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Serverless streaming for emerging media: towards 5G network-driven cost optimization

A real-time adaptive streaming FaaS service for small-session-oriented immersive media

  • 1172: 5G Multimedia communications for Vehicular, Industry and Entertainment applications
  • Published:
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Abstract

Immersive 3D media is an emerging type of media that captures, encodes and reconstructs the 3D appearance of people and objects, with applications in tele-presence, teleconference, entertainment, gaming and other fields. In this paper, we discuss a novel concept of live 3D immersive media streaming in a serverless setting. In particular, we present a novel network-centric adaptive streaming framework which deviates from the traditional client-based adaptive streaming used in 2D video. In our framework the decisions for the production of the transcoding profiles are taken in a centralized manner, by considering consumer metrics vs provisioning costs and inferring the expected consumer quality of experience and behavior based on them. In addition, we demonstrate that a naive application of the serverless paradigm might be sub-optimal under some common immersive 3D media scenarios.

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Notes

  1. A reference implementation of our extended FaaS framework and its integration with MANO, can be found in https://github.com/5g-media/faas-vim-plugin.

  2. In Apache OpenWhisk parlance, functions are termed actions. We will use the terms interchangeably, wherever this does not cause ambiguity

  3. https://www.nvidia.com/en-us/data-center/virtual-gpu-technology/

  4. https://www.nuweba.com/

  5. https://cloud.ibm.com/functions/learn/pricing

  6. https://www.ibm.com/cloud/virtual-servers/pricing/

  7. http://www.5gmedia.eu/

  8. https://github.com/5g-media/faas-vim-plugin

References

  1. Alexiadis D, Chatzitofis A, Zioulis N, Zoidi O, Louizis G, Zarpalas D, Daras P (2017) An integrated platform for live 3D human reconstruction and motion capturing. IEEE Trans Circ Syst Video Technol 27(4):798–813. https://doi.org/10.1109/TCSVT.2016.2576922

    Article  Google Scholar 

  2. Alvarez F, Breitgand D, Griffin D, Andriani P, Rizou S, Zioulis N, Moscatelli F, Serrano J, Keltsch M, Trakadas P et al (2019) An edge-to-cloud virtualized multimedia service platform for 5g networks. IEEE Trans Broadcast 65(2):369–380

    Article  Google Scholar 

  3. Ao L, Izhikevich L, Voelker GM, Porter G (2018) Sprocket: a serverless video processing framework. In: Proceedings of the ACM symposium on cloud computing (SoCC ’18). https://doi.org/10.1145/3267809.3267815, http://par.nsf.gov/biblio/10098946

  4. Apache OpenWhisk: Open Source Serverless Cloud Platform. https://openwhisk.apache.org/

  5. Argo Events Team: Argo Events - The Event-driven Workflow Automation Framework. https://github.com/argoproj/argo-events

  6. Argo Team: Argo Workflows. https://github.com/argoproj/argo

  7. Athanasoulis P, Christakis E, Konstantoudakis K, Drakoulis P, Rizou S, Weit A, Doumanoglou A, Zioulis N, Zarpalas D (2020) Optimizing qoe and cost in a 3d immersive media platform: a reinforcement learning approach. In: MMEDIA 2020: the twelfth international conference on advances in multimedia. IARIA

  8. Ballard T, Griwodz C, Steinmetz R, Rizk A Rats: adaptive 360-degree live streaming. In: Proceedings of the 10th ACM multimedia systems conference, MMSys ’19, p 308–311. Association for Computing Machinery (2019). https://doi.org/10.1145/3304109.3323837. Event-place: Amherst, Massachusetts

  9. Barman N, Martini MG (2019) QoE modeling for HTTP adaptive video streaming–a survey and open challenges. IEEE Access 7:30831–30859. https://doi.org/10.1109/ACCESS.2019.2901778. Conference Name: IEEE Access

    Article  Google Scholar 

  10. Bentaleb A, Taani B, Begen AC, Timmerer C, Zimmermann R (2018) A survey on bitrate adaptation schemes for streaming media over http. IEEE Commun Sur Tutor 21(1):562–585

    Article  Google Scholar 

  11. Bentaleb A, Taani B, Begen AC, Timmerer C, Zimmermann R (2019) A survey on bitrate adaptation schemes for streaming media over HTTP. IEEE Commun Surv Tutor 21(1):562–585. https://doi.org/10.1109/COMST.2018.2862938. Conference Name: IEEE Communications Surveys Tutorials

    Article  Google Scholar 

  12. Bhargava A, Martin J, Babu SV Comparative evaluation of user perceived quality assessment of design strategies for HTTP-based adaptive streaming (2019). https://doi.org/10.1145/3345313

  13. Breitgand D, Weit A (2019) Using gpus with apache openwhisk. https://medium.com/openwhisk/using-gpus-with-apache-openwhisk-c6773efcccfb

  14. Chakareski J, Aksu R, Corbillon X, Simon G, Swaminathan V (2018) Viewport-driven rate-distortion optimized 360∘ video streaming. In: 2018 IEEE International conference on communications (ICC), pp 1–7. https://doi.org/10.1109/ICC.2018.8422859

  15. Chen Y, Zhang F, Wu K, Zhang Q (2015) Qoe-aware dynamic video rate adaptation. In: 2015 IEEE Global communications conference (GLOBECOM). IEEE, pp 1–6

  16. Chou PA, Koroteev M, Krivokuća M (2020) A volumetric approach to point cloud compression—part i: attribute compression. IEEE Trans Image Process 29:2203–2216. https://doi.org/10.1109/TIP.2019.2908095

    Article  Google Scholar 

  17. Christaki K, Apostolakis KC, Doumanoglou A, Zioulis N, Zarpalas D, Daras P (2019) Space wars: an augmentedvr game. In: International conference on multimedia modeling. Springer, pp 566–570

  18. Collet A, Chuang M, Sweeney P, Gillett D, Evseev D, Calabrese D, Hoppe H, Kirk A, Sullivan S High-quality streamable free-viewpoint video (2015). https://doi.org/10.1145/2766945

  19. Crowle S, Doumanoglou A, Poussard B, Boniface M, Zarpalas D, Daras P (2015) Dynamic adaptive mesh streaming for real-time 3d teleimmersion. In: Proceedings of the 20th international conference on 3D web technology, Web3D ’15. https://doi.org/10.1145/2775292.2775296. Event-place: Heraklion, Crete, Greece. Association for Computing Machinery, pp 269–277

  20. Cui L, Mekuria R, Preda M, Jang E (2019) Point-cloud compression: moving picture experts group’s new standard in 2020. IEEE Consum Electron Mag 8(4):17–21. https://doi.org/10.1109/MCE.2019.2905483

    Article  Google Scholar 

  21. Ding AY, Janssen M (2018) 5g applications: requirements, challenges, and outlook. arXiv:1810.06057

  22. Domański M, Stankiewicz O, Wegner K, Grajek T (2017) Immersive visual media — mpeg-i: 360 video, virtual navigation and beyond. In: 2017 International conference on systems, signals and image processing (IWSSIP), pp 1–9

  23. Dou M, Khamis S, Degtyarev Y, Davidson P, Fanello SR, Kowdle A, Escolano SO, Rhemann C, Kim D, Taylor J, Kohli P, Tankovich V, Izadi S (2016) Fusion4D: real-time performance capture of challenging scenes. https://doi.org/10.1145/2897824.2925969

  24. Doumanoglou A, Alexiadis DS, Zarpalas D, Daras P (2014) Toward real-time and efficient compression of human time-varying meshes. IEEE Trans Circ Syst Video Technol 24(12):2099–2116. https://doi.org/10.1109/TCSVT.2014.2319631

    Article  Google Scholar 

  25. Doumanoglou A, Drakoulis P, Zioulis N, Zarpalas D, Daras P (2019) Benchmarking open-source static 3d mesh codecs for immersive media interactive live streaming. IEEE J Emerg Selected Topics Circ Syst 9(1):190–203. https://doi.org/10.1109/JETCAS.2019.2898768

    Article  Google Scholar 

  26. Doumanoglou A, Griffin D, Serrano J, Zioulis N, Phan TK, Jiménez D, Zarpalas D, Alvarez F, Rio M, Daras P (2018) Quality of experience for 3-D immersive media streaming. IEEE Trans Broadcast 64(2):379–391. https://doi.org/10.1109/TBC.2018.2823909. Conference Name: IEEE Transactions on Broadcasting

    Article  Google Scholar 

  27. Doumanoglou A, Zioulis N, Griffin D, Serrano J, Phan TK, Jiménez D, Zarpalas D, Alvarez F, Rio M, Daras P (2018) A system architecture for live immersive 3d-media transcoding over 5g networks. In: 2018 IEEE International symposium on broadband multimedia systems and broadcasting (BMSB). IEEE, pp 11–15

  28. El Marai O, Taleb T, Menacer M, Koudil M (2018) On improving video streaming efficiency, fairness, stability, and convergence time through client–server cooperation. IEEE Trans Broadcast 64(1):11–25. https://doi.org/10.1109/TBC.2017.2781146

    Article  Google Scholar 

  29. ETSI: Multi-access Edge Computing (MEC); Framework and Reference Architecture; GS MEC 003 V2.1.1 (2019-01) (2019). https://www.etsi.org/deliver/etsi_gs/MEC/001_099/003/02.01.01_60/gs_MEC003v020101p.pdf

  30. Fan CL, Lo WC, Pai YT, Hsu CH (2019) A survey on 360∘ video streaming: acquisition, transmission, and display. ACM Comput Surv, 52(4). https://doi.org/10.1145/3329119

  31. Flannel, Kubernetes Networking. https://github.com/coreos/flannel#flannel

  32. Girinathan J, Breckinridge R (2018) Simple serverless video on demand (vod) workflow. https://aws.amazon.com/blogs/networking-and-content-delivery/serverless-video-on-demand-vod-workflow/

  33. Graf M, Timmerer C, Mueller C (2017) Towards bandwidth efficient adaptive streaming of omnidirectional video over HTTP: design, implementation, and evaluation. In: Proceedings of the 8th ACM on multimedia systems conference - MMSys’17. https://doi.org/10.1145/3083187.3084016. ACM Press, Taipei, pp 261–271

  34. Hannuksela MM, Wang YK, Hourunranta A An overview of the OMAF standard for 360∘ video. In: 2019 Data compression conference (DCC), pp 418–427 (2019). https://doi.org/10.1109/DCC.2019.00050. ISSN: 2375-0359

  35. He J, Qureshi M, Qiu L, Li J, Li F, Han L (2018) Rubiks: practical 360-degree streaming for smartphones, p 482–494. https://doi.org/10.1145/3210240.3210323

  36. Hoßfeld T, Seufert M, Sieber C, Zinner T, Tran-Gia P (2015) Identifying QoE optimal adaptation of HTTP adaptive streaming based on subjective studies. Comput Netw 81:320–332. https://doi.org/10.1016/j.comnet.2015.02.015, http://www.sciencedirect.com/science/article/pii/S1389128615000626

    Article  Google Scholar 

  37. Hosseini M (2019) Adaptive rate allocation for view-aware point-cloud streaming. arXiv:1911.008121911.00812

  38. Hosseini M, Swaminathan V (2016) Adaptive 360 vr video streaming: divide and conquer. In: 2016 IEEE International symposium on multimedia (ISM). https://doi.org/10.1109/ISM.2016.0028, pp 107–110

  39. IBM Cloud Functions. https://cloud.ibm.com/functions/

  40. ISO/IEC: Information technology — Dynamic adaptive streaming over HTTP (DASH) — Part 5: Server and network assisted DASH (SAND). https://www.iso.org/standard/69079.html

  41. Jain R (1990) The art of computer systems performance analysis: techniques for experimental design, measurement, simulation, and modeling. Wiley. https://books.google.co.il/books?id=eOR0kJjgMqkC

  42. Karakottas A, Papachristou A, Doumanoqlou A, Zioulis N, Zarpalas D, Daras P (2018) Augmented vr. In: 2018 IEEE Conference on virtual reality and 3d user interfaces (VR), pp 1–1

  43. Kazhdan M (2005) Reconstruction of solid models from oriented point sets. In: Proceedings of the third eurographics symposium on geometry processing. Eurographics Association, p 73

  44. Kazhdan M, Bolitho M, Hoppe H (2006) Poisson surface reconstruction. In: Proceedings of the fourth eurographics symposium on geometry processing, vol 7

  45. Kleinrock L (1976) Queueing systems. Wiley

  46. Kritikos K, Skrzypek P (2018) A review of serverless frameworks. In: 2018 IEEE/ACM international conference on utility and cloud computing companion (UCC companion). IEEE, pp 161–168

  47. Krivokuća M, Chou PA, Koroteev M (2020) A volumetric approach to point cloud compression–part ii: geometry compression. IEEE Trans Image Process 29:2217–2229. https://doi.org/10.1109/TIP.2019.2957853

    Article  Google Scholar 

  48. Kubernetes: Production-grade container orchestrator. https://kubernetes.io/

  49. Li Z, Zhu X, Gahm J, Pan R, Hu H, Begen AC, Oran D (2014) Probe and adapt: rate adaptation for HTTP video streaming at scale. IEEE J Selected Areas Commun 32(4):719–733. https://doi.org/10.1109/JSAC.2014.140405. ArXiv:1305.0510

    Article  Google Scholar 

  50. Maglo A, Lavoué G., Dupont F, Hudelot C (2015) 3d mesh compression: survey, comparisons, and emerging trends. ACM Comput Surv 47(3). https://doi.org/10.1145/2693443

  51. Mao H, Netravali R, Alizadeh M (2017) Neural adaptive video streaming with pensieve. In: Proceedings of the conference of the ACM special interest group on data communication, SIGCOMM ’17. https://doi.org/10.1145/3098822.3098843. Association for Computing Machinery, Los Angeles, pp 197–210

  52. Mehrabi A, Siekkinen M, Ylä-Jääski A (2017) Joint optimization of qoe and fairness through network assisted adaptive mobile video streaming. In: 2017 IEEE 13th International Conference On Wireless And Mobile Computing, Networking And Communications (WiMob). IEEE, pp 1–8

  53. Mehrabi A, Siekkinen M, Yla-Jaaski A (2019) Edge computing assisted adaptive mobile video streaming. IEEE Trans Mob Comput 18(4):787–800. https://doi.org/10.1109/TMC.2018.2850026

    Article  Google Scholar 

  54. Mekuria R, Blom K, Cesar P (2017) Design, implementation, and evaluation of a point cloud codec for tele-immersive video. IEEE Trans Circ Syst Video Technol 27(4):828–842. https://doi.org/10.1109/TCSVT.2016.2543039

    Article  Google Scholar 

  55. Misra K, Segall A, Horowitz M, Xu S, Fuldseth A, Zhou M (2013) An overview of tiles in HEVC. IEEE J Selected Topics Signal Process 7(6):969–977. https://doi.org/10.1109/JSTSP.2013.2271451. Conference Name: IEEE Journal of Selected Topics in Signal Processing

    Article  Google Scholar 

  56. New European Media (NEM): 5G-MEDIA Slice Definition. https://bscw.5g-ppp.eu/pub/bscw.cgi/d322688/NEM%20Networld2020%205G%20media%20slice%20V1-2_24092019.pdf (2019)

  57. NVIDIA: Multi-process service. https://docs.nvidia.com/deploy/mps/

  58. Orts-Escolano S, Rhemann C, Fanello S, Chang W, Kowdle A, Degtyarev Y, Kim D, Davidson PL, Khamis S, Dou M, Tankovich V, Loop C, Cai Q, Chou PA, Mennicken S, Valentin J, Pradeep V, Wang S, Kang SB, Kohli P, Lutchyn Y, Keskin C, Izadi S (2016) Holoportation: virtual 3D teleportation in real-time. In: Proceedings of the 29th annual symposium on user interface software and technology, UIST ’16. https://doi.org/10.1145/2984511.2984517. Association for Computing Machinery, Tokyo, pp 741–754

  59. Pantos R, May W (2017) HTTP live streaming. Tech. Rep. RFC8216, RFC Editor. https://doi.org/10.17487/RFC8216. https://www.rfc-editor.org/info/rfc8216

  60. Park J, Chou PA, Hwang JN (2018) Volumetric media streaming for augmented reality. In: 2018 IEEE Global communications conference (GLOBECOM), pp 1–6. https://doi.org/10.1109/GLOCOM.2018.8647537

  61. Paudyal P, Battisti F, Carli M (2016) Impact of video content and transmission impairments on quality of experience. Multimed Tools Applic 75(23):16461–16485. https://doi.org/10.1007/s11042-015-3214-0

    Article  Google Scholar 

  62. Robitza W, Garcia MN, Raake A (2017) A modular http adaptive streaming qoe model—candidate for itu-t p 1203 (“p nats”). In: 2017 Ninth international conference on quality of multimedia experience (QoMEX). IEEE, pp 1–6

  63. Sami Kekki EA (2018) MEC in 5G networks, ETSI White Paper No. 28. https://www.etsi.org/images/files/ETSIWhitePapers/etsi_wp28_mec_in_5G_FINAL.pdf

  64. Schatz R, Sackl A, Timmerer C, Gardlo B (2017) Towards subjective quality of experience assessment for omnidirectional video streaming. In: 2017 Ninth international conference on quality of multimedia experience (QoMEX), pp 1–6. https://doi.org/10.1109/QoMEX.2017.7965657. ISSN: 2472-7814

  65. Schatz R, Zabrovskiy A, Timmerer C (2019) Tile-based streaming of 8K omnidirectional video: subjective and objective QoE evaluation. In: 2019 Eleventh international conference on quality of multimedia experience (QoMEX), pp 1–6. https://doi.org/10.1109/QoMEX.2019.8743230. ISSN: 2472-7814

  66. Schoeffelen T (2020) Designing a serverless video streaming pipeline. https://medium.com/@tschoffelen/designing-a-serverless-video-streaming-pipeline-2d3828f3ccf8

  67. Schreer O, Feldmann I, Renault S, Zepp M, Worchel M, Eisert P, Kauff P (2019) Capture and 3D video processing of volumetric video. In: 2019 IEEE International conference on image processing (ICIP), pp 4310–4314. https://doi.org/10.1109/ICIP.2019.8803576. ISSN: 2381-8549

  68. Service Development Kit for Media-Type Virtualized Network Services in 5G Networks (to appear). IEEE Communication Magazine (2020)

  69. Seufert M, Egger S, Slanina M, Zinner T, Hoßfeld T, Tran-Gia P (2015) A survey on quality of experience of HTTP adaptive streaming. IEEE Commun Surveys Tutor 17(1):469–492. https://doi.org/10.1109/COMST.2014.2360940. Conference Name: IEEE Communications Surveys Tutorials

    Article  Google Scholar 

  70. Singla A, Göring S, Raake A, Meixner B, Koenen R, Buchholz T (2019) Subjective quality evaluation of tile-based streaming for omnidirectional videos. In: Proceedings of the 10th ACM multimedia systems conference, MMSys ’19. https://doi.org/10.1145/3304109.3306218. Association for Computing Machinery, Amherst, pp 232–242

  71. Skupin R, Sanchez Y, Podborski D, Hellge C, Schierl T (2017) Viewport-dependent 360 degree video streaming based on the emerging Omnidirectional Media Format (OMAF) standard. In: 2017 IEEE international conference on image processing (ICIP), pp 4592–4592. https://doi.org/10.1109/ICIP.2017.8297155. ISSN: 2381-8549

  72. Sodagar I (2011) The MPEG-DASH standard for multimedia streaming over the internet. IEEE MultiMedia 18(4):62–67. https://doi.org/10.1109/MMUL.2011.71. Conference Name: IEEE MultiMedia

    Article  Google Scholar 

  73. Soltanian A, Naboulsi D, Salahuddin MA, Glitho R, Elbiaze H, Wette C (2018) Ads: adaptive and dynamic scaling mechanism for multimedia conferencing services in the cloud. In: 2018 15th IEEE Annual consumer communications & networking conference (CCNC). IEEE, pp 1–6

  74. Spiteri K, Urgaonkar R, Sitaraman RK (2016) BOLA: near-optimal bitrate adaptation for online videos. arXiv:1601.06748 [cs]

  75. Sterzentsenko V, Karakottas A, Papachristou A, Zioulis N, Doumanoglou A, Zarpalas D, Daras P (2018) A low-cost, flexible and portable volumetric capturing system, 200–207. https://doi.org/10.1109/SITIS.2018.00038

  76. Sterzentsenko V, Karakottas A, Papachristou A, Zioulis N, Doumanoglou A, Zarpalas D, Daras P (2018) A low-cost, flexible and portable volumetric capturing system. In: 2018 14th International conference on signal-image technology & internet-based systems (SITIS). IEEE, pp 200–207

  77. Sullivan G, Ohm JR, Han WJ, Wiegand T (2012) Overview of the high efficiency video coding (HEVC) standard. IEEE Trans Circ Syst Video Technol 22(12):1649–1668. https://doi.org/10.1109/TCSVT.2012.2221191

    Article  Google Scholar 

  78. Sun L, Duanmu F, Liu Y, Wang Y, Ye Y, Shi H, Dai D (2018) Multi-path multi-tier 360-degree video streaming in 5g networks. In: Proceedings of the 9th ACM multimedia systems conference, MMSys ’18. Association for Computing Machinery, pp 162–173. https://doi.org/10.1145/3204949.3204978. Event-place: Amsterdam, Netherlands

  79. Tian Y, Babcock R, Taylor C, Ji Y (2018) A new live video streaming approach based on amazon s3 pricing model. In: 2018 IEEE 8th Annual computing and communication workshop and conference (CCWC), pp 321–328. https://doi.org/10.1109/CCWC.2018.8301615

  80. van der Hooft J, Wauters T, De Turck F, Timmerer C, Hellwagner H (2019) Towards 6DoF HTTP adaptive streaming through point cloud compression. In: Proceedings of the 27th ACM international conference on multimedia, MM ’19. https://doi.org/10.1145/3343031.3350917. Association for Computing Machinery, Nice, pp 2405–2413

  81. Wien M, Boyce JM, Stockhammer T, Peng WH (2019) Standardization status of immersive video coding. IEEE J Emerg Selected Topics Circ Syst 9(1):5–17

    Article  Google Scholar 

  82. Xie L, Xu Z, Ban Y, Zhang X, Guo Z (2017) 360probdash: improving qoe of 360 video streaming using tile-based http adaptive streaming. In: Proceedings of the 2017 ACM on multimedia conference, MM 2017, Mountain View, CA, USA, October 23-27, 2017. ACM, pp 315–323. https://doi.org/10.1145/3123266.3123291

  83. Xin Z, Fu S (2019) User-centric qoe model of visual perception for mobile videos. Vis Comput 35(9):1245–1254

    Article  Google Scholar 

  84. Yamasaki T, Aizawa K (2010) Patch-based compression for time-varying meshes. In: 2010 IEEE International conference on image processing, pp 3433–3436. https://doi.org/10.1109/ICIP.2010.5652911

  85. Yates RD, Goodman DJ (2014) Probability and stochastic processes: a friendly introduction for electrical and computer engineers. Wiley

  86. Zadtootaghaj S, Schmidt S, Möller S (2018) Modeling gaming qoe: towards the impact of frame rate and bit rate on cloud gaming. In: 2018 Tenth international conference on quality of multimedia experience (QoMEX). IEEE, pp 1–6

  87. Zhang G, Lee JYB (2019) Ensemble adaptive streaming - a new paradigm to generate streaming algorithms via specializations. IEEE Transactions on Mobile Computing, pp 1–1. https://doi.org/10.1109/TMC.2019.2909202. Conference Name: IEEE Transactions on Mobile Computing

  88. Zhang M, Zhu Y, Zhang C, Liu J (2019) Video processing with serverless computing: a measurement study. In: Proceedings of the 29th ACM workshop on network and operating systems support for digital audio and video, pp 61–66

  89. Zhang W, Chen Q, Fu K, Zheng N, Huang Z, Leng J, Li C, Zheng W, Guo M (2020) Towards QoS-aware and resource-efficient GPU microservices based on spatial multitasking GPUs in datacenters. arXiv:2005.02088

  90. Zheng Y, Wu D, Ke Y, Yang C, Chen M, Zhang G (2016) Online cloud transcoding and distribution for crowdsourced live game video streaming. IEEE Trans Circ Syst Video Technol 27(8):1777–1789

    Article  Google Scholar 

  91. Zioulis N, Alexiadis D, Doumanoglou A, Louizis G, Apostolakis K, Zarpalas D, Daras P (2016) 3D tele-immersion platform for interactive immersive experiences between remote users. In: 2016 IEEE International conference on image processing (ICIP), pp 365–369. https://doi.org/10.1109/ICIP.2016.7532380. ISSN: 2381-8549

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Acknowledgements

This work has been realized in the context of the 5G-MEDIA project (www.5gmedia.eu), which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 761699.

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  1. Visual Computing Lab (VCL), Information Technologies Institute (ITI), Centre for Research and Technology - Hellas (CERTH), Thessaloniki, Greece

    Konstantinos Konstantoudakis, Alexandros Doumanoglou, Nikolaos Zioulis, Kyriaki Christaki, Petros Drakoulis, Emmanouil Christakis, Dimitrios Zarpalas & Petros Daras

  2. Hybrid Cloud, Cloud and Data Technologies, IBM Research, Haifa, Israel

    David Breitgand & Avi Weit

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  1. Konstantinos Konstantoudakis
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Konstantoudakis, K., Breitgand, D., Doumanoglou, A. et al. Serverless streaming for emerging media: towards 5G network-driven cost optimization. Multimed Tools Appl 81, 12211–12250 (2022). https://doi.org/10.1007/s11042-020-10219-7

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