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Classroom Contents
Overload Control for µs-scale RPCs with Breakwater
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- 1 Intro
- 2 Trend: High Fan-out Internet
- 3 Causes of Server Overload
- 4 Performance Without Overload Control
- 5 Ideal Overload Control
- 6 Strawman #1: Server-side AQM
- 7 Strawman #2: Client Rate limiting
- 8 Breakwater Overload control scheme for us-scale RPCs
- 9 Breakwater's benefits Handles server overload with us-scale RPCs with
- 10 Queueing delay as congestion signal
- 11 Credit-based admission control Breakwater controls amount of incoming requests with credits
- 12 Demand Message Overhead Server needs to know which client has demand
- 13 Impact of Credit-based Admission Control Credit-based admission control has lower and bounded tail latency but lower throughput.
- 14 Piggybacking Demand Information Breakwater piggybacks clients' demand information into requests.
- 15 Demand Speculation Breakwater speculate clients' demand to minimize message overhead
- 16 Impact of Adding Demand Speculation Demand speculation improves throughput with higher tail latency
- 17 Credit Overcommitment Server issues more credit than the number of requests it can accomodate
- 18 Incast Causing Long Queue With credit overcommitment, multiple requests may arrive at the server at the same time
- 19 Delay-based AQM To ensure low tail latency, the server drops requests if queueing delay exceeds threshold.
- 20 Impact of Adding Delay-based AQM Breakwater achieves high throughput and low and bounded tail latency at the same time
- 21 Evaluation
- 22 High Goodput with Fast Convergence
- 23 Fast Notification of Reject
- 24 Conclusion • Breakwater is a server-driven credit-based overload
