{
  "status": "research",
  "advantages": [],
  "limitations": [],
  "supersedes": [],
  "supersededBy": [],
  "firstSeen": null,
  "lastSeen": null,
  "updated": "2026-10-20",
  "slug": "slowdown-fairness",
  "term": "Slowdown fairness",
  "aliases": [
    "FLIN strict fairness"
  ],
  "definition": "Slowdown fairness compares the smallest and largest relative slowdowns among concurrently running I/O flows.",
  "note": "FLIN defines S_i as a flow's shared mean response time divided by its isolated mean, then F = min(S_i) / max(S_i). Compare equal-priority flows at matching timing boundaries. [flin]\n\nEqual ratios can describe equally poor service. The constructed pairs (2, 2) and (20, 20) both give F = 1, despite tenfold different slowdowns; (8, 2) gives F = 0.25. Keep absolute latency and the flow set alongside the fairness value. [hesela]",
  "related": [
    "inter-flow-interference",
    "latency-storage",
    "slowdown-ratio",
    "queue-depth"
  ],
  "citations": [
    {
      "id": "flin",
      "title": "Tavakkol et al. FLIN: Enabling Fairness and Enhancing Performance in Modern NVMe Solid State Drives. ISCA 2018, sections 2.2-6.",
      "url": "https://users.ece.cmu.edu/~saugatag/papers/18isca_flin.pdf",
      "accessed": "2026-10-20"
    },
    {
      "id": "hesela",
      "title": "Hesela: Sharing an SSD: who pays for the slowdown?",
      "url": "https://hesela.com/analyses/ssd-fairness-shared-queues/",
      "accessed": "2026-10-20"
    }
  ]
}