Title page for ETD etd-04292005-161445


Type of Document Master's Thesis
Author Han, Mei
URN etd-04292005-161445
Title Studies of Dynamic Bandwidth Allocation for Real-Time VBR Video Applications
Degree Master of Science
Department Electrical and Computer Engineering
Advisory Committee
Advisor Name Title
Liang, Yao Committee Chair
DaSilva, Luiz A. Committee Member
Wang, Yue J. Committee Member
Keywords
  • Traffic Model
  • Dynamic Network Bandwidth Allocation
  • Traffic Prediction
Date of Defense 2005-02-23
Availability unrestricted
Abstract
Variable bit rate (VBR) compressed video traffic, such as live video news, is expected to account for a large portion of traffic in future integrated networks. This real-time video traffic has strict delay and loss requirements, and exhibits burstiness over multiple time scales, thus imposing a challenge on network resource allocation and management. The renegotiated VBR (R-VBR) scheme, dynamically allocating resources to capture the burstiness of VBR traffic, substantially increases network utilization while satisfying any desired quality of service (QoS) requirements. This thesis focuses on the performance evaluation of R-VBR in the context of different R-VBR approaches. The renegotiated deterministic VBR (RED-VBR) scheme, proposed by Dr. H. Zhang et al., is thoroughly investigated in this research using a variety of real-world videos, with both high quality and low quality. A new Virtual-Queue-Based RED-VBR is then developed to reduce the implementation complexity of RED-VBR. Simulation results show that this approach obtains a comparable network performance as RED-VBR: relatively high network utilization and a very low drop rate. A Prediction-Based R-VBR based on a multiresolution learning neural network traffic predictor, developed by Dr. Y. Liang, is studied and the use of binary exponential backoff (BEB) algorithm is introduced to efficiently decrease the renegotiation frequency. Compared with RED-VBR, Prediction-Based R-VBR obtains significantly improved network utilization at a little expense of the drop rate. This work provides evaluations of the advantages and disadvantages of several R-VBR approaches, and thus provides a clearer big picture on the performance of the studied R-VBR approaches, which can be used as the basis to choose an appropriate R-VBR scheme to optimize network utilization while enabling QoS for the application tasks.
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