skip to main content
research-article

Scheduling a Video Transcoding Server to Save Energy

Published: 24 February 2015 Publication History

Abstract

Recent popular streaming services such as TV Everywhere, N-Screen, and dynamic adaptive streaming over HTTP (DASH) need to deliver content to the wide range of devices, requiring video content to be transcoded into different versions. Transcoding tasks require a lot of computation, and each task typically has its own real-time constraint. These make it difficult to manage transcoding, but the more efficient use of energy in servers is an imperative. We characterize transcoding workloads in terms of deadlines and computation times, and propose a new dynamic voltage and frequency scaling (DVFS) scheme that allocates a frequency and a workload to each CPU with the aim of minimizing power consumption while meeting all transcoding deadlines. This scheme has been simulated, and also implemented in a Linux transcoding server, in which a frontend node distributes transcoding requests to heterogeneous backend nodes. This required a new protocol for communication between nodes, a DVFS management scheme to reduce power consumption and thread management and scheduling schemes which ensure that transcoding deadlines are met. Power measurements show that this approach can reduce system-wide energy consumption by 17% to 31%, compared with the Linux Ondemand governor.

References

[1]
Amazon Elastic Computer. 2013. http://aws.amazon.com/ec2/.
[2]
American Power Convention. 2003. Determining total cost of ownership for data centers and network room infrastructure. White Paper.
[3]
A. Ashraf, F. Jokhio, T. Deneke, S. Lafond, I. Porres, and J. Lilius. 2013. Stream based admission control and scheduling for video transcoding in cloud computing. In Proceedings of the IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing. 482--489.
[4]
H. Aydin and Q. Yang. 2003. Energy-aware partitioning for multiprocessor real-time systems. In Proceedings of the IEEE Parallel and Distributed Processing Symposium. 1--9.
[5]
L. Bertinia, J. Leitea, and D. Mosse. 2010. Power optimization for dynamic configuration in heterogeneous web server clusters. J. Syst. Softw. 83, 4, 585--598.
[6]
D. Bovet and M. Cesati. 2005. Understanding the Linux Kernel. O'Reilly.
[7]
J. Chen and C. Kuo. 2007. Energy-efficient scheduling for real-time systems on dynamic voltage scaling (DVS) platforms. In Proceedings of the IEEE Real-Time Computing Systems and Applications. 28--38.
[8]
J. Chen and T. Kuo. 2005. Energy-efficient scheduling of periodic real-time tasks over homogeneous multiprocessors. In Proceedings of the IEEE Conference on Power-Aware Real-Time Computing. 30--35.
[9]
Cisco Visual Networking Index. 2013. http://www.cisco.com/en/US/solutions/collateral/ns341/ns525/ns537/ns705/ns827/white_paper_c11520862.pdf.
[10]
A. Dan, D. Sitaram, and P. Shahabuddin. 1996. Dynamic batching policies for an on-demand video server. ACM/Springer Multimed. Syst. J. 4, 3, 112--121.
[11]
M. Digalwar, S. Mohan, and B. Raveendran. 2013. Energy aware real time scheduling algorithm for mixed task set. In Proceedings of the IEEE Advanced Electronic Systems Conference. 325--327.
[12]
A. Garcia, H. Kalva, and B. Furht. 2010. A study of transcoding on cloud environments for video content delivery. In Proceedings of the ACM Multimedia Workshop on Mobile Cloud Media Computing. 13--18.
[13]
A. Horvath and K. Skadron. 2008. Multi-mode energy management for multi-tier server clusters. In Proceedings of the ACM International Conference on Parallel Architectures and Compilation Techniques. 270--279.
[14]
T. Horvath, T. Abdelzaher, K. Skadron, and X. Liu. 2007. Dynamic voltage scaling in multitier web servers with end-to-end delay control. IEEE Trans. Comput. 56, 4, 444--458.
[15]
J. Hsiao, H. Ping, and M. Chen. 2008. Versatile transcoding proxy for internet content adaptation. IEEE Trans. Multimed. 10, 4, 646--658.
[16]
J. Huang and M. Chen. 2007. A QoS-aware and energy-conserving transcoding proxy using on-demand data broadcasting. IEEE Trans. Mobile Comput. 6, 8, 971--987.
[17]
H. Hung and M. Chen. 2009. On designing a shortest-path-based cache replacement in a transcoding proxy. ACM/Springer Multimed. Syst. J. 15, 2, 49--62.
[18]
F. Jokhio, A. Ashraf, S. Lafond, and J. Lilius. 2013. A computation and storage trade-off strategy for cost-efficient video transcoding in the cloud. In Proceedings of the IEEE EUROMICRO Conference on Software Engineering and Advanced Applications. 365--372.
[19]
M. Kim and M. Song. 2012. Saving energy in video servers by the use of multispeed disks. IEEE Trans. Circ. Syst. Video Tech. 22, 4, 567--580.
[20]
S. Ko, S. Park, and H. Han. 2013. Design analysis for real-time video transcoding on cloud systems. In Proceedings of the ACM Symposium on Applied Computing. 1610--1615.
[21]
T. Kolpe, A. Zhai, and S. Sapatnekar. 2011. Enabling improved power management in multicore processors through clustered DVFS. In Proceedings of the ACM Design, Automation Test in Europe Conference. 1--6.
[22]
Z. Li, Y. Huang, G. Liu, F. Wang, Z. Zhang, and Y. Dai. 2012. Cloud transcoder: Bridging the format and resolution gap between internet videos and mobile devices. In Proceedings of the ACM NOSSDAV. 33--38.
[23]
G. Lim, C. Min, and Y. Eom. 2012. Load-balancing for improving user responsiveness on multicore embedded systems. In Proceedings of the Linux Symposium. 25--33.
[24]
Y. Ling, T. Mullen, and X. Lin. 2000. Analysis of optimal thread pool size. Oper. Syst. Rev. 34, 2, 42--55.
[25]
D. Liu, S. Chen, and B. Shen. 2006. AMTrac: Adaptive Meta-Caching for Transcoding. In Proceedings of the ACM NOSSDAV.
[26]
D. Liu, F. Li, S. Chen, and B. Shen. 2012. Building an efficient transcoding overlay for P2P streaming to heterogeneous devices. ACM Trans. Multimed. Comput. Commun. Appl. 5, 15, 333--335.
[27]
Lpsolver. 2013. http://lpsolve.sourceforge.net/5.5.
[28]
H. Ma, B. Seo, and R. Zimmermann. 2014. Dynamic scheduling on video transcoding for MPEG DASH in the cloud environment. In Proceedings of the ACM International Conference on Multimedia Systems. 227--238.
[29]
Mov-avi. 2014. http://online.movavi.com.
[30]
Online-convert. 2014. http://www.online-convert.com.
[31]
Online13 Power-calculator. 2014. http://www.extreme.outervision.com/psucalculator.jsp.
[32]
V. Pallipadi and A. Starikovskiy. 2006. The ondemand governor: Past, present, and future. In Proceedings of the Linux Symposium. 223--238.
[33]
P. Pillai and K. G. Shin. 2001. Real-time dynamic voltage scaling for low-power embedded operating systems. In Proceedings of the ACM Symposium on Operating Systems Principles. 89--102.
[34]
D. Pisinger. 1995. Algorithms for knapsack problems. Ph.D. Dissertation, University of Copenhagen.
[35]
A. Qu, K. Li, M. Kitsuregawa, and T. Nanya. 2007. An optimal solution for caching multimedia objects in transcoding proxies. Comput. Commun. 30, 8, 1802--1810.
[36]
C. Rusu, A. Ferreira, C. Scordino, and A. Watson. 2006. Energy-efficient real-time heterogeneous server clusters. In Proceedings of the IEEE International Conference on Real-Time and Embedded Technology and Applications Symposium. 418--428.
[37]
C. Santana, J. Leite, and D. Mosse. 2011. Power management by load forecasting in web server clusters. J. Cluster Comput. 14, 4, 471--481.
[38]
S. Seiden. 2002. On the online bin packing problem. J. ACM 49, 5, 640--671.
[39]
V. Sharma, A. Thomas, T. Abdelzaher, and K. Skadron. 2003. Power-aware QoS management in web servers. In Proceedings of the IEEE RTSS. 63--72.
[40]
B. Shen, S. Lee, and S. Basu. 2004. Caching Strategies in transcoding-enabled proxy systems for streaming media distribution networks. IEEE Trans. Multimed. 6, 2, 375--386.
[41]
I. Shin and K. Koh. 2004. Hybrid transcoding for QoS adaptive video-on-demand services. IEEE Trans. Consum. Elect. 50, 2, 732--736.
[42]
M. Song, Y. Lee, and E. Kim. 2013. Data prefetching to reduce energy use by heterogeneous disk arrays in video servers. In Proceeding of the ACM Workshop on Network and Operating Systems Support for Digital Audio and Video. 1--6.
[43]
M. Song, Y. Lee, and J. Park. 2014. CPU power management in video transcoding servers. in Proceedings of the ACM NOSSDAV. 91--96.
[44]
M. Song, J. Sim, J. Go, B. Lee, and S. Park. 2009. Balancing MPEG transcoding with storage in multiple-quality video-on-demand services. ETRI J. 31, 3, 333--335.
[45]
T. Stockhammer. 2011. Dynamic adaptive streaming over HTTP: Standards and design principles. In Proceedings of the ACM International Conference on Multimedia Systems. 133--144.
[46]
X. Tang, F. Zhang, and S. Chanson. 2002. Streaming media caching algorithms for transcoding proxies. In Proceedings of the International Conference on Parallel Processing. 287--295.
[47]
P. H. Tseng, P. C. Hsiu, C. C. Pan, and T. W. Kuo. 2014. User-centric energy-efficient scheduling on multi-core mobile devices. In Proceedings of the ACM Design, Automation Test in Europe Conference. 1--6.
[48]
VLC. 2014. https://wiki.videolan.org/Transcode/.
[49]
C. Xian, Y. Lu, and Z. Li. 2007. Energy-aware scheduling for realtime multiprocessor systems with uncertain task execution time. In Proceedings of the ACM DAC. 264--669.
[50]
YouConvertIt. 2014. http://www.youconvertit.com.
[51]
Zencoder. 2014. http://www.zencoder.com.
[52]
W. Zhang, Y. Wen, J. Cai, and D. Wu. 2014. Towards transcoding as a service in multimedia cloud: Energy-efficient job dispatching algorithm. IEEE Trans. Vehic. Tech. 63, 5 (June 2014), 2002--2012.
[53]
Q. Zhu, Z. Chen, L. Tan, Y. Zhou, K. Keeton, and J. Wilkes. 2005. Hibernator: Helping disk arrays sleep through the winter. ACM Oper. Syst. Rev. 39, 5, 177--190.
[54]
Q. Zhu and Y. Zhou. 2005. Power aware storage cache management. IEEE Trans. Comput. 54, 5, 587--602.

Cited By

View all
  • (2022)Quality-Oriented Task Allocation and Scheduling in Transcoding Servers With Heterogeneous ProcessorsIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2021.307415832:3(1667-1680)Online publication date: Mar-2022
  • (2022)Quality-Aware Transcoding Task Allocation Under Limited Power in Live-Streaming SystemsIEEE Systems Journal10.1109/JSYST.2021.310352616:3(4368-4379)Online publication date: Sep-2022
  • (2021)Reward-Oriented Task Offloading Under Limited Edge Server Power for Multiaccess Edge ComputingIEEE Internet of Things Journal10.1109/JIOT.2021.30654298:17(13425-13438)Online publication date: 1-Sep-2021
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Transactions on Multimedia Computing, Communications, and Applications
ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 11, Issue 2s
Special Issue on MMSYS 2014
February 2015
138 pages
ISSN:1551-6857
EISSN:1551-6865
DOI:10.1145/2739966
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 February 2015
Accepted: 01 November 2014
Revised: 01 September 2014
Received: 01 May 2014
Published in TOMM Volume 11, Issue 2s

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Multimedia systems
  2. dynamic voltage and frequency scaling
  3. low-power systems

Qualifiers

  • Research-article
  • Research
  • Refereed

Funding Sources

  • industrial strategic technology development program (10041971, Development of Power Efficient High-Performance Multimedia Contents Service Technology using Context-Adapting Distributed Transcoding)
  • Ministry of Knowledge Economy (MKE, Korea)
  • ICT R&D program of MSIP/IITP. [200352423, Component based Design Theory and Control Kernel for CPS (Cyber-Physical System)]
  • Inha University

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)10
  • Downloads (Last 6 weeks)0
Reflects downloads up to 19 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2022)Quality-Oriented Task Allocation and Scheduling in Transcoding Servers With Heterogeneous ProcessorsIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2021.307415832:3(1667-1680)Online publication date: Mar-2022
  • (2022)Quality-Aware Transcoding Task Allocation Under Limited Power in Live-Streaming SystemsIEEE Systems Journal10.1109/JSYST.2021.310352616:3(4368-4379)Online publication date: Sep-2022
  • (2021)Reward-Oriented Task Offloading Under Limited Edge Server Power for Multiaccess Edge ComputingIEEE Internet of Things Journal10.1109/JIOT.2021.30654298:17(13425-13438)Online publication date: 1-Sep-2021
  • (2020)Bitrate Adaptation for Video Streaming Services in Edge Caching SystemsIEEE Access10.1109/ACCESS.2020.30115178(135844-135852)Online publication date: 2020
  • (2019)Adaptive Wireless Video Streaming Based on Edge Computing: Opportunities and ApproachesIEEE Transactions on Services Computing10.1109/TSC.2018.282842612:5(685-697)Online publication date: 1-Sep-2019
  • (2019)Dynamic Priority-Based Resource Provisioning for Video Transcoding With Heterogeneous QoSIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2018.284035129:5(1515-1529)Online publication date: 2-May-2019
  • (2019)Video Quality Adaptation for Limiting Transcoding Energy Consumption in Video ServersIEEE Access10.1109/ACCESS.2019.2939007(1-1)Online publication date: 2019
  • (2018)QoE-Aware Video Storage Power Management Based on Hot and Cold Data ClassificationProceedings of the 28th ACM SIGMM Workshop on Network and Operating Systems Support for Digital Audio and Video10.1145/3210445.3210452(7-12)Online publication date: 12-Jun-2018
  • (2018)Quality of Experience-Centric Management of Adaptive Video Streaming ServicesACM Transactions on Multimedia Computing, Communications, and Applications10.1145/316526614:2s(1-29)Online publication date: 1-May-2018
  • (2017)Resource Provisioning and Profit Maximization for Transcoding in CloudsIEEE Transactions on Multimedia10.1109/TMM.2016.263501919:4(836-848)Online publication date: 1-Apr-2017
  • Show More Cited By

View Options

Login options

Full Access

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media