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dc.contributor.authorKadota, Igor
dc.contributor.authorModiano, Eytan
dc.date.accessioned2021-10-27T19:57:24Z
dc.date.available2021-10-27T19:57:24Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/1721.1/133960
dc.description.abstract© 2002-2012 IEEE. We consider a wireless network with a base station serving multiple traffic streams to different destinations. Packets from each stream arrive to the base station according to a stochastic process and are enqueued in a separate (per stream) queue. The queueing discipline controls which packet within each queue is available for transmission. The base station decides, at every time t, which stream to serve to the corresponding destination. The goal of scheduling decisions is to keep the information at the destinations fresh. Information freshness is captured by the Age of Information (AoI) metric. In this paper, we derive a lower bound on the AoI performance achievable by any given network operating under any queueing discipline. Then, we consider three common queueing disciplines and develop both an Optimal Stationary Randomized policy and a Max-Weight policy under each discipline. Our approach allows us to evaluate the combined impact of the stochastic arrivals, queueing discipline and scheduling policy on AoI. We evaluate the AoI performance both analytically and using simulations. Numerical results show that the performance of the Max-Weight policy is close to the analytical lower bound.
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.isversionof10.1109/TMC.2019.2959774
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.sourcearXiv
dc.titleMinimizing the Age of Information in Wireless Networks with Stochastic Arrivals
dc.typeArticle
dc.contributor.departmentMassachusetts Institute of Technology. Laboratory for Information and Decision Systems
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronautics
dc.contributor.departmentMassachusetts Institute of Technology. Operations Research Center
dc.relation.journalIEEE Transactions on Mobile Computing
dc.eprint.versionOriginal manuscript
dc.type.urihttp://purl.org/eprint/type/JournalArticle
eprint.statushttp://purl.org/eprint/status/NonPeerReviewed
dc.date.updated2021-05-03T17:17:31Z
dspace.orderedauthorsKadota, I; Modiano, E
dspace.date.submission2021-05-03T17:17:32Z
mit.journal.volume20
mit.journal.issue3
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusAuthority Work and Publication Information Needed


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