{
  "abstract": "We study the age of information and peak age of information in status update systems with an arbitrary number of independent sources sharing a single server with generally distributed service times. We consider a general age-dependent self-preemptive policy in which an in-service update from source $c$ is preempted by a new same-source arrival with a probability $p_c(x)$ that depends on the elapsed service time $x$. This formulation subsumes the non-preemptive, fully self-preemptive, and probabilistically preemptive policies as special cases, and also accommodates threshold-based preemption. We develop a unified analytical framework based on non-homogeneous absorbing continuous-time Markov chains and semi-Markov chains to derive explicit expressions for the average age of information and peak age of information of each source under general per-source service-time distributions and age-dependent preemption rules. The framework applies to both single-source and multi-source systems and enables joint tuning of per-source preemption parameters. Numerical results for fifteen service-time distributions in the single-source setting reveal that the benefits of preemption depend strongly on the service-time hazard-rate structure, with threshold-based preemption providing its most notable additional gains over age-independent policies for distributions with unimodal hazard rates. For a dual-source system with lognormal service times, jointly tuned threshold-based preemption achieves lower sum average age of information and peak age of information than the considered age-independent policies, highlighting the importance of cross-source interactions in preemption decisions.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2611.07151",
  "author_total": 5,
  "authors": [
    {
      "name": "Mohammad Moltafet"
    },
    {
      "name": "Nail Akar"
    },
    {
      "name": "Sennur Ulukus"
    },
    {
      "name": "Marian Codreanu"
    },
    {
      "name": "Roy D. Yates"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5c0zw2xq25tnr.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2611.07151",
  "fulltext_url": null,
  "id": "5c0zw2xq25tnr",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2611.07151",
  "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.IT"
    ],
    [
      "arxiv",
      "math.IT"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2611.07151",
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-04",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/5c0zw2xq25tnr.ris",
  "sources": [
    {
      "first_seen": "2026-11-06T18:21:34Z",
      "native_id": "2611.07151",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2611.07151"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.IT",
      "subfield": "general"
    }
  ],
  "title": "Elapsed-Service-Time-Aware Preemption for Age of Information Minimization",
  "title_text": "Elapsed-Service-Time-Aware Preemption for Age of Information Minimization",
  "type": "preprint",
  "updated_at": "2026-11-09T00:20:47Z",
  "url": "https://research.draconitic.com/paper/5c0zw2xq25tnr",
  "venue": "arXiv",
  "versions": []
}