factors ( bit error rate, attenuation, bandwidth, throughput, and SNR) and user preference factors (high/low quality and processing speed). In this stage, the SWARA decision-making algorithm is used to select optimal QP parameters for each video packet, which considers three parameters: distortion, previous QP value, and CSI, which improves the quality of the video. (3). Dynamic path selection is made using the Deng-based Type 2 Fuzzy algorithm (Deng-T2F), which selects the optimal path between source and destination based on the following parameters: the number of hops, link stability, and buffer size increases high throughput and reduce transmission delay. (4). Adaptive Buffer Management is proposed for reducing latency during video transmission. The Adaptive Pre-order Deficit Round Robin (ADPDRR) algorithm is used to evaluate the parameters of layer information, deadline, packet size, and arrival time to reduce packet loss and packet waiting time during video transmission. The proposed APDRR algorithm maintains three queues based on the packet priority, and then the prioritized packets are transmitted adaptively to reduce the packet waiting time. Finally, simulation is conducted using an NS-3.26 network simulator that evaluates the performance based on the following metrics: PSNR, MoS, bandwidth utilization, jitter, Throughput, Delay, Packet drop rate, and Goodput.

Keywords


Dynamic Path Selection, 5G-Multi-RAT, Red Deer Algorithm, SARSA, SWARA Decision Making, Adaptive Buffer Management.

References





DOI: https://doi.org/10.22247/ijcna%2F2021%2F209984