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    "abbrevTitle": "SMPTE Motion Imaging Jour.",
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      "source": "parsed",
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    "abstract": "Virtual Reality (VR) and other forms of extended reality (XR) are beginning to drive deep immersive experiences for premium entertainment and sports content. Data is streamed directly to a headset, requiring the underlying network to accommodate constant throughput of over 25 Mbits/s to support 4K (UHD-1) and over 50 Mbits/s for 8K (UHD-2). Even with the availability of ample capacity in both wireline and 5G mobile networks, network resources along the delivery path may not be shared equitably to meet immersive video's stringent delivery requirements and consequently lead to poor user experience. This study introduces a novel method for customizing existing content delivery networks to support stringent immersive video QoE requirements by increasing visibility into the last mile network by selecting the best congestion control (CC) scheme based on the network and varying content characteristics including machine learning to customize CC when possible.",
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    "authors": [
      {
        "name": "Sanjay Mishra"
      },
      {
        "name": "Ravid Hadar"
      },
      {
        "name": "Brian Stevenson"
      },
      {
        "name": "ErinRose Widner"
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      "year": "2024",
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    "docId": "10.5594-JMI.2024-RLWZ3064",
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    "docLabel": "MIJ 2024, Volume 133, Number 3 (pp. 56 to 64)",
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      "source": "parsed",
      "updated": "2026-07-10T20:01:10.986Z"
    },
    "docTitle": "Optimizing the Virtual Reality Experience Using a 360° View of Client and Network Data",
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    "docType": "Journal Article",
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      "source": "parsed",
      "updated": "2026-07-10T20:01:10.986Z"
    },
    "doi": "10.5594/JMI.2024/RLWZ3064",
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      "updated": "2026-07-10T20:01:10.986Z"
    },
    "href": "https://doi.org/10.5594/JMI.2024/RLWZ3064",
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      "updated": "2026-07-10T20:01:10.986Z"
    },
    "issn": {
      "electronic": "2160-2492",
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        "updated": "2026-07-10T20:01:10.986Z"
      },
      "print": "1545-0279",
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        "updated": "2026-07-10T20:01:10.986Z"
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    "issn$meta": {
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    "journalAcronym": "MIJ",
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    "journalTitle": "SMPTE Motion Imaging Journal",
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    "keywords": [
      "Immersive Video",
      "Extended Reality",
      "Congestion Control",
      "Edge Caching",
      "QoE"
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      "note": "Long-tail keyword cleanup (keywordLongTailApply.js): prose/contentless terms dropped, acronym casing + typos fixed, duplicate variants folded; all surviving terms indexed in controlledKeywords.",
      "source": "resolved",
      "updated": "2026-07-14T16:29:38.680Z"
    },
    "number": "3",
    "number$meta": {
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      "source": "parsed",
      "updated": "2026-07-10T20:01:10.986Z"
    },
    "pages": "56–64",
    "pages$meta": {
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    "publicationDate": "2024-05-01",
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    "publisher": "SMPTE",
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      "active": true,
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    "volume": "133",
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