Exact analytical model of age of information in multi-source status update systems with per-source queueing

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buir.contributor.authorGamgam, Ege Orkun
buir.contributor.authorAkar, Nail
buir.contributor.orcidGamgam, Ege Orkun|0000-0001-8770-7524
buir.contributor.orcidAkar, Nail|0000-0001-8143-1379
dc.citation.epage20718en_US
dc.citation.issueNumber20en_US
dc.citation.spage20706en_US
dc.citation.volumeNumber9en_US
dc.contributor.authorGamgam, Ege Orkun
dc.contributor.authorAkar, Nail
dc.date.accessioned2023-02-25T07:59:35Z
dc.date.available2023-02-25T07:59:35Z
dc.date.issued2022-05-27
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractWe study a multisource status update system with Poisson information packet arrivals and exponentially distributed service times. The server is equipped with a waiting room holding the freshest packet from each source referred to as single buffer per-source queueing (SBPSQ). The sources are assumed to be equally important, i.e., (nonweighted) average Age of Information (AoI) or average age violation probability are used as the information freshness metrics to optimize for, and subsequently, two symmetric SBPSQ-based scheduling policies are studied in this article, namely, first source first serve (FSFS) and the earliest served first serve (ESFS) policies. By employing the theory of Markov fluid queues (MFQs), an analytical model is proposed to obtain the exact distribution of the AoI for each source when the FSFS and ESFS policies are employed at the server. Additionally, a benchmark scheduling-free scheme named single buffer with replacement (SBR), which uses a single buffer to hold the freshest packet across all sources, is also studied with a similar but less complex analytical model. We comparatively study the performance of the three policies through numerical examples in terms of the average AoI and the age violation probability averaged across all sources, in a scenario of sources possessing different traffic intensities but sharing a common service time.en_US
dc.description.provenanceSubmitted by Evrim Ergin (eergin@bilkent.edu.tr) on 2023-02-25T07:59:35Z No. of bitstreams: 1 Exact_analytical_model_of_age_of_information_in_multi-source_status_update_systems_with_per-source_queueing.pdf: 1644306 bytes, checksum: c63adf4f1c0aef002a7820ff23fd42d1 (MD5)en
dc.description.provenanceMade available in DSpace on 2023-02-25T07:59:35Z (GMT). No. of bitstreams: 1 Exact_analytical_model_of_age_of_information_in_multi-source_status_update_systems_with_per-source_queueing.pdf: 1644306 bytes, checksum: c63adf4f1c0aef002a7820ff23fd42d1 (MD5) Previous issue date: 2022-05-27en
dc.identifier.doi10.1109/JIOT.2022.3178657en_US
dc.identifier.eissn2327-4662
dc.identifier.urihttp://hdl.handle.net/11693/111717
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttps://dx.doi.org/10.1109/JIOT.2022.3178657en_US
dc.source.titleIEEE Internet of Things Journalen_US
dc.subjectAge of Information (AoI)en_US
dc.subjectBuffer managementen_US
dc.subjectMarkov fluid queues (MFQs)en_US
dc.subjectMultisource queueing modelen_US
dc.subjectSchedulingen_US
dc.titleExact analytical model of age of information in multi-source status update systems with per-source queueingen_US
dc.typeArticleen_US

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