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Artykuły w czasopismach na temat „Adaptive bitrate Algorithm”

Autor: Grafiati

Data publikacji: 16 listopada 2024

Data aktualizacji: 31 lipca 2025

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1

Jabbar, Saba Qasim, and Dheyaa Jasim Kadhim. "A Proposed Adaptive Bitrate Scheme Based on Bandwidth Prediction Algorithm for Smoothly Video Streaming." Journal of Engineering 27, no. 1 (2021): 112–29. http://dx.doi.org/10.31026/j.eng.2021.01.08.

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A robust video-bitrate adaptive scheme at client-aspect plays a significant role in keeping a good quality of video streaming technology experience. Video quality affects the amount of time the video has turned off playing due to the unfilled buffer state. Therefore to maintain a video streaming continuously with smooth bandwidth fluctuation, a video buffer structure based on adapting the video bitrate is considered in this work. Initially, the video buffer structure is formulated as an optimal control-theoretic problem that combines both video bitrate and video buffer feedback signals. While

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Jabbar, Saba Qasim, and Dheyaa Jasim Kadhim. "A Proposed Adaptive Bitrate Scheme Based on Bandwidth Prediction Algorithm for Smoothly Video Streaming." Journal of Engineering 27, no. 1 (2021): 112–29. http://dx.doi.org/10.31026/10.31026/j.eng.2021.01.08.

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A robust video-bitrate adaptive scheme at client-aspect plays a significant role in keeping a good quality of video streaming technology experience. Video quality affects the amount of time the video has turned off playing due to the unfilled buffer state. Therefore to maintain a video streaming continuously with smooth bandwidth fluctuation, a video buffer structure based on adapting the video bitrate is considered in this work. Initially, the video buffer structure is formulated as an optimal control-theoretic problem that combines both video bitrate and video buffer feedback signals. While

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Karagkioules, Theodoros, Georgios S. Paschos, Nikolaos Liakopoulos, Attilio Fiandrotti, Dimitrios Tsilimantos, and Marco Cagnazzo. "Online Learning for Adaptive Video Streaming in Mobile Networks." ACM Transactions on Multimedia Computing, Communications, and Applications 18, no. 1 (2022): 1–22. http://dx.doi.org/10.1145/3460819.

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In this paper, we propose a novel algorithm for video bitrate adaptation in HTTP Adaptive Streaming (HAS), based on online learning. The proposed algorithm, named Learn2Adapt (L2A) , is shown to provide a robust bitrate adaptation strategy which, unlike most of the state-of-the-art techniques, does not require parameter tuning, channel model assumptions, or application-specific adjustments. These properties make it very suitable for mobile users, who typically experience fast variations in channel characteristics. Experimental results, over real 4G traffic traces, show that L2A improves on the

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Cwalina, Krzysztof, Slawomir Ambroziak, Piotr Rajchowski, Jaroslaw Sadowski, and Jacek Stefanski. "A Novel Bitrate Adaptation Method for Heterogeneous Wireless Body Area Networks." Applied Sciences 8, no. 7 (2018): 1209. http://dx.doi.org/10.3390/app8071209.

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In the article, a novel bitrate adaptation method for data streams allocation in heterogeneous Wireless Body Area Networks (WBANs) is presented. The efficiency of the proposed algorithm was compared with other known algorithms of data stream allocation using computer simulation. A dedicated simulator has been developed using results of measurements in the real environment. The usage of the proposed adaptive data streams allocation method by transmission rate adaptation based on radio channel parameters can increase the efficiency of resources’ usage in a heterogeneous WBANs, in relation to fix

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Guo, Jia, Chengrui Li, Jinqi Zhu, et al. "Long Short-Term Memory-Based Non-Uniform Coding Transmission Strategy for a 360-Degree Video." Electronics 13, no. 16 (2024): 3281. http://dx.doi.org/10.3390/electronics13163281.

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This paper studies an LSTM-based adaptive transmission method for a 360-degree video and proposes a non-uniform encoding transmission strategy based on LSTM. Our goal is to maximize the user’s video experience by dynamically dividing the 360-degree video into tiles of different numbers and sizes, and selecting different bitrates for each tile. This aims to reduce buffering events and video jitter. To determine the optimal number and size of tiles at the current moment, we constructed a dual-layer stacked LSTM network model. This model predicts, in real-time, the number, size, and bitrate of th

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Alahmadi, Mohannad, Peter Pocta, and Hugh Melvin. "An Adaptive Bitrate Switching Algorithm for Speech Applications in Context of WebRTC." ACM Transactions on Multimedia Computing, Communications, and Applications 17, no. 4 (2021): 1–21. http://dx.doi.org/10.1145/3458751.

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Web Real-Time Communication (WebRTC) combines a set of standards and technologies to enable high-quality audio, video, and auxiliary data exchange in web browsers and mobile applications. It enables peer-to-peer multimedia sessions over IP networks without the need for additional plugins. The Opus codec, which is deployed as the default audio codec for speech and music streaming in WebRTC, supports a wide range of bitrates. This range of bitrates covers narrowband, wideband, and super-wideband up to fullband bandwidths. Users of IP-based telephony always demand high-quality audio. In addition

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Li, Mao-quan, and Zheng-quan Xu. "An adaptive preprocessing algorithm for low bitrate video coding." Journal of Zhejiang University-SCIENCE A 7, no. 12 (2006): 2057–62. http://dx.doi.org/10.1631/jzus.2006.a2057.

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Peng, Shuai, Jialu Hu, Han Xiao, Shujie Yang, and Changqiao Xu. "Viewport-Driven Adaptive 360◦ Live Streaming Optimization Framework." Journal of Networking and Network Applications 1, no. 4 (2022): 139–49. http://dx.doi.org/10.33969/j-nana.2021.010401.

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Virtual reality (VR) video streaming and 360◦ panoramic video have received extensive attention in recent years, which can bring users an immersive experience. However, the ultra-high bandwidth and ultra-low latency requirements of virtual reality video or 360◦ panoramic video also put tremendous pressure on the carrying capacity of the current network. In fact, since the user’s field of view (a.k.a viewport) is limited when watching a panoramic video and users can only watch about 20%∼30% of the video content, it is not necessary to directly transmit all high-resolution content to the user. T

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Chen, Jessica, Henry Milner, Ion Stoica, and Jibin Zhan. "Benchmark of Bitrate Adaptation in Video Streaming." Journal of Data and Information Quality 13, no. 4 (2021): 1–24. http://dx.doi.org/10.1145/3468063.

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The HTTP adaptive streaming technique opened the door to cope with the fluctuating network conditions during the streaming process by dynamically adjusting the volume of the future chunks to be downloaded. The bitrate selection in this adjustment inevitably involves the task of predicting the future throughput of a video session, owing to which various heuristic solutions have been explored. The ultimate goal of the present work is to explore the theoretical upper bounds of the QoE that any ABR algorithm can possibly reach, therefore providing an essential step to benchmarking the performance

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Luo, Dan, Shuhua Xiong, Chao Ren, Raymond Edward Sheriff, and Xiaohai He. "Fusion-Based Versatile Video Coding Intra Prediction Algorithm with Template Matching and Linear Prediction." Sensors 22, no. 16 (2022): 5977. http://dx.doi.org/10.3390/s22165977.

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The new generation video coding standard Versatile Video Coding (VVC) has adopted many novel technologies to improve compression performance, and consequently, remarkable results have been achieved. In practical applications, less data, in terms of bitrate, would reduce the burden of the sensors and improve their performance. Hence, to further enhance the intra compression performance of VVC, we propose a fusion-based intra prediction algorithm in this paper. Specifically, to better predict areas with similar texture information, we propose a fusion-based adaptive template matching method, whi

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Guo, Jia, Shiqiang Li, Jinqi Zhu, Xiang Li, Bowen Sun, and Weijia Feng. "Adaptive Transmission Strategy for Non-Uniform Coding of 360∘ Videos." Electronics 13, no. 16 (2024): 3266. http://dx.doi.org/10.3390/electronics13163266.

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A 360° video offers a more immersive experience, gaining increasing popularity among users. However, enhancing the transmission efficiency of 360° videos under limited bandwidth conditions remains a significant challenge. This paper segments the video into three areas: the attention area, the edge area, and the viewpoint-switching transition area. Based on the segmentation of these three distinct video areas, a novel non-uniform coding transmission method for 360° videos is presented, along with mathematical modeling to define the optimization problem. A heuristic algorithm is subsequently int

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Pan, Tung-Ming, Kuo-Chin Fan, and Yuan-Kai Wang. "Object-Based Approach for Adaptive Source Coding of Surveillance Video." Applied Sciences 9, no. 10 (2019): 2003. http://dx.doi.org/10.3390/app9102003.

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Intelligent analysis of surveillance videos over networks requires high recognition accuracy by analyzing good-quality videos that however introduce significant bandwidth requirement. Degraded video quality because of high object dynamics under wireless video transmission induces more critical issues to the success of smart video surveillance. In this paper, an object-based source coding method is proposed to preserve constant quality of video streaming over wireless networks. The inverse relationship between video quality and object dynamics (i.e., decreasing video quality due to the occurren

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13

Saleem, Muhammad, Yasir Saleem, H. M. Shahzad Asif, and M. Saleem Mian. "Quality Enhanced Multimedia Content Delivery for Mobile Cloud with Deep Reinforcement Learning." Wireless Communications and Mobile Computing 2019 (July 18, 2019): 1–15. http://dx.doi.org/10.1155/2019/5038758.

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The importance of multimedia streaming using mobile devices has increased considerably. The dynamic adaptive streaming over HTTP is an efficient scheme for bitrate adaptation in which video is segmented and stored in different quality levels. The multimedia streaming with limited bandwidth and varying network environment for mobile users affects the user quality of experience. We have proposed an adaptive rate control using enhanced Double Deep Q-Learning approach to improve multimedia content delivery by switching quality level according to the network, device, and environment conditions. The

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14

Uddin, Syed, Michał Grega, Mikołaj Leszczuk, and Waqas ur Rahman. "Evaluating HAS and Low-Latency Streaming Algorithms for Enhanced QoE." Electronics 14, no. 13 (2025): 2587. https://doi.org/10.3390/electronics14132587.

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The demand for multimedia traffic over the Internet is exponentially growing. HTTP adaptive streaming (HAS) is the leading video delivery system that delivers high-quality video to the end user. The adaptive bitrate (ABR) algorithms running on the HTTP client select the highest feasible video quality by adjusting the quality according to the fluctuating network conditions. Recently, low-latency ABR algorithms have been introduced to reduce the end-to-end latency commonly experienced in HAS. However, a comprehensive study of the low-latency algorithms remains limited. This paper investigates th

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15

Zhang, Xi Nan, and Yan Jun Gong. "The Improvement of UMHexagonS Algorithm in AVS Video Coding." Advanced Materials Research 457-458 (January 2012): 819–24. http://dx.doi.org/10.4028/www.scientific.net/amr.457-458.819.

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To reduce the complexity of AVS pixel motion vector search, this paper proposes a improved AVS pixel motion estimation UMHexagonS algorithm. The algorithm adds the improve of advanced new array and adaptive adjustment search template. To the video sequence of different motion feature, compare with UMHexagonS algorithm, in the case of mean PSNR descend less than 0.01dB and bitrate only mean increase 0.54％, the time of pixel motion estimation is reduced by 8.72％～20.25％ and the calculated amount of pixel motion estimation is also reduced.

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Dai, Yuqi, Changbin Xue, and Li Zhou. "Visual saliency guided perceptual adaptive quantization based on HEVC intra-coding for planetary images." PLOS ONE 17, no. 2 (2022): e0263729. http://dx.doi.org/10.1371/journal.pone.0263729.

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Due to the limited storage space of spacecraft and downlink bandwidth in the data delivery during planetary exploration, an efficient way for image compression onboard is essential to reduce the volume of acquired data. Applicable for planetary images, this study proposes a perceptual adaptive quantization technique based on Convolutional Neural Network (CNN) and High Efficiency Video Coding (HEVC). This technique is used for bitrate reduction while maintaining the subjective visual quality. The proposed algorithm adaptively determines the Coding Tree Unit (CTU) level Quantization Parameter (Q

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17

Nikolyukin, M. S., and A. D. Obukhov. "Adaptive Processing of Camera Video Stream with Limitations on the Network Data Transmission Bandwidth." Informacionnye Tehnologii 30, no. 5 (2024): 252–60. http://dx.doi.org/10.17587/it.30.252-260.

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Video surveillance systems, cameras, and video stream processing are actively used in many enterprises as a monitoring and control tool for regular and emergency situations, as well as staff activities. The application of intelligent algorithms allows tracking and minimizing operator errors, but these approaches are highly sensitive to the quality of the original video, presence of noise, and low resolution. On the other hand, such video surveillance systems may be limited by network bandwidth. Therefore, this work considers an adaptive video stream processing algorithm that ensures efficient

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18

Kang, Jeongho, and Kwangsue Chung. "HTTP Adaptive Streaming Framework with Online Reinforcement Learning." Applied Sciences 12, no. 15 (2022): 7423. http://dx.doi.org/10.3390/app12157423.

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Dynamic adaptive streaming over HTTP (DASH) is an effective method for improving video streaming’s quality of experience (QoE). However, the majority of existing schemes rely on heuristic algorithms, and the learning-based schemes that have recently emerged also have a problem in that their performance deteriorates in a specific environment. In this study, we propose an adaptive streaming scheme that applies online reinforcement learning. When QoE degradation is confirmed, the proposed scheme adapts to changes in the client’s environment by upgrading the ABR model while performing video stream

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Hong Lin, Kuei, and Kuo Huang Chung. "A Greedy-Based Video Bitrate Selection Algorithm with Consideration of QoE Fairness for Adaptive Streaming over Software Defined Network." International Journal of Future Computer and Communication 4, no. 2 (2015): 136–42. http://dx.doi.org/10.7763/ijfcc.2015.v4.372.

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Gomezcoello Rodríguez, Marlon, Justin Picón Barros, and Santiago González Martínez. "Evaluación de un algoritmo de control para video adaptativo empleando enrutamiento tradicional y SDN." Revista Tecnológica - ESPOL 37, no. 1 (2025): 264–84. https://doi.org/10.37815/rte.v37n1.1308.

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Currently, according to the Cisco Annual Internet Report, between 80% and 85% of internet data traffic is generated by video content, making it imperative to develop methods or algorithms that enable the efficient transmission of multimedia content over the network. In this context, this article proposes an optimized algorithm for video traffic control in an SDN environment, allowing for adaptive real-time transmission. The methodology consists of the following stages: first, the video is transmitted at a minimum encoded bitrate; then, the available network bandwidth is measured, based on whic

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Hu, Jianhua, Weimei Wu, Bo Wang, Jiahui Yang, Xiaolin Liu, and Guixiang Luo. "Enhanced image compression with global adaptive loop filter and machine learning-based optimization." Journal of Computational Methods in Sciences and Engineering 25, no. 1 (2024): 270–81. https://doi.org/10.1177/14727978241303212.

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Lossy compression often results in artifacts due to block-based encoding and decoding. A common strategy to mitigate these artifacts is the adaptive loop filter (ALF) method, which calculates the optimal filter for each image frame. However, achieving global adaptive filtering increases bitrate during code transmission. To address this challenge, this paper introduces the global adaptive loop filter and machine learning-based model (GALFMLM), an algorithm that effectively eliminates artifacts and enhances the quality of reconstructed images. It employs a more rational pixel classification meth

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Guo, Jia, Yexuan Zhu, Jinqi Zhu, Fan Shen, Hui Gao, and Ye Tian. "Adaptive Streaming Transmission Optimization Method Based on Three-Dimensional Caching Architecture and Environment Awareness in High-Speed Rail." Electronics 13, no. 1 (2023): 41. http://dx.doi.org/10.3390/electronics13010041.

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In high-mobility scenarios, a user’s media experience is severely constrained by the difficulty of network channel prediction, the instability of network quality, and other problems caused by the user’s fast movement, frequent base station handovers, the Doppler effect, etc. To this end, this paper proposes a video adaptive transmission architecture based on three-dimensional caching. In the temporal dimension, video data are cached to different base stations, and in the spatial dimension video data are cached to base stations, high-speed trains, and clients, thus constructing a multilevel cac

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Rahman, Waqas ur, Md Delowar Hossain, and Eui-Nam Huh. "Fuzzy-Based Quality Adaptation Algorithm for Improving QoE from MPEG-DASH Video." Applied Sciences 11, no. 11 (2021): 5270. http://dx.doi.org/10.3390/app11115270.

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Video clients employ HTTP-based adaptive bitrate (ABR) algorithms to optimize users’ quality of experience (QoE). ABR algorithms adopt video quality based on the network conditions during playback. The existing state-of-the-art ABR algorithms ignore the fact that video streaming services deploy segment durations differently in different services, and HTTP clients offer distinct buffer sizes. The existing ABR algorithms use fixed control laws and are designed with predefined client/server settings. As a result, adaptation algorithms fail to achieve optimal performance across a variety of video

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Chen, Yi, Hongxia Wang, Hanzhou Wu, and Yong Liu. "An adaptive data hiding algorithm with low bitrate growth for H.264/AVC video stream." Multimedia Tools and Applications 77, no. 15 (2017): 20157–75. http://dx.doi.org/10.1007/s11042-017-5411-5.

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Wang, Yimeng, Mridul Agarwal, Tian Lan, and Vaneet Aggarwal. "Learning-Based Online QoE Optimization in Multi-Agent Video Streaming." Algorithms 15, no. 7 (2022): 227. http://dx.doi.org/10.3390/a15070227.

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Video streaming has become a major usage scenario for the Internet. The growing popularity of new applications, such as 4K and 360-degree videos, mandates that network resources must be carefully apportioned among different users in order to achieve the optimal Quality of Experience (QoE) and fairness objectives. This results in a challenging online optimization problem, as networks grow increasingly complex and the relevant QoE objectives are often nonlinear functions. Recently, data-driven approaches, deep Reinforcement Learning (RL) in particular, have been successfully applied to network o

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Liu, Peng, Jongwon Yoon, Ha Ryung Kim, and Suman Banerjee. "VideoCoreCluster: Energy-Efficient, Low-Cost, and Hardware-Assisted Video Transcoding System." Wireless Communications and Mobile Computing 2018 (June 5, 2018): 1–13. http://dx.doi.org/10.1155/2018/7470234.

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Video streaming is one of the killer applications in recent years. Video transcoding plays an important role in the video streaming service to cope with the various purposes. Specifically, content owners and publishers heavily utilize video transcoders to reconfigure source video in a variety of formats, video qualities, and bitrate to provide end users with the best possible quality of service. In this paper, we present VideoCoreCluster, a low-cost and energy-efficient transcoder cluster that is suitable for live streaming services. We designed and implemented real-time video transcoder clust

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Woo, Jeonghun, Seungwoo Hong, Donghyun Kang, and Donghyeok An. "Improving the Quality of Experience of Video Streaming Through a Buffer-Based Adaptive Bitrate Algorithm and Gated Recurrent Unit-Based Network Bandwidth Prediction." Applied Sciences 14, no. 22 (2024): 10490. http://dx.doi.org/10.3390/app142210490.

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With the evolution of cellular networks and wireless-local-area-network-based communication technologies, services for smart device users have appeared. With the popularity of 4G and 5G, smart device users can now consume larger bandwidths than before. Consequently, the demand for various services, such as streaming, online games, and video conferences, has increased. For improved quality of experience (QoE), streaming services utilize adaptive bitrate (ABR) algorithms to handle network bandwidth variations. ABR algorithms use network bandwidth history for future network bandwidth prediction,

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Ahmed, Zaheer, Ayaz Ahmad, Muhammad Altaf, and Mohammed Ahmed Hassan. "Power-Efficient UAV Positioning and Resource Allocation in UAV-Assisted Wireless Networks for Video Streaming with Fairness Consideration." Drones 9, no. 5 (2025): 356. https://doi.org/10.3390/drones9050356.

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This work proposes a power-efficient framework for adaptive video streaming in UAV-assisted wireless networks specially designed for disaster-hit areas where existing base stations are nonfunctional. Delivering high-quality videos requires higher video rates and more resources, which leads to increased power consumption. With the increasing demand of mobile video, efficient bandwidth allocation becomes essential. In shared networks, users with lower bitrates experience poor video quality when high-bitrate users occupy most of the bandwidth, leading to a degraded and unfair user experience. Add

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Rodrigues, Frederico, Ivo Sousa, Maria Paula Queluz, and António Rodrigues. "QoE-Aware Scheduling Algorithm for Adaptive HTTP Video Delivery in Wireless Networks." Wireless Communications and Mobile Computing 2018 (September 2, 2018): 1–16. http://dx.doi.org/10.1155/2018/9736360.

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In the last years, the video content consumed by mobile users has increased exponentially. Since mobile network capacity cannot be increased as fast as required, it is crucial to develop intelligent schedulers that allocate radio resources very efficiently and are able to provide a high Quality of Experience (QoE) to most of the users. This paper proposes a new and effective scheduling solution—the Maximum Buffer Filling (MBF) algorithm—which aims to increase the number of satisfied users in video streaming services provided by wireless networks. The MBF algorithm uses the current buffer level

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Patel, Sagar, Sangeetha Abdu Jyothi, and Nina Narodytska. "CrystalBox: Future-Based Explanations for Input-Driven Deep RL Systems." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 13 (2024): 14563–71. http://dx.doi.org/10.1609/aaai.v38i13.29372.

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We present CrystalBox, a novel, model-agnostic, posthoc explainability framework for Deep Reinforcement Learning (DRL) controllers in the large family of input-driven environments which includes computer systems. We combine the natural decomposability of reward functions in input-driven environments with the explanatory power of decomposed returns. We propose an efficient algorithm to generate future-based explanations across both discrete and continuous control environments. Using applications such as adaptive bitrate streaming and congestion control, we demonstrate CrystalBox's capability to

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A. Abdulhadi, Huda, Dia M. Ali, and Ehab Al-Rawachy. "Advances in Adaptive Filtering for Coherent Dual-Polarization Optical Communication Systems and Their Integration in Dynamic Optical Networks." International Research Journal of Innovations in Engineering and Technology 08, no. 08 (2024): 118–27. http://dx.doi.org/10.47001/irjiet/2024.808014.

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A thorough examination of current developments in adaptive filtering for coherent dualpolarization optical communication systems is provided in this work. The emphasis is on high-capacity networks made possible by dual-polarization, coherent detection, variable bit-rate transceivers. The review explores the effectiveness of different adaptive algorithms in coherent receivers, the importance of dual polarization, and the function of adaptive filters in reducing channel impairments. The research also sheds light on the tradeoffs and difficulties related to flexible bitrate optical transceivers.

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Sima, Qian, Hui Feng, and Bo Hu. "Latitude-Adaptive Integer Bit Allocation for Quantization of Omnidirectional Images." Applied Sciences 14, no. 5 (2024): 1861. http://dx.doi.org/10.3390/app14051861.

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Omnidirectional images have gained significant popularity and drawn great attention nowadays, which poses challenges to omnidirectional image processing in solving the bottleneck of storage and transmission. Projecting onto a two-dimensional image plane is generally used to compress an omnidirectional image. However, the most commonly used projection format, the equirectangular projection (ERP), results in a significant amount of redundant samples in the polar areas, thus incurring extra bitrate and geometric distortion. We derive the optimal latitude-adaptive bit allocation for each image til

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Zhang, Weifeng. "Quality Evaluation of Online Mental Health Education Based on Reinforcement Learning in the Pandemic." Discrete Dynamics in Nature and Society 2021 (December 17, 2021): 1–12. http://dx.doi.org/10.1155/2021/7849194.

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The COVID-19 pandemic has become one of the biggest major health crises reported due its massive impact on many countries. From mental health experts, we know that we cannot lose sight of an equally alarming issue which is the long-term mental health impact the pandemic is going to leave on the society. The rapid spread of the pandemic gives little chance to prepare for or even process all that has happened in terms of job losses and the complete uprooting of everyday life and relationships. It is understandable that students may feel irritable, frustrated, or sad sometimes. Loneliness, confus

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Siddaramappa, Sandeep Gowdra, and Gowdra Shivanandappa Mamatha. "Bit-rate aware effective inter-layer motion prediction using multi-loop encoding structure." Indonesian Journal of Electrical Engineering and Computer Science 37, no. 1 (2025): 569. http://dx.doi.org/10.11591/ijeecs.v37.i1.pp569-579.

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Recently, there has been a notable increase in the use of video content on the internet, leading for the creation of improved codecs like versatile-video-coding (VVC) and high-efficiency video-coding (HEVC). It is important to note that these video coding techniques continue to demonstrate quality degradation and the presence of noise throughout the decoded frames. A number of deep-learning (DL) algorithm-based network structures have been developed by experts to tackle this problem; nevertheless, because many of these solutions use in-loop filtration, extra bits must be sent among the encodin

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Sandeep, Gowdra Siddaramappa Gowdra Shivanandappa Mamatha. "Bit-rate aware effective inter-layer motion prediction using multi-loop encoding structure." Indonesian Journal of Electrical Engineering and Computer Science 37, no. 1 (2025): 569–79. https://doi.org/10.11591/ijeecs.v37.i1.pp569-579.

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Recently, there has been a notable increase in the use of video content on the internet, leading for the creation of improved codecs like versatile-video-coding (VVC) and high-efficiency video-coding (HEVC). It is important to note that these video coding techniques continue to demonstrate quality degradation and the presence of noise throughout the decoded frames. A number of deep-learning (DL) algorithm-based network structures have been developed by experts to tackle this problem; nevertheless, because many of these solutions use in-loop filtration, extra bits must be sent among the encodin

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Vlaović, Jelena, Drago Žagar, Snježana Rimac-Drlje, and Mario Vranješ. "Evaluation of objective video quality assessment methods on video sequences with different spatial and temporal activity encoded at different spatial resolutions." International journal of electrical and computer engineering systems 12, no. 1 (2021): 1–9. http://dx.doi.org/10.32985/ijeces.12.1.1.

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With the development of Video on Demand applications due to the availability of high-speed internet access, adaptive streaming algorithms have been developing and improving. The focus is on improving user’s Quality of Experience (QoE) and taking it into account as one of the parameters for the adaptation algorithm. Users often experience changing network conditions, so the goal is to ensure stable video playback with satisfying QoE level. Although subjective Video Quality Assessment (VQA) methods provide more accurate results regarding user’s QoE, objective VQA methods cost less and are less t

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Viet Hung, Nguyen, Trinh Dac Chien, Nam Pham Ngoc, and Thu Huong Truong. "Flexible HTTP-based Video Adaptive Streaming for good QoE during sudden bandwidth drops." EAI Endorsed Transactions on Industrial Networks and Intelligent Systems 10, no. 2 (2023): e3. http://dx.doi.org/10.4108/eetinis.v10i2.2994.

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We have observed a boom in video streaming over the Internet, especially during the Covid-19 pandemic, that could exceed the network resource availability. In addition to upgrading the network infrastructure, finding a way to smartly adapt the streaming system to the network and users’ conditions to satisfy clients’ perceptions is exceptionally critical, too. This paper proposes a new QoE-aware adaptive streaming scheme over HTTP - ABRA - to make flexible adaptations based on the network and the client’s current status. Besides, we propose a technique that can keep the buffer at an average hig

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Nam, Yun Seong, Jianfei Gao, Chandan Bothra, et al. "Xatu." ACM SIGMETRICS Performance Evaluation Review 50, no. 1 (2022): 9–10. http://dx.doi.org/10.1145/3547353.3522641.

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The performance of Adaptive Bitrate (ABR) algorithms for video streaming depends on accurately predicting the download time of video chunks. Existing prediction approaches (i) assume chunk download times are dominated by network throughput; and (ii) apriori cluster sessions (e.g., based on ISP and CDN) and only learn from sessions in the same cluster. We make three contributions. First, through analysis of data from real-world video streaming sessions, we show (i) apriori clustering prevents learning from related clusters; and (ii) factors such as the Time to First Byte (TTFB) are key componen

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Nam, Yun Seong, Jianfei Gao, Chandan Bothra, et al. "Xatu: Richer Neural Network Based Prediction for Video Streaming." Proceedings of the ACM on Measurement and Analysis of Computing Systems 5, no. 3 (2021): 1–26. http://dx.doi.org/10.1145/3491056.

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The performance of Adaptive Bitrate (ABR) algorithms for video streaming depends on accurately predicting the download time of video chunks. Existing prediction approaches (i) assume chunk download times are dominated by network throughput; and (ii) apriori cluster sessions (e.g., based on ISP and CDN) and only learn from sessions in the same cluster. We make three contributions. First, through analysis of data from real-world video streaming sessions, we show (i) apriori clustering prevents learning from related clusters; and (ii) factors such as the Time to First Byte (TTFB) are key componen

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Li, Xiang, Junfeng Nie, Xinmiao Zhang, et al. "MNCATM: A Multi-Layer Non-Uniform Coding-Based Adaptive Transmission Method for 360° Video." Electronics 13, no. 21 (2024): 4200. http://dx.doi.org/10.3390/electronics13214200.

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With the rapid development of multimedia services and smart devices, 360-degree video has enhanced the user viewing experience, ushering in a new era of immersive human–computer interaction. These technologies are increasingly integrating everyday life, including gaming, education, and healthcare. However, the uneven spatiotemporal distribution of wireless resources presents significant challenges for the transmission of ultra-high-definition 360-degree video streaming. To address this issue, this paper proposes a multi-layer non-uniform coding-based adaptive transmission method for 360° video

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Andrievsky, Boris, Alexander L. Fradkov, and Elena V. Kudryashova. "Control of Two Satellites Relative Motion over the Packet Erasure Communication Channel with Limited Transmission Rate Based on Adaptive Coder." Electronics 9, no. 12 (2020): 2032. http://dx.doi.org/10.3390/electronics9122032.

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The paper deals with the navigation data exchange between two satellites moving in a swarm. It is focused on the reduction of the inter-satellite demanded communication channel capacity taking into account the dynamics of the satellites relative motion and possible erasures in the channel navigation data. The feedback control law is designed ensuring the regulation of the relative satellites motion. The adaptive binary coding/decoding procedure for the satellites navigation data transmission over the limited capacity communication channel is proposed and studied for the cases of ideal and eras

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Ma, Linh, Jaehyung Park, Jiseung Nam, HoYong Ryu, and Jinsul Kim. "A Fuzzy-Based Adaptive Streaming Algorithm for Reducing Entropy Rate of DASH Bitrate Fluctuation to Improve Mobile Quality of Service." Entropy 19, no. 9 (2017): 477. http://dx.doi.org/10.3390/e19090477.

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Kim, Kyungmin, and Minseok Song. "Energy-Saving SSD Cache Management for Video Servers with Heterogeneous HDDs." Energies 15, no. 10 (2022): 3633. http://dx.doi.org/10.3390/en15103633.

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Dynamic adaptive streaming over HTTP (DASH) technique, the most popular streaming method, requires a large number of hard disk drives (HDDs) to store multiple bitrate versions of many videos, consuming significant energy. A solid-state drive (SSD) can be used to cache popular videos, thus reducing HDD energy consumption by allowing I/O requests to be handled by an SSD, but this requires effective HDD power management due to limited SSD bandwidth. We propose a new SSD cache management scheme to minimize the energy consumption of a video storage system with heterogeneous HDDs. We first present a

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Garcia, Henrique D., Mylène C. Q. Farias, Ravi Prakash, and Marcelo M. Carvalho. "Statistical characterization of tile decoding time of HEVC-encoded 360° video." Electronic Imaging 2020, no. 9 (2020): 285–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.9.iqsp-285.

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In this paper, we present a statistical characterization of tile decoding time of 360° videos encoded via HEVC that considers different tiling patterns and quality levels (i.e., bitrates). In particular, we present results for probability density function estimation of tile decoding time based on a series of experiments carried out over a set of 360° videos with different spatial and temporal characteristics. Additionally, we investigate the extent to which tile decoding time is correlated with tile bitrate (at chunk level), so that DASH-based video streaming can make possible use of such an i

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Roh Bintang Jaya, Mabrur, Widyastuti Andriyani, Domy Kristomo, and Muhammad Agung Nugroho. "Dynamic Bitrate Adjustment in Web-based Video Streaming Applications Using HTTP Live Streaming (HLS)." Journal of Intelligent Software Systems 3, no. 1 (2024): 13. http://dx.doi.org/10.26798/jiss.v3i1.1344.

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This research aims to implement Adaptive Bit Rate (ABR) in the web-based video streaming application JBTV using HTTP Live Streaming (HLS). ABR is a technique that enables automatic adjustment of video bitrate according to user network conditions, while HLS is a streaming protocol that supports adaptive streaming based on HTTP. The research methodology encompasses requirements analysis, system design, implementation, and evaluation. During the requirements analysis phase, the identification of JBTV application requirements and the features needed to implement ABR with HLS were conducted. System

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Zhang, Rui-Xiao, and Tianchi Huang. "Adversarial Attacks on Federated-Learned Adaptive Bitrate Algorithms." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 1 (2024): 419–27. http://dx.doi.org/10.1609/aaai.v38i1.27796.

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Learning-based adaptive bitrate (ABR) algorithms have revolutionized video streaming solutions. With the growing demand for data privacy and the rapid development of mobile devices, federated learning (FL) has emerged as a popular training method for neural ABR algorithms in both academia and industry. However, we have discovered that FL-based ABR models are vulnerable to model-poisoning attacks as local updates remain unseen during global aggregation. In response, we propose MAFL (Malicious ABR model based on Federated Learning) to prove that backdooring the learning-based ABR model via FL is

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Wu, Dapeng, Linfeng Cui, Tong Tang, and Ruyan Wang. "Adaptive Bandwidth Prediction and Smoothing Glitches in Low-Latency Live Streaming." Security and Communication Networks 2022 (May 9, 2022): 1–13. http://dx.doi.org/10.1155/2022/4992957.

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HTTP adaptive streaming (HAS) technologies such as dynamic adaptive streaming over HTTP (DASH) and common media application format (CMAF) are now used extensively to deliver live streaming services to large numbers of viewers. However, in dynamic networks, inaccurate bandwidth prediction may result in the wrong request of bitrate, and short-term network fluctuations may produce glitches, causing unnecessary bitrate switching, thereby degrading clients' Quality of Experience (QoE). To tackle this, we propose adaptive bandwidth prediction and smoothing glitches in low-latency live streaming (cal

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Brown, Harrison, Kai Fricke, and Eiko Yoneki. "World-Models for Bitrate Streaming." Applied Sciences 10, no. 19 (2020): 6685. http://dx.doi.org/10.3390/app10196685.

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Adaptive bitrate (ABR) algorithms optimize the quality of streaming experiences for users in client-side video players, especially in unreliable or slow mobile networks. Several rule-based heuristic algorithms can achieve stable performance, but they sometimes fail to properly adapt to changing network conditions. Fluctuating bandwidth may cause algorithms to default to behavior that creates a negative experience for the user. ABR algorithms can be generated with reinforcement learning, a decision-making paradigm in which an agent learns to make optimal choices through interactions with an env

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Meng, Zili, Yaning Guo, Yixin Shen, et al. "Practically Deploying Heavyweight Adaptive Bitrate Algorithms With Teacher-Student Learning." IEEE/ACM Transactions on Networking 29, no. 2 (2021): 723–36. http://dx.doi.org/10.1109/tnet.2020.3048666.

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Izhikevich, Liz, Reese Enghardt, Te-Yuan Huang, and Renata Teixeira. "A Global Perspective on the Past, Present, and Future of Video Streaming over Starlink." Proceedings of the ACM on Measurement and Analysis of Computing Systems 8, no. 3 (2024): 1–22. https://doi.org/10.1145/3700412.

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This study presents the first global analysis of on-demand video streaming over Low Earth Orbit (LEO) satellite networks, using data from over one million households across 85 countries. We highlight Starlink's role as a major LEO provider, enhancing connectivity in underserved regions. Our findings reveal that while overall video quality on Starlink matches that of traditional networks, the inherent variability in LEO conditions---such as throughput fluctuations and packet loss---leads to an increase in bitrate switches and rebuffers. To further improve the quality of experience for the LEO c

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