Rain: RDMA-assisted In-Network Scheduling for Microsecond-scale Workloads
2026-06-03T07:23:55Z•a292f7ebecf6927d2e49dde87c8da38ee5ee9524f98643a46c7950cb51031227
5G802.11bqAUGUSTEBBRIDSKV-cacheLLM-inferenceQUICRDMARPLURLLCcongestion-controlfoundation-modelsin-network-schedulinglive-streamingmicrosecond-latencymmWavemodel-routingmulti-armed-banditnetwork-aware-schedulingone-sided-RDMA-WRITEprogrammable-switchesqueueingschedulingvLLM-router","BigDipper","data-availability","BFT","payment-ch渠道
What happened
Collection of recent systems and networking research: Rain proposes an RDMA-assisted, programmable-switch in-network scheduler that buffers tasks and worker tokens on-switch and uses one-sided WRITE multicasts to pre-write large tasks, improving throughput and tail latency for microsecond-scale workloads (1.75x vs SOTA on RocksDB). Papers include a combinatorial MAB approach for multi-AP IEEE P802.11bq throughput tuning, AUGUSTE — an online-learning MAC scheduler that predicts uplink arrivals to deliver URLLC-like latency with far lower overhead in 5G testbeds, and BBR-Copilot — a QUIC-sideaux
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_ni
- Record identifier
- a292f7ebecf6927d2e49dde87c8da38ee5ee9524f98643a46c7950cb51031227
- Enrichment time
- 2026-06-03T07:23:55Z
- AI-assisted enrichment
- Yes
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