38 lines
2.3 KiB
Markdown
38 lines
2.3 KiB
Markdown
---
|
|
type: source
|
|
title: "Resource Scheduling in Non-Stationary Service Systems"
|
|
author: "Simio / WinterSim 2018"
|
|
url: https://www.simio.com/resources/papers/WinterSim2018/Resource-Scheduling-In-Non-stationary-Service-Systems.php
|
|
date: 2018-12-01
|
|
domain: internet-finance
|
|
format: paper
|
|
status: processed
|
|
tags: [pipeline-architecture, stochastic-modeling, non-stationary-arrivals, resource-scheduling, simulation]
|
|
processed_by: rio
|
|
processed_date: 2026-03-11
|
|
claims_extracted: ["non-stationary-service-systems-require-dynamic-worker-allocation-because-fixed-staffing-wastes-capacity-during-low-demand-and-creates-bottlenecks-during-peaks.md"]
|
|
extraction_model: "anthropic/claude-sonnet-4.5"
|
|
extraction_notes: "Single claim extracted validating dynamic worker allocation for pipeline architecture. Paper provides theoretical foundation for queue-depth-based scaling vs fixed worker pools. No entity data (academic paper, no companies/products/people to track). No enrichments to existing claims (this is infrastructure theory, not market mechanism design)."
|
|
---
|
|
|
|
# Resource Scheduling in Non-Stationary Service Systems
|
|
|
|
WinterSim 2018 paper on scheduling resources (servers/workers) when arrival rates change over time. Addresses the gap between theoretical queueing models (which assume stationarity) and real systems (which don't).
|
|
|
|
## Key Content
|
|
|
|
- Non-stationary service systems require time-varying staffing — fixed worker counts are suboptimal
|
|
- The goal: determine the number of servers as a function of time
|
|
- Without server constraints there would be no waiting time, but this wastes capacity since arrivals are stochastic and nonstationary
|
|
- Simulation-based approach: use discrete-event simulation to test staffing policies against realistic arrival patterns
|
|
- Key tradeoff: responsiveness (adding workers fast when load spikes) vs. efficiency (not wasting workers during quiet periods)
|
|
|
|
## Relevance to Teleo Pipeline
|
|
|
|
Directly applicable: our pipeline needs time-varying worker counts, not fixed MAX_WORKERS. The paper validates the approach of measuring queue depth and adjusting workers dynamically rather than using static cron-based fixed pools.
|
|
|
|
|
|
## Key Facts
|
|
- WinterSim 2018 conference paper on resource scheduling
|
|
- Addresses queueing theory gap between stationary assumptions and nonstationary reality
|
|
- Proposes simulation-based staffing optimization for time-varying demand
|