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[Author] Yuthapong SOMCHIT(2hit)

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  • Dynamic Activating and Deactivating Loss Recovery Router for Live Streaming Multicast

    Yuthapong SOMCHIT  Aki KOBAYASHI  Katsunori YAMAOKA  Yoshinori SAKAI  

     
    PAPER-Network

      Vol:
    E89-B No:5
      Page(s):
    1534-1544

    Live streaming is delay sensitive and can tolerate some amount of loss. The QoS Multicast for Live Streaming (QMLS) Protocol, focuses on the characteristics of live streaming. It has been shown to improve the performance of live streaming multicast by reducing the end-to-end packet loss probability. However, the placement of active routers performing the QMLS function has not been discussed. This paper proposes a dynamic method to activate and deactivate routers in order to minimize the number of active routers for each QMLS-packet flow and discusses its parameters. The results of an evaluation show that the proposed method can reduce the number of active routers for each flow and adjust the active routers according to changes in the multicast tree.

  • QoS Multicast Protocol for Live Streaming

    Yuthapong SOMCHIT  Aki KOBAYASHI  Katsunori YAMAOKA  Yoshinori SAKAI  

     
    PAPER-Network

      Vol:
    E88-B No:3
      Page(s):
    1128-1138

    Live streaming media are delay sensitive and have limited allowable delays. Current conventional multicast protocols do not have a loss retransmission mechanism. Even though several reliable multicast protocols with retransmission mechanisms have been proposed, the long delay and high packet loss rate make them inefficient for live streaming. This paper proposes a multicast protocol focusing on the allowable delay called the QoS Multicast for Live Streaming (QMLS) protocol. QMLS routers are placed along the multicast tree to detect and retransmit lost packets. We propose a method that enables data recovery to be done immediately after lost packets are detected by the QMLS router and a method that reduces the unnecessary packets sent to end receivers. This paper discusses the mathematical analysis of the proposed protocol and compares it with other multicast protocols. The results reveal that our protocol is more effective in live streaming. Finally, we do a simulation to evaluate its performance and study the effect of consecutive losses. The simulation reveals that consecutive losses can slightly increase losses with our protocol.