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Local error recovery in SRM: comparison of two approaches
IEEE/ACM Transactions on Networking (TON)
Scalable feedback for large groups
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A model, analysis, and protocol framework for soft state-based communication
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SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
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ICOIN '02 Revised Papers from the International Conference on Information Networking, Wireless Communications Technologies and Network Applications-Part I
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HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
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Crossroads
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IEEE Transactions on Evolutionary Computation
Dynamic Hello/Timeout timer adjustment in routing protocols for reducing overhead in MANETs
Computer Communications
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Modeling soft state protocols with SDL
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On the scaling of feedback algorithms for very large multicast groups
Computer Communications
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Soft state protocols use periodic refresh messages to keep network state alive while adapting to changing network conditions; this has raised concerns regarding the scalability of protocols that use the soft-state approach. In existing soft state protocols, the values of the timers that control the sending of these messages, and the timers for aging out state, are chosen by matching empirical observations with desired recovery and response times. These fixed timer-values fail because they use time as a metric for bandwidth; they adapt neither to (1) the wide range of link speeds that exist in most wide-area internets, nor to (2) fluctuations in the amount of network state over time.We propose and evaluate a new approach in which timer-values adapt dynamically to the volume of control traffic and available bandwidth on the link. The essential mechanisms required to realize this scalable timers approach are: (1) dynamic adjustment of the senders' refresh rate so that the bandwidth allocated for control traffic is not exceeded, and (2) estimation of the senders' refresh rate at the receiver in order to determine when state can be timed-out and deleted. The refresh messages are sent in a round robin manner not exceeding the bandwidth allocated to control traffic, and taking into account message priorities.We evaluate two receiver estimation methods for dynamically adjusting network state timeout values: (1) counting of the rounds and (2) exponential weighted moving average.