A Q-Learning Driven Energy-Aware Multipath Transmission Solution for 5G Media Services

Zhong, Lujie; Xiang, Ji; Wang, Zhaoxue; Qin, Jiuren; Muntean, Gabriel‐Miro

doi:10.1109/tbc.2022.3147098

Cited by 12 publications

(6 citation statements)

References 45 publications

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“…e multipath transmission protocol must ensure that all active pathways are fully functional. If the communication quality of a particular way suddenly deteriorates, packets assigned to that path will be delayed or lost, lowering the overall throughput [30,31]. To circumvent this, the MP layer should label the low-quality link as inactive, and no packets should be scheduled to inactive pathways.…”

Section: Resultsmentioning

confidence: 99%

A Novel Analytical Framework Is Developed for Wireless Heterogeneous Networks for Video Streaming Applications

Kumarganesh¹,

Anthoniraj

Kumar³

et al. 2022

Journal of Mathematics

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Due to bandwidth and time limits, delivering high-quality video streaming facility offers real-time wireless networks, but assuring quality of experience (QoE) is rather difficult. A network host can deliver its data stream via numerous different network pathways. At the same time, using multipath data transmission, where video streaming may be supplied through Internet protocols (IPs) as well as broadband with bidirectional communication between video sources and consumers, is one way to address this difficult problem. In this work, a novel framework is developed for wireless heterogeneous networks for video streaming applications using concurrent multipath transfer (CMT). The performance of frame-level delay can be enhanced for better video quality using this proposed method. The network congestion on end-to-end path utilised in CMT is not dependent of one another, and we operate under prior assumption that receiver’s announced window does not limit the sender. The analytical results show that the proposed framework outperforms existing methods in terms of performance with minimum retransmission delay.

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Section: Resultsmentioning

confidence: 99%

A Novel Analytical Framework Is Developed for Wireless Heterogeneous Networks for Video Streaming Applications

Kumarganesh¹,

Anthoniraj

Kumar³

et al. 2022

Journal of Mathematics

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“…Several recent studies attempts to apply the machine learning method to deal with the high dynamic network conditions when adaptively streaming the video content. For example, in [18], a Q-learning model is applied to generate adaptive streaming schemes for 5G multimedia services with the aim to preserve both energy efficiency and user QoE. TCLiVi in [19] applies the deep reinforcement learning to control the bitrate selection for adaptive streaming.…”

Section: B Related Workmentioning

confidence: 99%

“…Link l receives the x i,j (t) of all users that use l and select max j∈s i (u) l x i,j (t) as x l i (t) for each source s in l(s). Then, l uses all x l k ,k ∈ l(s)/i and x i,j to compute the λ l (t + 1) and υ l (t + 1) by ( 17), (18). The derived λ l (t + 1), υ l (t + 1) will be delivered to user j for computing the new x i,j (t + 1) in the next iteration.…”

Section: B Distributed Optimal Rate Adaptation Algorithmmentioning

confidence: 99%

Decentralized Optimization for Multicast Adaptive Video Streaming in Edge Cache-Assisted Networks

Zhong

Wang

et al. 2023

IEEE Trans. on Broadcast.

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Adaptive streaming based on DASH offers personalized video experience and smooth playback by allowing dynamical adjustments of the video bitrate to the variations of network conditions. This is especially important for current and future Internet video streaming applications, including emerging ones such as virtual reality-based, as adaptive streaming plays a key role in providing high quality viewing experience, especially in limited bandwidth delivery environments. To enable this promising avenue in a 5G context, efforts are made to consider it alongside multicast and edge caching, as part of the next generation communication technology. In this paper, we model the adaptive streaming transmission problem in a mobile scenario as a multi-source multicast multi-rate problem (MMMP) whose linear relaxation is concave. We decompose the problem in terms of clients and propose the distributed delivery algorithm (DDA). The computation complexity, convergence and time-varying adaptation of DDA are theoretically analyzed. Additionally, to further reduce the computation complexity of the solution, a heuristic approximation method (H-DDA) based on the physical meaning of the problem is proposed and it is also shown how H-DDA converges to the optimal value by numerical means. Finally, we conduct a series of simulation tests to demonstrate the superiority of the proposed HDDA in comparison with other state-of-art solutions.

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“…on mobile and fixed networks. These solutions use a wide range of approaches from classic optimization techniques [21] to innovative methods such as machine learning [22]. More recently many efforts were put to design adaptive streaming solutions which target non-traditional content, including 4K/8K, 360 • [23] and multisensorial [9] and innovative settings, including multi-device [12] and multistream [24].…”

Section: Related Workmentioning

confidence: 99%

User Gaze-Driven Adaptation of Omnidirectional Video Delivery Using Spatial Tiling and Scalable Video Encoding

Polakovic

Muntean

2022

IEEE Trans. on Broadcast.

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Omnidirectional video is becoming increasingly popular among viewers, but its delivery requires considerable amount of network bandwidth. Today's streaming services are transmitting the full spatial angle of omnidirectional videos, although most of the transmitted content is not utilized. Due to both limited bandwidth availability and its dynamic fluctuations, adaptive delivery solutions play a key role in supporting high user quality streaming of omnidirectional videos. This paper describes research which extends the MPEG-DASH Spatial Relationship Description by adding scalable video encoding to spatial tiling. It proposes a novel tile-layering based gaze adaptation algorithm for omnidirectional video delivery and employs it in conjunction with multiple tiling schemes. The benefits of the proposed algorithm with diverse tiling schemes are evaluated objectively in terms of bandwidth savings and adaptation latency. The results show a reduction of network bandwidth requirements to about 30% of the original bandwidth value with a low processing latency of 70.87 ms.

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A Q-Learning Driven Energy-Aware Multipath Transmission Solution for 5G Media Services

Cited by 12 publications

References 45 publications

A Novel Analytical Framework Is Developed for Wireless Heterogeneous Networks for Video Streaming Applications

A Novel Analytical Framework Is Developed for Wireless Heterogeneous Networks for Video Streaming Applications

Decentralized Optimization for Multicast Adaptive Video Streaming in Edge Cache-Assisted Networks

User Gaze-Driven Adaptation of Omnidirectional Video Delivery Using Spatial Tiling and Scalable Video Encoding

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