Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Advances in modeling and engineering of Longe-Range dependent traffic
Loss ratio approximations in buffered systems with regulated inputs
valuetools '06 Proceedings of the 1st international conference on Performance evaluation methodolgies and tools
Energy-Efficient Wireless Packet Scheduling with Quality of Service Control
IEEE Transactions on Mobile Computing
A new model for MPEG video traffic at the frame level using self-similar processes
SpringSim '07 Proceedings of the 2007 spring simulaiton multiconference - Volume 1
New stochastic network calculus for loss analysis
Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools
Modeling of H.264 high definition video traffic using discrete-time semi-Markov processes
ITC20'07 Proceedings of the 20th international teletraffic conference on Managing traffic performance in converged networks
Workload loss examinations with a novel probabilistic extension of network calculus
NETWORKING'06 Proceedings of the 5th international IFIP-TC6 conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communications Systems
A novel direct upper approximation for workload loss ratio in general buffered systems
NETWORKING'05 Proceedings of the 4th IFIP-TC6 international conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communication Systems
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We analyze the autocorrelation structure for a class of scene-based MPEG video models at the groups-of-pictures (GOP) (course grain) and frame (fine grain) levels assuming an arbitrary scene-length distribution. At the GOP level, we establish the relationship between the scene-length statistics and the short-range/long-range dependence (SRD/LRD) of the underlying model. We formally show that when the intrascene dynamics exhibit SRD, the overall model exhibits LRD if and only if the second moment of the scene length is infinite. Our results provide the theoretical foundation for several empirically derived scene-based models. We then study the impact of traffic correlations on the packet loss performance at a video buffer. Two popular families of scene-length distributions are investigated: Pareto and Weibull. In the case of Pareto distributed scene lengths, it is observed that the performance is rather insensitive to changes in the buffer size even as the video model enters the SRD regime. For Weibull distributed scene lengths, we observe that for small buffers the loss performance under a frame-level model can be larger than its GOP-level counterpart by orders of magnitude. In this case, the reliance on GOP-level models will result in very optimistic results