Congestion avoidance and control
SIGCOMM '88 Symposium proceedings on Communications architectures and protocols
Analysis of the increase and decrease algorithms for congestion avoidance in computer networks
Computer Networks and ISDN Systems
Inter-receiver fairness: a novel performance measure for multicast ABR sessions
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Achieving bounded fairness for multicast and TCP traffic in the Internet
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
Modeling TCP throughput: a simple model and its empirical validation
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
The impact of multicast layering on network fairness
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Promoting the use of end-to-end congestion control in the Internet
IEEE/ACM Transactions on Networking (TON)
A Class of End-to-End Congestion Control Algorithms for the Internet
ICNP '98 Proceedings of the Sixth International Conference on Network Protocols
MTCP: Scalable TCP-like Congestion Control for Reliable Multicast
MTCP: Scalable TCP-like Congestion Control for Reliable Multicast
On max-min fair congestion control for multicast ABR service in ATM
IEEE Journal on Selected Areas in Communications
LE-SBCC: Loss-Event Oriented Source-Based Multicast Congestion Control
Multimedia Tools and Applications
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A key issue in the design of source-based multicast congestion control schemes is how to aggregate loss indications from multiple receivers into a single rate control decision at the source. Such aggregation entails filtering out a portion of the loss indications received by the source, and then using the remaining for rate adjustments. In this paper, we first propose a set of goals guiding the design of loss indication filters. We then present a novel loss indication filtering approach, the linear proportional response (LPR) approach. Analysis and simulation is used to compare LPR to two well-known approaches - the random listening algorithm (RLA) [Proceedings of ACM SIGCOMM (1998)] and the worst estimate-based tracking (WET) [Proceedings of IEEE Infocom (1999)] approach. Our results indicate that LPR achieves a desirable tradeoff between stability and response, thereby making it more suitable than WET and RLA for deployment in an Internet-like environment.