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Ching-Gung Liu

Researcher at University of Southern California

Publications -  7
Citations -  3429

Ching-Gung Liu is an academic researcher from University of Southern California. The author has contributed to research in topics: Reliable multicast & Multicast. The author has an hindex of 7, co-authored 7 publications receiving 3417 citations. Previous affiliations of Ching-Gung Liu include Fujitsu.

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Journal ArticleDOI

A reliable multicast framework for light-weight sessions and application level framing

TL;DR: An adaptive algorithm is demonstrated that uses the results of previous loss recovery events to adapt the control parameters used for future loss recovery, and provides good performance over a wide range of underlying topologies.
Journal ArticleDOI

The PIM architecture for wide-area multicast routing

TL;DR: The protocol independent multicast (PIM) architecture maintains the traditional IP multicast service model of receiver-initiated membership, supports both shared and source-specific (shortest-path) distribution trees, and uses soft-state mechanisms to adapt to underlying network conditions and group dynamics.
Proceedings ArticleDOI

A reliable multicast framework for light-weight sessions and application level framing

TL;DR: An adaptive algorithm that uses the results of previous loss recovery events to adapt the control parameters used for future loss recovery is demonstrated, and the reliable multicast delivery algorithm provides good performance over a wide range of underlying topologies.
Proceedings ArticleDOI

An architecture for wide-area multicast routing

TL;DR: The Protocol Independent Multicast (PIM) architecture maintains the traditional IP multicast service model of receiver-initiated membership and uses soft-state mechanisms to adapt to underlying network conditions and group dynamics, which make it well suited to large heterogeneous inter-networks.

Protocol Independent Multicast-Sparse Mode (PIM-SM): Motivation and Architecture

TL;DR: The robustness, exibility, and scaling properties of this architecture make it well suited to large heterogeneous inter-networks, and it uses soft-state mechanisms to adapt to underlying network conditions and group dynamics.