Data Placement in Heterogeneous Storage of Short Videos
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32797
Data Placement in Heterogeneous Storage of Short Videos

Authors: W. Jaipahkdee, C. Srinilta

Abstract:

The overall service performance of I/O intensive system depends mainly on workload on its storage system. In heterogeneous storage environment where storage elements from different vendors with different capacity and performance are put together, workload should be distributed according to storage capability. This paper addresses data placement issue in short video sharing website. Workload contributed by a video is estimated by the number of views and life time span of existing videos in same category. Experiment was conducted on 42,000 video titles in six weeks. Result showed that the proposed algorithm distributed workload and maintained balance better than round robin and random algorithms.

Keywords: data placement, heterogeneous storage system, YouTube, short videos

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1085133

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1439

References:


[1] "YouTube", http://www.youtube.com/
[2] R.J. Honicky and E.L. Miller. Replication under scalable hashing: a family of algorithms for scalable decentralized data distribution. In Proceedings of 18th International Parallel and Distributed Processing Symposium (IPDPS -04), Santa Fe, NM, Apr. 2004
[3] L.W. Lee, P. Scheuermann and R. Vingralek. File assignment in parallel I/O systems with minimal variance of service time. IEEE Trans. on Computers, Vol 49, No.2. (2000) 127-140
[4] P. Scheuermann, G. Weikum and P. Zabback. Data partitioning and load balancing in parallel disk systems. The VLDB Journal - The International Journal on Very Large Data Bases, Vol. 7, No. 1. (1998) 48-66
[5] D. Feng and L. Qin. Adaptive Object Placement in Object-Based Storage Systems with Minimal Blocking Probability. In Proceedings of the 20th International Conference on Advanced Information Networking and Applications (AINA ÔÇÿ06), Vienna, Austria, Apr. 2006
[6] X. Cheng, C. Dale and J. Liu. Statistics and social network of youtube videos. In Proceedings of the 16th IEEE International Workshop on Quality of Service (IWQoS -08), Enschede, Netherlands, Jun. 2008
[7] M. Factor, K. Meth, D. Naor, O. Rodeh and J. Satran. Object Storage: The Future Building Block for Storage Systems. In Proceedings of the Second International IEEE Symposium on Emergence of Globally Distributed Data, Sardinia, Italy, Jun. 2005
[8] K. S. Tang, K. T. KO, S. Chan and E. Wong, "Optimal file placement in VOD system using genetic algorithm", IEEE Industrial Electronics, Vol 48, No.5. (2001) 891-897
[9] W.K.S. Tang, E.W.M. Wong, S. Chan and K.-T. Ko, "Optimal video placement scheme for batching VOD services", IEEE Trans. on Broadcasting, Vol 50, No.1. (2004) 16-25
[10] A. Goel, C. Shahabi, D. S. Yao and R. Zimmermann. SCADDAR: An Efficient Randomized Technique to Reorganize Continuous Media Blocks. In Proceedings of The 18th IEEE International Conference on Data Engineering (ICDE -02), San Jose, CA, Feb. 2002
[11] S. A. Weil, S. A. Brandt, E. L. Miller and C. Maltzahn. CRUSH: Controlled, Scalable, Decentralized Placement of Replicated Data. In Proceedings of the 2006 ACM/IEEE Conference on Supercomputing (SC -06), Tampa, FL, Nov. 2006.
[12] "Alexa Top 500 Global Sites", http://www.alexa.com/topsites.
[13] "YouTube Metadata", http://code.google.com/apis/youtube/2.0/reference.html.