{
  "abstract": "In large-scale computing systems, jobs often demand heterogeneous server allocations: large jobs that occupy a substantial fraction of the servers are of high importance and are thus latency-sensitive, while small jobs fill in the remaining capacity to maintain throughput. To model this dynamic, we introduce the half-batch multiserver-job (MSJ) framework, a queueing model in which large jobs arrive according to a Poisson process and require all servers simultaneously, while small jobs, each needing only one server, are always available. We prove that, in the half-batch MSJ model, the Pareto frontier for large-job mean response time and small-job throughput admits a simple and exact characterization. It is generated by a family of convoy policies, under which the system serves small jobs until $k$ large jobs have arrived and then switches to serving large jobs, together with convex combinations of neighboring convoy policies. Our result is fully general and non-asymptotic, holding for every stable arrival rate $λ$, every number of servers $n$, and every large-job size distribution $S$.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2607.08999",
  "author_total": 2,
  "authors": [
    {
      "name": "Ziyuan Wang"
    },
    {
      "name": "Izzy Grosof"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9rs2gsw62bw6f.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2607.08999",
  "fulltext_url": null,
  "id": "9rs2gsw62bw6f",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2607.08999",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.PF"
    ],
    [
      "arxiv",
      "math.PR"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2607.08999",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-11",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/9rs2gsw62bw6f.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:21:29Z",
      "native_id": "2607.08999",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2607.08999"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.PR",
      "subfield": "probability"
    }
  ],
  "title": "Pareto-Optimal Scheduling in the Half-batch Multiserver-job Model",
  "title_text": "Pareto-Optimal Scheduling in the Half-batch Multiserver-job Model",
  "type": "preprint",
  "updated_at": "2026-10-30T12:21:29Z",
  "url": "https://research.draconitic.com/paper/9rs2gsw62bw6f",
  "venue": "arXiv",
  "versions": []
}