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dc.contributor.authorKadota, Igor
dc.contributor.authorModiano, Eytan H
dc.date.accessioned2020-07-22T13:43:42Z
dc.date.available2020-07-22T13:43:42Z
dc.date.issued2019-07
dc.identifier.isbn978-1-4503-6764
dc.identifier.urihttps://hdl.handle.net/1721.1/126303
dc.description.abstractWe 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.en_US
dc.language.isoen
dc.publisherAssociation for Computing Machinery (ACM)en_US
dc.relation.isversionof10.1145/3323679.3326520en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT web domainen_US
dc.titleMinimizing the Age of Information in Wireless Networks with Stochastic Arrivalsen_US
dc.typeArticleen_US
dc.identifier.citationKadota, Igor and Eytan Modiano. “Minimizing the Age of Information in Wireless Networks with Stochastic Arrivals.” Paper presented at Mobihoc ’19, Catania, Italy, July 2-5 2019, Association for Computing Machinery (ACM) © 2019 The Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Laboratory for Information and Decision Systemsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronauticsen_US
dc.relation.journalMobihoc ’19en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-10-30T16:05:17Z
dspace.date.submission2019-10-30T16:05:22Z
mit.journal.volume2019en_US
mit.metadata.statusComplete


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