Publication:
Optimal power control and scheduling for energy harvesting wireless networked control systems

dc.contributor.coauthorN/A
dc.contributor.departmentN/A
dc.contributor.departmentDepartment of Electrical and Electronics Engineering
dc.contributor.kuauthorKaradağ, Göksu
dc.contributor.kuauthorErgen, Sinem Çöleri
dc.contributor.kuprofileMaster Student
dc.contributor.kuprofileFaculty Member
dc.contributor.otherDepartment of Electrical and Electronics Engineering
dc.contributor.schoolcollegeinstituteGraduate School of Sciences and Engineering
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.yokidN/A
dc.contributor.yokid7211
dc.date.accessioned2024-11-09T23:59:53Z
dc.date.issued2019
dc.description.abstractCommunication system design for wireless networked control systems (WNCSs) requires strict timing, reliability and lifetime guarantees despite limited battery resources and the non-idealities introduced by wireless networking such as delays. In this paper, we introduce radio frequency (RF) energy harvesting paradigm into WNCS framework for the first time in the literature. We study the optimal power control, energy harvesting and scheduling problem with the objective of providing maximum level of adaptivity under periodicity, delay and reliability requirements. We show that the power allocation problem is separable from the scheduling problem at optimality and provide the exact expression for optimal power control. The scheduling problem is then formulated as a mixed integer linear programming (MILP) problem and proven to be NP-Hard. For the scheduling, we propose polynomial-Time heuristic algorithms motivated by the analogy between scheduling sensor nodes with energy harvesting requirements over time units and jobs with sequence dependent setup times on identical machines. We prove the theoretical worst-case bound for the performance of these heuristics. We show via extensive simulations that the proposed algorithms perform close-To-optimal and significantly better than Earliest Deadline First (EDF) algorithm in terms of adaptivity, delay, reliability and average runtime.
dc.description.indexedbyWoS
dc.description.indexedbyScopus
dc.description.openaccessNO
dc.description.publisherscopeInternational
dc.identifier.doiN/A
dc.identifier.isbn978-1-5386-6528-2
dc.identifier.issn2325-3789
dc.identifier.quartileQ1
dc.identifier.scopus2-s2.0-85072326250
dc.identifier.uriN/A
dc.identifier.urihttps://hdl.handle.net/20.500.14288/15716
dc.identifier.wos539626100061
dc.keywordsScheduling
dc.keywordsDelays
dc.keywordsEnergy harvesting
dc.keywordsWireless sensor networks
dc.keywordsWireless communication
dc.keywordsScheduling algorithms
dc.keywordsReliability
dc.keywordsWireless networked control systems
dc.keywordsRF energy harvesting
dc.keywordsAdaptivity
dc.keywordsPower control
dc.keywordsScheduling
dc.languageEnglish
dc.publisherIEEE
dc.source2019 IEEE 20th International Workshop On Signal Processing Advances In Wireless Communications (Spawc 2019)
dc.subjectEngineering
dc.subjectElectrical and electronic engineering
dc.subjectTelecommunications
dc.titleOptimal power control and scheduling for energy harvesting wireless networked control systems
dc.typeConference proceeding
dspace.entity.typePublication
local.contributor.authorid0000-0002-4596-0983
local.contributor.authorid0000-0002-7502-3122
local.contributor.kuauthorKaradağ, Göksu
local.contributor.kuauthorErgen, Sinem Çöleri
relation.isOrgUnitOfPublication21598063-a7c5-420d-91ba-0cc9b2db0ea0
relation.isOrgUnitOfPublication.latestForDiscovery21598063-a7c5-420d-91ba-0cc9b2db0ea0

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