A multicast transport protocol
SIGCOMM '88 Symposium proceedings on Communications architectures and protocols
Random early detection gateways for congestion avoidance
IEEE/ACM Transactions on Networking (TON)
TCP and explicit congestion notification
ACM SIGCOMM Computer Communication Review
Computer networks (3rd ed.)
Scalable flow control for multicast ABR services in ATM networks
IEEE/ACM Transactions on Networking (TON)
Random Early Marking: An Optimization Approach to Internet Congestion Control
ICON '99 Proceedings of the 7th IEEE International Conference on Networks
Delay analysis of feedback-synchronization signaling for multicast flow control
IEEE/ACM Transactions on Networking (TON)
Second-Order Rate-Control Based Transport Protocols
ICNP '01 Proceedings of the Ninth International Conference on Network Protocols
Performance issues in public ABR service
IEEE Communications Magazine
On max-min fair congestion control for multicast ABR service in ATM
IEEE Journal on Selected Areas in Communications
Delay analysis of feedback-synchronization signaling for multicast flow control
IEEE/ACM Transactions on Networking (TON)
Markov-chain modeling for multicast signaling delay analysis
IEEE/ACM Transactions on Networking (TON)
Delay analysis of real-time data dissemination
Proceedings of the 11th communications and networking simulation symposium
Statistical QoS provisionings for wireless unicast/multicast of multi-layer video streams
IEEE Journal on Selected Areas in Communications
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Feedback signaling plays a key role in flow control because the traffic source relies on the signaling information to make correct and timely flow-control decisions. Design of an efficient signaling algorithm is a challenging task since the signaling messages can tolerate neither error nor latency. Multicast flow-control signaling imposes two additional challenges: scalability and feedback synchronization. Previous research on multicast feedback-synchronization signaling has mainly focused on the algorithm design and implementation. However, the delay properties of these algorithms are, despite their vital importance, neither well understood nor thoroughly studied. In this paper, we develop both deterministic and statistical binary-tree models to study the delay performance of the multicast signaling algorithms. The deterministic model is used to derive the expressions of each path's feedback roundtrip time in a multicast tree, while the statistical model is employed to derive the general probability distributions of each path becoming the multicast-tree bottleneck. Using these models, we analyze and contrast the signaling delay scalability of two representative multicast signaling protocols--the Soft-Synchronization Protocol (SSP) and the Hop-By-Hop (HBH) scheme--by deriving the first and second moments of multicast signaling delays. Also derived is the optimal flow-control update interval for SSP to minimize the multicast signaling delay.