Statistical analysis of feedback synchronization signaling delay for multicast flow control (2001) [2 citations — 1 self]
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Abstract:
Feedback signaling plays a crucial role in flow control because the traffic source relies on the signaling information to make correct and timely flow-control decisions. However, design of an efficient signaling algorithm is a challenging problem since the signaling message can tolerate neither error nor latency. Multicast flow-control signaling imposes two additional challenges: scalability and feedback synchronization. Previous research on multicast signaling has mainly focused on the design and implementation of algorithms without analyzing their delay performances. To address this deficiency, we developed a binary-tree deterministic model [1] and an independent-marking statistical model [2] to explore the delay performance of various multicast feedback-synchronization signaling algorithms. In this paper, we consider cases where the congestion markings at different links are dependent. Including congestion-marking dependence in the analysis is usually much harder than under the independence assumption. However, the analysis without the independence assumption can capture the statistical characteristics for many practical cases where the congestion markings are not independent. Specifically, we develop a Markov chain model defined by the link-marking state on each path
