Water-filling-based scheduling for weighted binary freshness in cache update systems
buir.contributor.author | Gamgam, Ege Orkun | |
buir.contributor.author | Akar, Nail | |
buir.contributor.orcid | Gamgam, Ege Orkun|0000-0001-8770-7524 | |
buir.contributor.orcid | Akar, Nail|0000-0001-8143-1379 | |
dc.citation.epage | 8972 | en_US |
dc.citation.issueNumber | 5 | |
dc.citation.spage | 8961 | |
dc.citation.volumeNumber | 11 | |
dc.contributor.author | Gamgam, Ege Orkun | |
dc.contributor.author | Akar, Nail | |
dc.date.accessioned | 2024-03-12T11:46:46Z | |
dc.date.available | 2024-03-12T11:46:46Z | |
dc.date.issued | 2023-10-09 | |
dc.department | Department of Electrical and Electronics Engineering | |
dc.description.abstract | We consider a cache update system with a remote server delivering time-varying contents of multiple Internet of Things (IoT) items with heterogeneous popularities and service times to a local cache so as to keep the items as fresh as possible at the cache. New content for an item arrives at the server according to a Poisson process and the server is equipped with multiple queues each of which holds the most up-to-date content for the corresponding item. In this setting, we study several scheduling policies employed at the server so as to maximize the popularity-weighted binary freshness across the items. The scheduling problem is first formulated as an infinite-horizon average-reward Markov decision process (MDP) which suffers from the curse of dimensionality when the number of items is large. We then propose a water-filling-based scheduling (WFS) policy and its extension, namely, extended WFS (E-WFS) policy, with worst case complexities being quadratic and cubic in the number of items, respectively, based on convex optimization applied to a relaxation of the original system. Simulation results are provided to validate the effectiveness of the proposed policies. | |
dc.description.provenance | Made available in DSpace on 2024-03-12T11:46:46Z (GMT). No. of bitstreams: 1 Water-Filling-Based_Scheduling_for_Weighted_Binary_Freshness_in_Cache_Update_Systems.pdf: 1026340 bytes, checksum: 2fb189ed12bc59df27c0ebe9d8bd5e07 (MD5) Previous issue date: 2023-10-09 | en |
dc.identifier.doi | 10.1109/JIOT.2023.3322360 | |
dc.identifier.issn | 2327-4662 | |
dc.identifier.uri | https://hdl.handle.net/11693/114596 | |
dc.language.iso | en | |
dc.publisher | Institute of Electrical and Electronics Engineers | |
dc.relation.isversionof | https://dx.doi.org/10.1109/JIOT.2023.3322360 | |
dc.rights | CC BY | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.source.title | IEEE Internet of Things Journal | |
dc.subject | Binary freshness | |
dc.subject | Cache update system | |
dc.subject | Markov decision processes (MDPs) | |
dc.subject | Scheduling; water-filling | |
dc.title | Water-filling-based scheduling for weighted binary freshness in cache update systems | |
dc.type | Article |
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