Chenwei Song, W. Shen, Lianqiang Sun, Zhou Lei, Weimin Xu
{"title":"基于MapReduce的分布式视频转码","authors":"Chenwei Song, W. Shen, Lianqiang Sun, Zhou Lei, Weimin Xu","doi":"10.1109/ICIS.2014.6912152","DOIUrl":null,"url":null,"abstract":"Video transcoding is an important job in video processing and network service. With the improvement of devices and the Internet, the size of the video increases rapidly so that it takes a lot of resources to transcode. Low efficiency, high cost of upgrading hardware and low capacity of processing failure are problems of the traditional method of serial transcoding. Distributed transcoding can resolve these problems. To reduce the time of serial processing and be able to deal with the fault, this paper means to model a distributed video transcoding system which is based on MapReduce, an open source distribute computing model, and FFmpeg.","PeriodicalId":237256,"journal":{"name":"2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS)","volume":"211 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Distributed video transcoding based on MapReduce\",\"authors\":\"Chenwei Song, W. Shen, Lianqiang Sun, Zhou Lei, Weimin Xu\",\"doi\":\"10.1109/ICIS.2014.6912152\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Video transcoding is an important job in video processing and network service. With the improvement of devices and the Internet, the size of the video increases rapidly so that it takes a lot of resources to transcode. Low efficiency, high cost of upgrading hardware and low capacity of processing failure are problems of the traditional method of serial transcoding. Distributed transcoding can resolve these problems. To reduce the time of serial processing and be able to deal with the fault, this paper means to model a distributed video transcoding system which is based on MapReduce, an open source distribute computing model, and FFmpeg.\",\"PeriodicalId\":237256,\"journal\":{\"name\":\"2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS)\",\"volume\":\"211 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIS.2014.6912152\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIS.2014.6912152","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Video transcoding is an important job in video processing and network service. With the improvement of devices and the Internet, the size of the video increases rapidly so that it takes a lot of resources to transcode. Low efficiency, high cost of upgrading hardware and low capacity of processing failure are problems of the traditional method of serial transcoding. Distributed transcoding can resolve these problems. To reduce the time of serial processing and be able to deal with the fault, this paper means to model a distributed video transcoding system which is based on MapReduce, an open source distribute computing model, and FFmpeg.