MapReduce-Based Distributed Video Encoding Using Content-Aware Video Segmentation and Scheduling
The objective of this paper is to improve the overall performance of distributed encoding, with a particular focus on encoding speed. The proposed scheme consists of content-aware video segmentation and scheduling that consists of two major parts. In the first part, segmentation is carried out with...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2016-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/7588152/ |
| _version_ | 1818877164719702016 |
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| author | Myunghoon Jeon Namgi Kim Byoung-Dai Lee |
| author_facet | Myunghoon Jeon Namgi Kim Byoung-Dai Lee |
| author_sort | Myunghoon Jeon |
| collection | DOAJ |
| description | The objective of this paper is to improve the overall performance of distributed encoding, with a particular focus on encoding speed. The proposed scheme consists of content-aware video segmentation and scheduling that consists of two major parts. In the first part, segmentation is carried out with greater efficiency by considering changes in the video content, and in the second part, the segment assignment process is carried out using an efficient scheduling scheme that changes the encoding order of the segments. We measured the content similarity by using the sum of absolute difference algorithm and then applied a threshold to define the degree of change in similarity. The video was segmented based on the extent to which the similarity had changed, and the encoding order of the segments was rearranged to perform distributed encoding. Finally, this paper introduces the MapReduce-based distributed video encoding, using the content-aware video segmentation and scheduling described above, and presents the results of the performance using this scheme, which indicate that the proposed scheme increases the bitrate by a maximum of 2.9% over existing segmentation schemes, and also increases the speed by a maximum of 15.3%. |
| first_indexed | 2024-12-19T13:53:56Z |
| format | Article |
| id | doaj.art-e142adfc5f084d049a08296f3a10e674 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T13:53:56Z |
| publishDate | 2016-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-e142adfc5f084d049a08296f3a10e6742022-12-21T20:18:38ZengIEEEIEEE Access2169-35362016-01-0146802681510.1109/ACCESS.2016.26165407588152MapReduce-Based Distributed Video Encoding Using Content-Aware Video Segmentation and SchedulingMyunghoon Jeon0Namgi Kim1Byoung-Dai Lee2https://orcid.org/0000-0002-4028-6168Computer Science Department, Kyonggi University, Suwon, South KoreaComputer Science Department, Kyonggi University, Suwon, South KoreaComputer Science Department, Kyonggi University, Suwon, South KoreaThe objective of this paper is to improve the overall performance of distributed encoding, with a particular focus on encoding speed. The proposed scheme consists of content-aware video segmentation and scheduling that consists of two major parts. In the first part, segmentation is carried out with greater efficiency by considering changes in the video content, and in the second part, the segment assignment process is carried out using an efficient scheduling scheme that changes the encoding order of the segments. We measured the content similarity by using the sum of absolute difference algorithm and then applied a threshold to define the degree of change in similarity. The video was segmented based on the extent to which the similarity had changed, and the encoding order of the segments was rearranged to perform distributed encoding. Finally, this paper introduces the MapReduce-based distributed video encoding, using the content-aware video segmentation and scheduling described above, and presents the results of the performance using this scheme, which indicate that the proposed scheme increases the bitrate by a maximum of 2.9% over existing segmentation schemes, and also increases the speed by a maximum of 15.3%.https://ieeexplore.ieee.org/document/7588152/Distributed video encodingMapReduceresource schedulingvideo segmentation |
| spellingShingle | Myunghoon Jeon Namgi Kim Byoung-Dai Lee MapReduce-Based Distributed Video Encoding Using Content-Aware Video Segmentation and Scheduling IEEE Access Distributed video encoding MapReduce resource scheduling video segmentation |
| title | MapReduce-Based Distributed Video Encoding Using Content-Aware Video Segmentation and Scheduling |
| title_full | MapReduce-Based Distributed Video Encoding Using Content-Aware Video Segmentation and Scheduling |
| title_fullStr | MapReduce-Based Distributed Video Encoding Using Content-Aware Video Segmentation and Scheduling |
| title_full_unstemmed | MapReduce-Based Distributed Video Encoding Using Content-Aware Video Segmentation and Scheduling |
| title_short | MapReduce-Based Distributed Video Encoding Using Content-Aware Video Segmentation and Scheduling |
| title_sort | mapreduce based distributed video encoding using content aware video segmentation and scheduling |
| topic | Distributed video encoding MapReduce resource scheduling video segmentation |
| url | https://ieeexplore.ieee.org/document/7588152/ |
| work_keys_str_mv | AT myunghoonjeon mapreducebaseddistributedvideoencodingusingcontentawarevideosegmentationandscheduling AT namgikim mapreducebaseddistributedvideoencodingusingcontentawarevideosegmentationandscheduling AT byoungdailee mapreducebaseddistributedvideoencodingusingcontentawarevideosegmentationandscheduling |