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Server selection in large-scale video-on-demand systems

Niklas Carlsson, Derek L. Eager
2010 ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)  
SYSTEM MODEL We consider a video-on-demand system with N servers.  ...  Video on demand, particularly with user-generated content, is emerging as one of the most bandwidth-intensive applications on the Internet.  ...  Guo et al. [2002] design and evaluate server selection techniques for replicated video-on-demand servers, each with a fixed number of channels.  ... 
doi:10.1145/1671954.1671955 fatcat:i2mevpvyvncidjnbmrmlcd3pva

Simulations on Batching in Video-on-Demand Transmissions [chapter]

Juan Segarra, Vicent Cholvi
2003 Lecture Notes in Computer Science  
One of the methods for taking advantage of multicast services is the use of batching.  ...  We also propose a dynamic batching policy which improves the system performance both in mean and in maximum serving times.  ...  Conclusions In this paper we have studied the effect of using batching in the transmission of video on demand.  ... 
doi:10.1007/3-540-44864-0_47 fatcat:4gn2r6bmx5c37fyghhcdsk5d24

CVSS: A Cost-Efficient and QoS-Aware Video Streaming Using Cloud Services

Xiangbo Li, Mohsen Amini Salehi, Magdy Bayoumi, Rajkumar Buyya
2016 2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)  
To address this challenge, in this paper, we present the Cloud-based Video Streaming Service (CVSS) architecture to transcode video streams in an on-demand manner.  ...  In particular, the architecture includes a QoS-aware scheduling method to efficiently map video streams to cloud resources, and a cost-aware dynamic (i.e., elastic) resource provisioning policy that adapts  ...  CLOUD-BASED VIDEO STREAMING SERVICE (CVSS) ARCHITECTURE We propose the CVSS architecture for on-demand video transcoding on the cloud. An overview of the architecture is presented in Figure 3 .  ... 
doi:10.1109/ccgrid.2016.49 dblp:conf/ccgrid/LiSBB16 fatcat:4k64d5frbnaalbi2lett6ccvri

A hybrid priority-based video-on-demand resource sharing scheme

Chenn-Jung Huang, Yi-Ta Chuang, Chih-Tai Guan, Yun-Cheng Luo, Kai-Wen Hu, Chun-Hua Chen
2008 Computer Communications  
Video-on-demand (VoD) environments frequently batch video requests to decrease I/O demand and increase throughput.  ...  Since users may leave due to waiting too long, a good video scheduling policy has to consider not only the batch size, but also the user defection probabilities and waiting times.  ...  Ted Knoy is appreciated for his editorial assistance.  ... 
doi:10.1016/j.comcom.2008.02.007 fatcat:dy7inn7ptfeexc2xhmqkznjqna

Dynamic Distributed Collaborative Merging Policy to Optimize the Multicasting Delivery Scheme [chapter]

X. Y. Yang, Porfidio Hernández, F. Cores, A. Ripoll, R. Suppi, Emilio Luque
2005 Lecture Notes in Computer Science  
The advance of Internet 2 and the proliferation of switches and routers with level three functionalities made the multicast one of the most feasible video streaming delivering techniques for the near future  ...  The new video delivering scheme was designed as two separate policies: the first policy used client collaboration to deliver first part of videos and the second policy could merge two or more multicast  ...  Introduction The high increase in the commercial use of the Internet (distance learning, Video on Demand (VoD) and digital video libraries) has generated a substantial growth in the demand for video streaming  ... 
doi:10.1007/11549468_96 fatcat:4l4kpfk6mrb2tlwe2w3ucutvoa

Supporting VCR in Peer-to-Peer Video-On-Demand

Yuan He, Yunhao Liu
2007 2007 IEEE International Conference on Network Protocols  
INTRODUCTION Video-On-Demand (VOD) is an interactive multimedia service, which delivers video content to subscribers (users) [2] .  ...  As for the management on buffer, a hybrid caching strategy is adopted. Every peer caches the latest 5 minutes of the video played and uses the Least-Recently-Used (LRU) policy for cache replacement.  ... 
doi:10.1109/icnp.2007.4375865 dblp:conf/icnp/HeL07 fatcat:ismj772b2vbbdmmeb3xoibxuua

Towards scalable delivery of video streams to heterogeneous receivers

Bashar Qudah, Nabil J. Sarhan
2006 Proceedings of the 14th annual ACM international conference on Multimedia - MULTIMEDIA '06  
The required real-time and high-rate transfers for multimedia data severely limit the number of requests that can be serviced concurrently by Video-on-Demand (VOD) servers.  ...  We evaluate the effectiveness of the proposed solutions and analyze various scheduling policies through extensive simulation.  ...  We consider two service models: True Video-on-Demand (TVOD) and Near Video-on-Demand (NVOD).  ... 
doi:10.1145/1180639.1180716 dblp:conf/mm/QudahS06 fatcat:v575s4pojvefjcbwb6bbnflgsi

Design, performance analysis, and implementation of a super-scalar video-on-demand system

J.Y.B. Lee, C.H. Lee
2002 IEEE transactions on circuits and systems for video technology (Print)  
Index Terms-Multicast, performance analysis, super-scaler video-in-demand (SS-VoD), super-scalar, video-on-demand.  ...  This paper presents this new architecture, proposes methods to support interactive playback controls without the need for additional server or client resources, and derives an approximate performance model  ...  Unlike static multicast channels, dynamic multicast channels are allocated in an on-demand basis according to the admission procedure described in Section III-B.  ... 
doi:10.1109/tcsvt.2002.805510 fatcat:ymbmqslgtbchle2t65anl6kime

Multicast Transmission Prefix and Popularity Aware Interval Caching Based Admission Control Policy [article]

P. Jayarekha, T.R. Gopalakrishnan Nair
2010 arXiv   pre-print
An admission control algorithm for a multimedia server is responsible for determining if a new request can be accepted without violating the QoS requirements of the existing requests in the system.  ...  An admission control strategy based on Popularity-aware interval caching for Prefix [3] scheme extends the interval caching by considering different popularity of multimedia objects.  ...  The future work is carried out on an efficient replacement technique and to dynamically allocate the blocks to the frames in the cache depending on popularity.  ... 
arXiv:1001.3744v1 fatcat:7fj74knatvajdnw2nxj262n5yq

Efficient cost-based scheduling for scalable media streaming

Nabil J. Sarhan, Bashar Qudah, Roger Zimmermann, Carsten Griwodz
2007 Multimedia Computing and Networking 2007  
The achieved resource sharing depends greatly on how the waiting requests are scheduled for service.  ...  and the average waiting time for service.  ...  Video delivery can be done in a client-pull or a server-push fashion, depending on whether the channels are allocated on demand or reserved in advance.  ... 
doi:10.1117/12.706022 fatcat:dkvmpfviejepnfsv3e72qgofpm

Multimedia resource management in OS/390 LAN Server

A. Dan, S. Dulin, S. Marcotte, D. Sitaram
1997 IBM Systems Journal  
Shahabuddin, “Dynamic Batch- ing Policies for an On-Demand Video Server” (invited pa- per), ACM Multimedia Systems 4, No. 3, 112-121 (June 1996). . M. Kienzle, A. Dan, D. Sitaram, and W.  ...  Sitaram, “Dynamic Policy of Seg- ment Replication for Load-Balancing in Video-on-Demand Servers,” ACM Multimedia Systems 3, No. 3, 93-103 (July 1995). . A. Dan and D.  ... 
doi:10.1147/sj.363.0393 fatcat:rfjpahhho5effmpasesmwu7e54

Video delivery technologies for large-scale deployment of multimedia applications

K.A. Hua, M.A. Tantaoui, W. Tavanapong
2004 Proceedings of the IEEE  
Deployment of a large-scale multimedia streaming application requires an enormous amount of server and network resources.  ...  The simplest delivery technique allocates server resources for each specific request. This technique is very expensive and is not scalable to support a very large user community such as the Internet.  ...  . • Near Video-on-Demand (NVOD): Users requesting for the same video are served using one video stream to minimize the demand on server bandwidth.  ... 
doi:10.1109/jproc.2004.832954 fatcat:vmanamrpwvclvhfaze2twfczpq

The effectiveness of intelligent scheduling for multicast video-on-demand

Vaneet Aggarwal, Robert Caldebank, Vijay Gopalakrishnan, Rittwik Jana, K. K. Ramakrishnan, Fang Yu
2009 Proceedings of the seventeen ACM international conference on Multimedia - MM '09  
Adopting multicast for on-demand access, however, is challenging because of the need to temporally aggregate requests.  ...  As more and more video content is made available and accessed on-demand, content and service providers face challenges of scale.  ...  INTRODUCTION With the growth in use of Internet Protocol (IP) for video delivery, there has been a lot of emphasis on delivering video to viewers on-demand.  ... 
doi:10.1145/1631272.1631330 dblp:conf/mm/AggarwalCGJRY09 fatcat:duklwdmg25gkvl7obkeyv6jjsq

Bandwidth skimming: a technique for cost-effective video on demand

Derek L. Eager, Mary K. Vernon, John Zahorjan, Klara Nahrstedt, Wu-chi Feng
1999 Multimedia Computing and Networking 2000  
Video-on-demand applications must consider the bandwidth limitations at the server, within the network, and at the client.  ...  This paper proposes a new technique for on-demand delivery of streaming media that addresses this problem.  ...  INTRODUCTION Application of video-on-demand is currently limited by economic considerations that are largely dominated by bandwidth issues, at both the client and server.  ... 
doi:10.1117/12.373523 fatcat:ciw6mqqvs5bp7amjytdlt4ikfy

Multicast Video-on-Demand services

Huadong Ma, Kang G. Shin
2002 Computer communication review  
Long-lived session: a VoD system should support long-lived sessions; for example, a typical movie-on-demand service usually lasts 90-120 minutes.  ...  Efficiency: The system should impose a minimal additional burden on the server and the network, and should sufficiently utilize critical resources on the server and the network.  ...  The data-centered scheme has the potential for dramatically re-Batching policy Features Comparison Maximum Queue Length requests for the video with the largest maximizing the server throughput (MQLF)  ... 
doi:10.1145/510726.510729 fatcat:6rqftq5zg5aytg6byeayvwssju
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