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SPMLD: Sub-Packet based Multipath Load Distribution for Real-Time Multimedia Traffic

  • Wu, Jiyan (State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications) ;
  • Yang, Jingqi (State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications) ;
  • Shang, Yanlei (State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications) ;
  • Cheng, Bo (State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications) ;
  • Chen, Junliang (State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications)
  • Received : 2013.07.07
  • Accepted : 2014.02.07
  • Published : 2014.10.31

Abstract

Load distribution is vital to the performance of multipath transport. The task becomes more challenging in real-time multimedia applications (RTMA), which impose stringent delay requirements. Two key issues to be addressed are: 1) How to minimize end-to-end delay and 2) how to alleviate packet reordering that incurs additional recovery time at the receiver. In this paper, we propose sub-packet based multipath load distribution (SPMLD), a new model that splits traffic at the granularity of sub-packet. Our SPMLD model aims to minimize total packet delay by effectively aggregating multiple parallel paths as a single virtual path. First, we formulate the packet splitting over multiple paths as a constrained optimization problem and derive its solution based on progressive approximation method. Second, in the solution, we analyze queuing delay by introducing D/M/1 model and obtain the expression of dynamic packet splitting ratio for each path. Third, in order to describe SPMLD's scheduling policy, we propose two distributed algorithms respectively implemented in the source and destination nodes. We evaluate the performance of SPMLD through extensive simulations in QualNet using real-time H.264 video streaming. Experimental results demonstrate that: SPMLD outperforms previous flow and packet based load distribution models in terms of video peak signal-to-noise ratio, total packet delay, end-to-end delay, and risk of packet reordering. Besides, SPMLD's extra overhead is tiny compared to the input video streaming.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation of China

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