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{
    "pk": 57192,
    "title": "[Solution] End-to-end Scheduling of Real-time Task Pipelines on Multiprocessors",
    "subtitle": null,
    "abstract": "Task pipelines are common in today’s embedded systems, as data moves from source to sink in sensing-processing-actuation task chains. A real-time task pipeline is constructed by connecting a series of periodic tasks with data buffers. In a time-critical system, end-to-end timing and data-transfer properties of a task pipeline must be guaranteed. A guarantee could be mathematically expressed by assigning constraints to the tasks of a pipeline. However, deriving task scheduling parameters to meet end-to-end guarantees is an NP-hard constraint optimization problem. Hence, a traditional constraint solver is not a suitable runtime solution.\nIn this paper, we present a heuristic constraint solver algorithm, CoPi, to derive the execution times and periods of pipelined tasks that meet the end-to-end constraints and schedulability requirements. We consider two upper bound constraints on a task pipeline: end-to-end delay and loss-rate. After satisfying these constraints, CoPi schedules a pipeline as a set of asynchronous and data independent periodic tasks, under the rate-monotonic scheduling algorithm. Simulations show that CoPi has a comparable pipeline acceptance ratio and significantly better runtime than open-source MINLPsolvers. Furthermore, we use CoPi to map multiple task pipelines to a multiprocessor system. We demonstrate that a partitioned multiprocessor scheduling algorithm coupled with CoPi accommodates dynamically appearing pipelines, while attempting to minimize task migrations.",
    "language": "en",
    "license": {
        "name": "Creative Commons Attribution-NonCommercial  4.0",
        "short_name": "CC BY-NC 4.0",
        "text": "Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.\n\nNonCommercial — You may not use the material for commercial purposes.\n\nNo additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.",
        "url": "https://creativecommons.org/licenses/by-nc/4.0"
    },
    "keywords": [
        {
            "word": "real-time computing"
        }
    ],
    "section": "Articles",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/2h11n6xj",
    "frozenauthors": [
        {
            "first_name": "Soham",
            "middle_name": "",
            "last_name": "Sinha",
            "name_suffix": "",
            "institution": "Department of Computer Science\nBoston University",
            "department": ""
        },
        {
            "first_name": "Richard",
            "middle_name": "",
            "last_name": "West",
            "name_suffix": "",
            "institution": "Department of Computer Science\nBoston University",
            "department": ""
        }
    ],
    "date_submitted": "2022-08-29T05:36:18Z",
    "date_accepted": "2022-08-29T05:36:18Z",
    "date_published": "2022-08-29T07:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/jsys/article/57192/galley/43389/download/"
        }
    ]
}