• Title/Summary/Keyword: 트랜스코딩(transcoding)

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Load Distribution Method based on Transcoding Time Estimation on Distributed Transcoding Environments (분산 트랜스코딩 환경에서 트랜스코딩 시간 예측 기반 부하 분산 기법)

  • Kim, Jong-Woo;Seo, Dong-Mahn;Jung, In-Bum
    • Journal of KIISE:Computer Systems and Theory
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    • v.37 no.4
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    • pp.195-204
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    • 2010
  • Due to improved wireless communication technologies, it is possible to provide multimedia streaming service for mobile device clients like PDAs and cellphones. Wireless networks are serviced on low bandwidth channels and mobile devices work on limited hardware specifications. In these conditions, transcoding technologies are needed to adapt the media for streaming services to given mobile environments. To transcode from the source media to the target media for corresponding grades, transcoding servers perform transcoding jobs as exhausting their resources. Since various transcoding loads occur according to the target transconding grades, an effective transcoding load balancing policy is required among transcoding servers. In addition to transcoding process, servers should maintain QoS streams for mobile clients for total serviced times. It requires real-time requirements to support QoS for various mobile clients. In this paper, a new transcoding load distribution method is proposed. The proposed method can be driven for fair load balance between distributed transcoding servers. Based on estimated transcoding time, movie information and target transcoding bit-rate, it provides fair transcoding load distribution and also performs admission control to support QoS streams for mobile clients.

Transcoding Load Estimation Method for Load Balance on Distributed Transcoding Environments (분산 트랜스코딩 환경에서 부하 균형을 위한 트랜스코딩 부하 예측 기법)

  • Seo, Dong-Mahn;Heo, Nan-Sok;Kim, Jong-Woo;Jung, In-Bum
    • Journal of KIISE:Computer Systems and Theory
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    • v.35 no.9_10
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    • pp.466-475
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    • 2008
  • Owing to the improved wireless communication technologies, it is possible to provide streaming service of multimedia with PDAs and mobile phones in addition to desktop PCs. Since mobile client devices have low computing power and low network bandwidth due to wireless network, the transcoding technology to adapt media for mobile client devices considering their characteristics is necessary. Transcoding servers transcode the source media to the target media within corresponding grades and provide QoS in real-time. In particular, an effective load balancing policy for transcoding servers is inevitable to support QoS for large scale mobile users. In this paper, the transcoding load estimation algorithm is proposed for load balance on the distributed transcoding environments. The proposed algorithm estimates transcoding time from transcoding server information, movie information and target transcoding bit-rate. The estimated transcoding time is proved based on experiments.

A Degraded Quality Service Policy for reducing the transcoding loads in a Transcoding Proxy (트랜스코딩 프록시에서 트랜스코딩 부하를 줄이기 위한 낮은 품질 서비스 정책)

  • Park, Yoo-Hyun
    • The KIPS Transactions:PartA
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    • v.16A no.3
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    • pp.181-188
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    • 2009
  • Transcoding is one of core techniques that implement VoD services according to QoS. But it consumes a lot of CPU resource. A transcoding proxy transcodes multimedia objects to meet requirements of various mobile devices and caches them to reuse later. In this paper, we propose a service policy that reduces the load of transcoding multimedia objects by degrading QoS in a transcoding proxy. Due to the tradeoff between QoS and the load of a proxy system, a transcoding proxy provides lower QoS than a client's requirement so that it can accomodate more clients.

A Dual Transcoding Method for Retaining QoS of Video Streaming Services under Restricted Computing Resources (동영상 스트리밍 서비스의 QoS유지를 위한 듀얼 트랜스코딩 기법)

  • Oh, Doohwan;Ro, Won Woo
    • KIPS Transactions on Computer and Communication Systems
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    • v.3 no.7
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    • pp.231-240
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    • 2014
  • Video transcoding techniques provide an efficient mechanism to make a video content adaptive to the capabilities of a variety of clients. However, it is hard to provide an appropriate quality-of-service(QoS) to the clients owing to heavy workload on transcoding operations. In light of this fact, this paper presents the dual transcoding method in order to guarantee QoS in streaming services by maximizing resource usage in a transcoding server equipped with both CPU and GPU computing units. The CPU and GPU computing units have different architectural features. The proposed method speculates workload of incoming transcoding requests and then schedules the requests either to the CPU or GPU accordingly. From performance evaluation, the proposed dual transcoding method achieved a speedup of 1.84 compared with traditional transcoding approach.

Design and Implementation of Low-Power Transcoding Servers Based on Transcoding Task Distribution (트랜스코딩 작업의 분배를 활용한 저전력 트랜스코딩 서버 설계 및 구현)

  • Lee, Dayoung;Song, Minseok
    • The Journal of Korean Institute of Next Generation Computing
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    • v.15 no.4
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    • pp.18-29
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    • 2019
  • A dynamic adaptive streaming server consumes high processor power because it handles a large amount of transcoding operations at a time. For this purpose, multi-processor architecture is mandatory for which effective transcoding task distribution strategies are essential. In this paper, we present the design and implementation details of the transcoding workload distribution schemes at a 2-tier (frontend node and backend node) transcoding server. For this, we implemented four schemes: 1) allocation of transcoding tasks to appropriate back-end nodes, 2) task scheduling in the back-end node and 3) the communication between front-end and back-end nodes. Experiments were conducted to compare the estimated and the actual power consumption in a real testbed to verify the efficacy of the system. It also proved that the system can reduce the load on each node to optimize the power and time used for transcoding.

A Study on the Distributed Transcoding System using Secret Sharing Techniques (비밀분산기법을 이용한 분산 트랜스코딩 시스템 연구)

  • Song, You-Jin;Gu, Seokmo;Kim, Yei-Chang
    • Journal of Digital Convergence
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    • v.12 no.11
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    • pp.233-239
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    • 2014
  • Ultra high-resolution content, the file size is very large, therefore existing encoding techniques, it is not possible to transmit via the network. Efficient use of the network encoder HEVC corporation can be transferred. Compression requires a lot of time because it requires a distributed transcoding system. Distributed transcoding system is a distributed data store, and then encoded using a large number of nodes. The disadvantage of distributed transcoding system for distributed information is exposed or vulnerable to attack by internal managers. In this paper, when the super high definition content transcoding, distributed transcoding system does not guarantee the confidentiality of the problem to solve. We are using SNA, HEVC encoded content data encrypted using the secret distributing scheme was. Consequently, secure shared transcoding is possible, the internal administrator could prevent the attack.

Resource Weighted Load Distribution Policy for Effective Transcoding Load Distribution (효과적인 트랜스코딩 부하 분산을 위한 자원 가중치 부하분산 정책)

  • Seo, Dong-Mahn;Lee, Joa-Hyoung;Choi, Myun-Uk;Kim, Yoon;Jung, In-Bum
    • Journal of KIISE:Computing Practices and Letters
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    • v.11 no.5
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    • pp.401-415
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    • 2005
  • Owing to the improved wireless communication technologies, it is possible to provide streaming service of multimedia with PDAs and mobile phones in addition to desktop PCs. Since mobile client devices have low computing power and low network bandwidth due to wireless network, the transcoding technology to adapt media for mobile client devices considering their characteristics is necessary. Transcoding servers transcode the source media to the target media within corresponding grades and provide QoS in real-time. In particular, an effective load balancing policy for transcoding servers is inevitable to support QoS for large scale mobile users. In this paper, the resource weighted load distribution policy is proposed for a fair load balance and a more scalable performance in cluster-based transcoding servers. Our proposed policy is based on the resource weighted table and number of maximum supported users, which are pre-computed for each pre-defined grade. We implement the proposed policy on cluster-based transcoding servers and evaluate its fair load distribution and scalable performance with the number of transcoding servers.

A Heuristic Search Based Optimal Transcoding Path Generation Algorithm for the Play of Multimedia Data (멀티미디어 자료 재생을 위한 경험적 탐색 기반 최적 트랜스코딩 경로 생성 알고리즘)

  • 전성미;이보영;허기중
    • Journal of the Korea Society of Computer and Information
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    • v.8 no.4
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    • pp.47-56
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    • 2003
  • According to rapidly developed mobile terminals and network in the play environment for multimedia presentation, different end-to-end QoS situations appear. Then the generation of transcoding path algorithm was reviewed to transcode a source'data satisfying the needed QoS from a destination and play it considering given transcoders and network. This method used only workload as a parameter although two parameters, workload and throughput, were needed to process multimedia stream in a transcoder, Therefore generated transcoding path with this method had additional calculation to check playability whether it was safisfed the QoS of a destination or not. To solve the problem this paper suggests T algorithm with evaluation function using isochronous property that is needed for multimedia stream to arrive a destination. That means, most playable path is selected with heuristic search based isochronous property between many transcoding paths. Using the suggested algorithm, a transcoding path can be generated faster to play the multimedia data with different end-to-end QoS in real-time transmission.

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Segment-based Cache Replacement Policy in Transcoding Proxy (트랜스코딩 프록시에서 세그먼트 기반 캐쉬 교체 정책)

  • Park, Yoo-Hyun;Kim, Hag-Young;Kim, Kyong-Sok
    • The KIPS Transactions:PartA
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    • v.15A no.1
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    • pp.53-60
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    • 2008
  • Streaming media has contributed to a significant amount of today's Internet Traffic. Like traditional web objects, rich media objects can benefit from proxy caching, but caching streaming media is more of challenging than caching simple web objects, because the streaming media have features such as huge size and high bandwidth. And to support various bandwidth requirements for the heterogeneous ubiquitous devices, a transcoding proxy is usually necessary to provide not only adapting multimedia streams to the client by transcoding, but also caching them for later use. The traditional proxy considers only a single version of the objects, whether they are to be cached or not. However the transcoding proxy has to evaluate the aggregate effect from caching multiple versions of the same object to determine an optimal set of cache objects. And recent researches about multimedia caching frequently store initial parts of videos on the proxy to reduce playback latency and archive better performance. Also lots of researches manage the contents with segments for efficient storage management. In this paper, we define the 9-events of transcoding proxy using 4-atomic events. According to these events, the transcoding proxy can define the next actions. Then, we also propose the segment-based caching policy for the transcoding proxy system. The performance results show that the proposing policy have a low delayed start time, high byte-hit ratio and less transcoding data.

Fast Bitrate Reduction Transcoding using Probability-Based Block Mode Determination in H.264 (확률 기반의 블록 모드 결정 기법을 이용한 H.264에서의 고속 비트율 감축 트랜스코딩)

  • Kim, Dae-Yeon;Lee, Yung-Lyul
    • Journal of Broadcast Engineering
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    • v.10 no.3
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    • pp.348-356
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    • 2005
  • In this paper, we propose a fast bitrate reduction transcoding method to convert a bitstream coded by H.264 into a lower bitrate H.264 bitstream. Block mode informations and motion vectors generated by H.264 decoder are used for probability-based block mode determination in the proposed transcoding method. And the motion vector reuse and motion vector refinement process are applied in the proposed transcoding. In the experiment results, the proposed methods achieves approximately 40 times improvement in computation complexity compared with the cascaded pixel domain transcoding, while the PSNR(Peak Signal to Noise Ratio) is degraded with only $0.1\~0.3$ dB.