Video Traffic Flow Analysis in Distributed System during Interactive Session

Cost effective, smooth multimedia streaming to the remote customer through the distributed “video on demand” architecture is the most challenging research issue over the decade. The hierarchical system design is used for distributed network to satisfy more requesting users. The distributed hierarchical network system contains all the local and remote storage multimedia servers. The hierarchical network system is used to provide continuous availability of the data stream to the requesting customer. In this work, we propose a novel data stream that handles the methodology for reducing the connection failure and smooth multimedia stream delivery to the remote customer. The proposed session based single-user bandwidth requirement model presents the bandwidth requirement for any interactive session like pause, move slowly, rewind, skip some of the frame, and move fast with some constant number of frames. The proposed session based optimum storage finding algorithm reduces the search hop count towards the remote storage-data server. The modeling and simulation result shows the better impact over the distributed system architecture. This work presents the novel bandwidth requirement model at the interactive session and gives the trade-off in communication and storage costs for different system resource configurations.

[1]  Yao Liang,et al.  Real-Time VBR Video Traffic Prediction for Dynamic Bandwidth Allocation , 2004, IEEE Trans. Syst. Man Cybern. Part C.

[2]  James Won-Ki Hong,et al.  Application‐Level Traffic Monitoring and an Analysis on IP Networks , 2005 .

[3]  Gyu Myoung Lee,et al.  Functional Architecture for NGN-Based Personalized IPTV Services , 2009, IEEE Transactions on Broadcasting.

[4]  Sally Floyd,et al.  Wide area traffic: the failure of Poisson modeling , 1995, TNET.

[5]  Anja Feldmann,et al.  On dominant characteristics of residential broadband internet traffic , 2009, IMC '09.

[6]  Soumen Kanrar,et al.  Efficient Traffic Control of VoD System , 2011, ArXiv.

[7]  Eric Wing Ming Wong,et al.  Performance Model of Interactive Video-on-Demand Systems , 1996, IEEE J. Sel. Areas Commun..

[8]  Soumen Kanrar,et al.  Performance Enhancement for Audio-Video Proxy Server , 2014, FICTA.

[9]  Krishna P. Gummadi,et al.  An analysis of Internet content delivery systems , 2002, OPSR.

[10]  Thomas D. C. Little,et al.  Prospects for Interactive Video-on-Demand , 1994, IEEE MultiMedia.

[11]  Siddhartha Annapureddy,et al.  Exploring VoD in P2P Swarming Systems , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[12]  Soumen Kanrar,et al.  Optimum storage finding in video on demand system , 2015, 2015 2nd International Conference on Signal Processing and Integrated Networks (SPIN).

[13]  Cheng-Zhong Xu,et al.  Efficient algorithms of video replication and placement on a cluster of streaming servers , 2007, J. Netw. Comput. Appl..

[14]  Michael Zink,et al.  Characteristics of YouTube network traffic at a campus network - Measurements, models, and implications , 2009, Comput. Networks.

[15]  Cheng Huang,et al.  Can internet video-on-demand be profitable? , 2007, SIGCOMM '07.

[16]  Lei Shi,et al.  Quantitative Analysis of Zipf's Law on Web Cache , 2005, ISPA.

[17]  Soumen Kanrar Analysis and implementation of the Large Scale Video-on-Demand System , 2012, ArXiv.

[18]  Laurent Massoulié,et al.  Push-to-Peer Video-on-Demand System: Design and Evaluation , 2007, IEEE Journal on Selected Areas in Communications.

[19]  Soumen Kanrar,et al.  Performance of distributed video on demand system for multirate traffic , 2011, 2011 International Conference on Recent Trends in Information Systems.

[20]  Soumen Kanrar,et al.  Dynamic Page Replacement at the Cache Memory for the Video on Demand Server , 2014 .

[21]  James Won-Ki Hong,et al.  Characteristic analysis of internet traffic from the perspective of flows , 2006, Comput. Commun..

[22]  Gerhard Haßlinger,et al.  Efficiency of caches for content distribution on the Internet , 2010, 2010 22nd International Teletraffic Congress (lTC 22).

[23]  Arun K. Sood,et al.  Class-based access control for distributed video-on-demand systems , 2005, IEEE Transactions on Circuits and Systems for Video Technology.

[24]  Leonard Kleinrock,et al.  Proportional Replication in Peer-to-Peer Networks , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[25]  Anja Feldmann,et al.  An analysis of Internet chat systems , 2003, IMC '03.

[26]  Hayder Radha,et al.  End-to-end Internet video traffic dynamics: statistical study and analysis , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[27]  Leonard Kleinrock,et al.  On Fairness, Optimal Download Performance and Proportional Replication in Peer-to-Peer Networks , 2005, NETWORKING.

[28]  Antonio Pescapè,et al.  Traffic analysis of peer-to-peer IPTV communities , 2009, Comput. Networks.

[29]  Jia Wang,et al.  Analyzing peer-to-peer traffic across large networks , 2004, IEEE/ACM Trans. Netw..

[30]  Kang-Won Lee,et al.  Planning and Managing the IPTV Service Deployment , 2007, 2007 10th IFIP/IEEE International Symposium on Integrated Network Management.

[31]  Asit Dan,et al.  Scheduling policies for an on-demand video server with batching , 1994, MULTIMEDIA '94.

[32]  Christophe Diot,et al.  A distributed architecture for multiplayer interactive applications on the Internet , 1999, IEEE Netw..