The bi-channel paradigm separates database networking into a high-performance UDP data path and a TCP control path to reduce kernel overhead while preserving reliability on fast cloud networks.
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3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
BlobShuffle reduces shuffling costs by over 40x in Kafka Streams by using object storage for batching with notifications, achieving sub-2s 95th-percentile latency and scaling beyond 2 GiB/s.
In closed-loop OLTP the group commit timer collapses to greedy above λ*=2/F0, rendering tuning vacuous and the greedy policy within 0.1% of oracle optimum.
citing papers explorer
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The Bi-Channel Networking Paradigm for Database Systems in the Cloud
The bi-channel paradigm separates database networking into a high-performance UDP data path and a TCP control path to reduce kernel overhead while preserving reliability on fast cloud networks.
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BlobShuffle: Cost-Effective Repartitioning in Stream Processing Systems via Object Storage Exemplified with Kafka Streams
BlobShuffle reduces shuffling costs by over 40x in Kafka Streams by using object storage for batching with notifications, achieving sub-2s 95th-percentile latency and scaling beyond 2 GiB/s.
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Group Commit Self-Clocks: Why Tuning Is Unnecessary Above a Device-Set Load Threshold
In closed-loop OLTP the group commit timer collapses to greedy above λ*=2/F0, rendering tuning vacuous and the greedy policy within 0.1% of oracle optimum.