e0c9323264
Pentagon-Agent: Ganymede <F99EBFA6-547B-4096-BEEA-1D59C3E4028A>
3.2 KiB
| type | title | author | url | date | domain | format | status | tags | processed_by | processed_date | claims_extracted | extraction_model | extraction_notes | ||||||||
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| source | What You Should Know About Queueing Models | Ward Whitt (Columbia University) | https://www.columbia.edu/~ww2040/shorter041907.pdf | 2019-04-19 | internet-finance | paper | processed |
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rio | 2026-03-11 |
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anthropic/claude-sonnet-4.5 | Extracted three proven claims about queueing theory fundamentals: square-root staffing principle, Halfin-Whitt QED regime, and economies of scale in multi-server systems. All claims are foundational results from operations research with direct applicability to pipeline architecture and resource provisioning. Source is practitioner-oriented guide by Ward Whitt, a founder of modern queueing theory. No entities to extract (theoretical paper, no companies/products/decisions). No enrichments (queueing theory is new domain for KB). |
What You Should Know About Queueing Models
Practitioner-oriented guide by Ward Whitt (Columbia), one of the founders of modern queueing theory for service systems. Covers the essential queueing models practitioners need and introduces the Halfin-Whitt heavy-traffic regime.
Key Content
- Square-root staffing principle: optimal server count = base load + β√(base load), where β is a quality-of-service parameter
- The Halfin-Whitt (QED) regime: systems operate near full utilization while keeping delays manageable — utilization approaches 1 at rate Θ(1/√n) as servers n grow
- Economies of scale in multi-server systems: larger systems need proportionally fewer excess servers
- Practical formulas for determining server counts given arrival rates and service level targets
- Erlang C formula as the workhorse for staffing calculations
Relevance to Teleo Pipeline
The square-root staffing rule is directly applicable: if our base load requires R workers at full utilization, we should provision R + β√R workers where β ≈ 1-2 depending on target service level. For our scale (~8 sources/cycle, ~5 min service time), this gives concrete worker count guidance.
Critical insight: you don't need to match peak load with workers. The square-root safety margin handles variance efficiently. Over-provisioning for peak is wasteful; under-provisioning for average causes queue explosion. The sweet spot is the QED regime.
Key Facts
- Erlang C formula is the computational workhorse for staffing calculations in multi-server queues
- Square-root staffing formula: optimal servers = R + β√R where R is base load and β ≈ 1-2 for typical service levels
- Halfin-Whitt regime characterized by utilization approaching 1 at rate Θ(1/√n) as servers n grow