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dc.contributor.authorSingh, Rahul
dc.contributor.authorModiano, Eytan H
dc.date.accessioned2020-07-23T11:59:35Z
dc.date.available2020-07-23T11:59:35Z
dc.date.issued2017-12
dc.identifier.isbn9781509028733
dc.identifier.urihttps://hdl.handle.net/1721.1/126333
dc.description.abstractWe consider the problem of designing risk-sensitive optimal control policies for scheduling packet transmissions in a stochastic wireless network. A single client is connected to an access point (AP) through a wireless channel. Packet transmission incurs a cost C, while packet delivery yields a reward of R units. The client maintains a finite buffer of size B, and a penalty of L units is imposed upon packet loss which occurs due to buffer overflow. We show that the risk-sensitive optimal control policy for such a simple set-up is of threshold type, i.e., it is optimal to carry out packet transmissions only when Q(t), i.e., the queue length at time t exceeds a certain threshold t. It is also shown that the value of the threshold t increases upon increasing the cost per unit packet transmission C. Furthermore, it is also shown that a threshold policy with threshold equal to t is optimal for a set of problems in which cost C lies within an interval [Cl, Cu]. Equations that need to be solved in order to obtain C¡, Cu are also provided.en_US
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionof10.1109/CDC.2017.8264182en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearXiven_US
dc.titleRisk-sensitive optimal control of queuesen_US
dc.typeArticleen_US
dc.identifier.citationSingh, Rahul, Xueying Guo and Eytan Modiano. “Risk-sensitive optimal control of queues.” Paper presented at the 2017 IEEE 56th Annual Conference on Decision and Control (CDC) Conference, Melbourne, VIC, Australia, 12-15 Dec 2017, © 2017, IEEE 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.journal2017 IEEE 56th Annual Conference on Decision and Control (CDC)en_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-10-30T14:14:41Z
dspace.date.submission2019-10-30T14:14:44Z
mit.journal.volume2017en_US
mit.metadata.statusComplete


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