Academic literature on the topic 'Codes for low-latency streaming'
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Journal articles on the topic "Codes for low-latency streaming"
Nikhil Krishnan, M., Vinayak Ramkumar, Myna Vajha, and P. Vijay Kumar. "Simple Streaming Codes for Reliable, Low-Latency Communication." IEEE Communications Letters 24, no. 2 (February 2020): 249–53. http://dx.doi.org/10.1109/lcomm.2019.2956500.
Full textWang, Cong. "A Novel Model for Large-Scale Online College Learning in Postpandemic Era: AI-Driven Approach." Mobile Information Systems 2021 (December 14, 2021): 1–10. http://dx.doi.org/10.1155/2021/1048186.
Full textBadr, Ahmed, Pratik Patil, Ashish Khisti, Wai-Tian Tan, and John Apostolopoulos. "Layered Constructions for Low-Delay Streaming Codes." IEEE Transactions on Information Theory 63, no. 1 (January 2017): 111–41. http://dx.doi.org/10.1109/tit.2016.2618924.
Full textYıldız, Ezgi Pelin, and Sahap Altınbas. "Investigation of Efficient Backup Tecniques To Reduce Late In Cloud Systems: A Modeling Study." Global Journal of Information Technology: Emerging Technologies 13, no. 1 (April 1, 2023): 46–54. http://dx.doi.org/10.18844/gjit.v13i1.8863.
Full textPetracca, Matteo, Claudio Salvadori, Stefano Bocchino, and Paolo Pagano. "Error Resilient Video Streaming with BCH Code Protection in Wireless Sensor Networks." Journal of Communications Software and Systems 10, no. 1 (March 21, 2014): 41. http://dx.doi.org/10.24138/jcomss.v10i1.139.
Full textOkwudire, Chinedum, Sharankumar Huggi, Sagar Supe, Chengyang Huang, and Bowen Zeng. "Low-Level Control of 3D Printers from the Cloud: A Step toward 3D Printer Control as a Service." Inventions 3, no. 3 (August 19, 2018): 56. http://dx.doi.org/10.3390/inventions3030056.
Full textGiraldo Barrada, Jorge Enrique, Juan Camilo García Viana, John Edison Morales Galeano, and Emanuel Valencia Henáo. "Construction of metal transfer modes maps for an ER4130 filler metal in GMAW process." DYNA 87, no. 215 (November 5, 2020): 126–35. http://dx.doi.org/10.15446/dyna.v87n215.86825.
Full textShoucri, M., X. Lavocat-Dubuis, J. P. Matte, and F. Vidal. "Numerical study of ion acceleration and plasma jet formation in the interaction of an intense laser beam normally incident on an overdense plasma." Laser and Particle Beams 29, no. 3 (July 11, 2011): 315–32. http://dx.doi.org/10.1017/s026303461100036x.
Full textGoel, Ashvin, Charles Krasic, and Jonathan Walpole. "Low-latency adaptive streaming over tcp." ACM Transactions on Multimedia Computing, Communications, and Applications 4, no. 3 (August 2008): 1–20. http://dx.doi.org/10.1145/1386109.1386113.
Full textMaiya, S. V., Daniel J. Costello, and T. E. Fuja. "Low Latency Coding: Convolutional Codes vs. LDPC Codes." IEEE Transactions on Communications 60, no. 5 (May 2012): 1215–25. http://dx.doi.org/10.1109/tcomm.2012.042712.110189.
Full textDissertations / Theses on the topic "Codes for low-latency streaming"
Goel, Ashvin. "Operating system support for low-latency streaming /." Full text open access at:, 2003. http://content.ohsu.edu/u?/etd,194.
Full textTay, Kah Keng. "Low-latency network coding for streaming video multicast." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/46523.
Full textIncludes bibliographical references (p. 95-98).
Network coding has been successfully employed to increase throughput for data transfers. However, coding inherently introduces packet inter-dependencies and adds decoding delays which increase latency. This makes it difficult to apply network coding to real-time video streaming where packets have tight arrival deadlines. This thesis presents FLOSS, a wireless protocol for streaming video multicast. At the core of FLOSS is a novel network code. This code maximizes the decoding opportunities at every receiver, and at the same time minimizes redundancy and decoding latency. Instead of sending packets plainly to a single receiver, a sender mixes in packets that are immediately beneficial to other receivers. This simple technique not only allows us to achieve the coding benefits of increased throughput, it also decreases delivery latency, unlike other network coding approaches. FLOSS performs coding over a rolling window of packets from a video flow, and determines with feedback the optimal set of packet transmissions needed to get video across in a timely and reliable manner. A second important characteristic of FLOSS is its ability to perform both interand intra-flow network coding at the same time. Our technique extends easily to support multiple video streams, enabling us to effectively and transparently apply network coding and opportunistic routing to video multicast in a wireless mesh. We devise VSSIM*, an improved video quality metric based on [46]. Our metric addresses a significant limitation of prior art and allows us to evaluate video with streaming errors like skipped and repeated frames. We have implemented FLOSS using Click [22]. Through experiments on a 12-node testbed, we demonstrate that our protocol outperforms both a protocol that does not use network coding and one that does so naively. We show that the improvement in video quality comes from increased throughput, decreased latency and opportunistic receptions from our scheme.
by Kah Keng Tay.
M.Eng.
Tafleen, Sana. "Fault Tolerance Strategies for Low-Latency Live Video Streaming." Thesis, University of Louisiana at Lafayette, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=13420002.
Full textThis paper describes the effect of failures on various video QoS metrics like delay, packet loss, and recovery time. SDN network has been used to guarantee reliability and efficient data transmission. There are many failures that can occur within the SDN mesh network or between the non-SDN and the SDN network. There is a need for both reliable and low-latency transmission of live video streams, especially in situations such as public safety or public gathering events. This is because everyone is trying to use the limited network at the same time. That leads to oversubscription and network outages, and computing devices may fail. Existing mechanisms built into TCP/IP and video streaming protocols, and fault tolerance strategies (such as buffering), are inadequate due to low latency and reliability requirements for live streaming, especially in the presence of limited bandwidth and computational power of mobile or edge devices. The objective of this paper is to develop an efficient fault tolerant strategy at the source-side to produce a high-quality video with low latency and data loss. To recover the lost data during failures, buffering approach is used to store chunks in a buffer and retransmit the lost frames, requested by the receiver.
Ben, Yahia Mariem. "Low latency video streaming solutions based on HTTP/2." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2019. http://www.theses.fr/2019IMTA0136/document.
Full textAdaptive video streaming techniques enable the delivery of content that is encoded at various levels of quality and split into temporal segments. Before downloading a segment, the client runs an adaptation algorithm to determine the level of quality that best matches the network resources. For immersive video streaming this adaptation mechanism should also consider the head movement of a user watching the 360° video to maximize the quality of the viewed portion. However, this adaptation may suffer from errors, which impact the end user’s quality of experience. In this case, an HTTP/1 client must wait for the download of the next segment to choose a suitable quality. In this thesis, we propose to use the HTTP/2 protocol instead to address this problem. First, we focus live streaming video. We design a strategy to discard video frames when the band width is very variable in order so as to avoid the rebuffering events and the accumulation of delays. The customer requests each video frame in an HTTP/2 stream which allows to control the delivery of frames by leveraging the HTTP/2 features at the level of the dedicated stream. Besides, we use the priority and reset stream features of HTTP/2 to optimize the delivery of immersive videos. We propose a strategy to benefit from the improvement of the user’s head movements prediction overtime. The results show that HTTP/2 allows to optimize the use of network resources and to adapt to the latencies required by each service
Tideström, Jakob. "Investigation into low latency live video streaming performance of WebRTC." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-249446.
Full textEftersom WebRTC är menat för peer-to-peer realtidskommunikation så har den förmågan att strömma video med låg latens. Denna avhandling utnyttjar den här förmågan för att strömma livevideo i ett klient-server-scenario. Med en uppsättning som omfattar en lokal sändare, server, och klient strömmas en statisk videofil som en live-video. Prestandan jämförs med hur de samtida liveströmningsteknikerna HTTP Live Streaming respective Dynamic Adaptive Streaming over HTTP strömmar samma innehåll. Slutsatsen är att WebRTC lyckas uppnå lägre latens än båda de andra teknikerna men utan relativt mycket finjustering så försämras kvaliteten på strömmen.
Bhat, Amit. "Low-latency Estimates for Window-Aggregate Queries over Data Streams." PDXScholar, 2011. https://pdxscholar.library.pdx.edu/open_access_etds/161.
Full textGazi, Orhan. "Parallelized Architectures For Low Latency Turbo Structures." Phd thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608110/index.pdf.
Full textSonono, Tofik. "Interoperable Retransmission Protocols with Low Latency and Constrained Delay : A Performance Evaluation of RIST and SRT." Thesis, KTH, Kommunikationssystem, CoS, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254897.
Full textI mediabranschen finns det en efterfrågan på utrustning som har inslag av interoperabilitet.Anledningen till detta är att någon som köper produkter från en viss återförsäljare inte vill låsas in idenna återförsäljares ”ekosystem” i flera år framöver. Då en studio sällan uppgraderar hela sinproduktionskedja på samma gång ger interoperabilitet möjligheten att köpa utrustning från andraåterförsäljare när man ska uppgradera något i produktionslinan. Detta leder till en merkonkurrenskraftig marknad samt ger incentiv till nya innovativa lösningar. Detta examensarbete går ut på att utvärdera lösningar som tagits fram för att främjainteroperabilitet och jämföra dem med en existerande proprietärlösning. Reliable Internet StreamTransport (RIST) och Secure Reliable Transport (SRT) är två protokoll som tagits fram för just dettasyfte. Utmaningen med att utvärdera dessa protokoll är att i en labbmiljö få resultat som reflekteraranvändandet av protokollen i verkligheten. Detta har gjorts med hjälp av ett program som tagitsfram i detta examensarbete. Med detta program har testandet kunnat automatiseras. Resultaten i detta examensarbete visar potential hos båda RIST och SRT. SRT är i vissascenarion till och med bättre än den proprietära lösningen. Protokollen visar något buggigtbeteende i vissa instanser, såsom att i vissa fal sluta fungera och inte kunna återgå till normalfunktion utan manuell interaktion. Allt som allt är dock protokollen i de flesta fallen testade i dettaexamensarbete ett godtyckligt alternativ till den jämförda proprietära lösningen.
Lai, Hsu-Te, and 賴旭德. "Low Latency and Efficient Packet Scheduling for Streaming Applications." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/30454995901658632809.
Full text國立中央大學
資訊工程研究所
91
Adequate bandwidth allocations and strict delay requirements are critical for real time applications. Packet scheduling algorithms like Class Based Queue (CBQ), Nested Deficit Round Robin (Nested-DRR) are designed to ensure the bandwidth reservation function. However, they might cause unsteady packet latencies and introduce extra application handling overhead, such as allocating a large buffer for playing the media stream. High and unstable latency of packets might jeopardize the corresponding Quality of Service since real-time applications prefer low playback latency. Existing scheduling algorithms which keep latency of packets stable require knowing the details of individual flows. GPS (General Processor Sharing)-like algorithms does not consider the real behavior of a stream. A real stream is not perfectly smooth after forwarded by routers. GPS-like algorithms will introduce extra delay on the stream which is not perfectly smooth. This thesis presents an algorithm which provides low latency and efficient packet scheduling service for streaming applications called LLEPS.
Huang, Ting-Chun, and 黃亭鈞. "Realizing Low Latency Real-Time Video Streaming Service with TCP." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/34440272109505633081.
Full text國立臺灣海洋大學
資訊工程學系
103
Most real-time video streams are delivered using UDP. Compared against TCP, UDP does not have the head-of-line blocking effect, and therefore the performance does not drop dramatically due to packet losses. However, UDP does not offer a reliable packet delivery service, and it may not work in certain network setups including traffic shaping, firewall, and NAT. Researchers have attempted to solve the aforementioned problem using SCTP. However, the performance of SCTP on real-time video streaming is not clear, and it is not built-in for most off-the-shelf operating systems including both desktop and mobile OSes. As a result, it could not be a good choice for the demanding real-time multimedia streaming applications such as cloud gaming and video surveillance. Based on the observation, we proposed a real-time video streaming protocol design based on TCP, which is called multiple-flow TCP model. In this model, we leverage concurrent TCP flows to deliver multimedia streams. In addition to take the benefits of reliable packet delivery, the performance drop caused on packet losses can be mitigated and therefore improve the overall throughput. Our evaluation shows that the multiple-flow TCP model has a similar performance to UDP, and it offers the benefits of TCP and SCTP. We further conduct user studies to understand real user experiences regarding the performance of the proposed model. It also shows that the multiple-flow TCP model can perform better than TCP and SCTP in terms of real-timeliness and video quality.
Book chapters on the topic "Codes for low-latency streaming"
Giard, Pascal, Claude Thibeault, and Warren J. Gross. "Low-Latency Software Polar Decoders." In High-Speed Decoders for Polar Codes, 31–53. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59782-9_3.
Full textAmini Salehi, Mohsen, and Xiangbo Li. "Low-Latency Delivery Networks for Multimedia Streaming." In Multimedia Cloud Computing Systems, 125–51. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88451-2_7.
Full textMouhoubi, Oualid, Charbel Abdel Nour, and Amer Baghdadi. "Low Latency Architecture Design for Decoding 5G NR Polar Codes." In Design and Architecture for Signal and Image Processing, 16–28. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12748-9_2.
Full textCappellari, Paolo, Mark Roantree, and Soon Ae Chun. "A Scalable Platform for Low-Latency Real-Time Analytics of Streaming Data." In Communications in Computer and Information Science, 1–24. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62911-7_1.
Full textCarbone, Paris, and Vana Kalogeraki. "A Topologically-Aware Overlay Tree for Efficient and Low-Latency Media Streaming." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 383–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10625-5_24.
Full textChen, Si, Yuan Zhang, Huan Peng, and Jinyao Yan. "A Joint Bitrate and Buffer Control Scheme for Low-Latency Live Streaming." In Intelligence Science and Big Data Engineering. Big Data and Machine Learning, 369–80. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36204-1_31.
Full textDrioli, Carlo, Claudio Allocchio, and Nicola Buso. "Networked Performances and Natural Interaction via LOLA: Low Latency High Quality A/V Streaming System." In Lecture Notes in Computer Science, 240–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40050-6_21.
Full textFleury, Martin, and Laith Al-Jobouri. "Data Partitioning." In Advances in Multimedia and Interactive Technologies, 118–58. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-8850-6.ch004.
Full textRaheel, Muhammad Salman, and Raad Raad. "Streaming Coded Video in P2P Networks." In Advances in Wireless Technologies and Telecommunication, 188–222. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2113-6.ch009.
Full textRaheel, Muhammad Salman, and Raad Raad. "Streaming Coded Video in P2P Networks." In Research Anthology on Recent Trends, Tools, and Implications of Computer Programming, 1304–39. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-3016-0.ch060.
Full textConference papers on the topic "Codes for low-latency streaming"
Tonomura, Yoshihide, Daisuke Shirai, Masahiko Kitamura, Takayuki Nakachi, Tatsuya Fujii, and Hitoshi Kiya. "Low-Density Generator Matrix Codes for IP Packet Video Streaming with Backward Compatibility." In ICC 2011 - 2011 IEEE International Conference on Communications. IEEE, 2011. http://dx.doi.org/10.1109/icc.2011.5963201.
Full textKalan, Reza Shokri, Reza Farahani, Emre Karsli, Christian Timmerer, and Hermann Hellwagner. "Towards low latency live streaming." In MMSys '22: 13th ACM Multimedia Systems Conference. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3524273.3532904.
Full textShuai, Yongtao, Manuel Gorius, and Thorsten Herfet. "Low-latency dynamic adaptive video streaming." In 2014 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB). IEEE, 2014. http://dx.doi.org/10.1109/bmsb.2014.6873486.
Full textKim, Seohyang, Seungyoung Shin, and Joonseok Moon. "UDP-based Extremely Low Latency Streaming." In 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC). IEEE, 2022. http://dx.doi.org/10.1109/ccnc49033.2022.9700635.
Full textZhu, Xiaoqing, Jiang Zhu, Rong Pan, Mythili Suryanarayana Prabhu, and Flavio Bonomi. "Cloud-assisted streaming for low-latency applications." In 2012 International Conference on Computing, Networking and Communications (ICNC). IEEE, 2012. http://dx.doi.org/10.1109/iccnc.2012.6167565.
Full textKaragkioules, Theo, Rufael Mekuria, Dirk Griffioen, and Arjen Wagenaar. "Online learning for low-latency adaptive streaming." In MMSys '20: 11th ACM Multimedia Systems Conference. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3339825.3397042.
Full textSun, Liyang, Tongyu Zong, Siquan Wang, Yong Liu, and Yao Wang. "Tightrope walking in low-latency live streaming." In MMSys '21: 12th ACM Multimedia Systems Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3458305.3463382.
Full textSanchez, Yago, Edward Grinshpun, David Faucher, Thomas Schierl, and Sameer Sharma. "Low latency DASH based streaming over LTE." In 2014 IEEE Visual Communications and Image Processing Conference (VCIP). IEEE, 2014. http://dx.doi.org/10.1109/vcip.2014.7051489.
Full textBentaleb, Abdelhak, Christian Timmerer, Ali C. Begen, and Roger Zimmermann. "Bandwidth prediction in low-latency chunked streaming." In the 29th ACM Workshop. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3304112.3325611.
Full textMatri, Pierre, and Robert Ross. "Neon: Low-Latency Streaming Pipelines for HPC." In 2021 IEEE 14th International Conference on Cloud Computing (CLOUD). IEEE, 2021. http://dx.doi.org/10.1109/cloud53861.2021.00089.
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