Publication: Optimal power control and scheduling for energy harvesting wireless networked control systems
dc.contributor.coauthor | N/A | |
dc.contributor.department | N/A | |
dc.contributor.department | Department of Electrical and Electronics Engineering | |
dc.contributor.kuauthor | Karadağ, Göksu | |
dc.contributor.kuauthor | Ergen, Sinem Çöleri | |
dc.contributor.kuprofile | Master Student | |
dc.contributor.kuprofile | Faculty Member | |
dc.contributor.other | Department of Electrical and Electronics Engineering | |
dc.contributor.schoolcollegeinstitute | Graduate School of Sciences and Engineering | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.contributor.yokid | N/A | |
dc.contributor.yokid | 7211 | |
dc.date.accessioned | 2024-11-09T23:59:53Z | |
dc.date.issued | 2019 | |
dc.description.abstract | Communication 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.indexedby | WoS | |
dc.description.indexedby | Scopus | |
dc.description.openaccess | NO | |
dc.description.publisherscope | International | |
dc.identifier.doi | N/A | |
dc.identifier.isbn | 978-1-5386-6528-2 | |
dc.identifier.issn | 2325-3789 | |
dc.identifier.quartile | Q1 | |
dc.identifier.scopus | 2-s2.0-85072326250 | |
dc.identifier.uri | N/A | |
dc.identifier.uri | https://hdl.handle.net/20.500.14288/15716 | |
dc.identifier.wos | 539626100061 | |
dc.keywords | Scheduling | |
dc.keywords | Delays | |
dc.keywords | Energy harvesting | |
dc.keywords | Wireless sensor networks | |
dc.keywords | Wireless communication | |
dc.keywords | Scheduling algorithms | |
dc.keywords | Reliability | |
dc.keywords | Wireless networked control systems | |
dc.keywords | RF energy harvesting | |
dc.keywords | Adaptivity | |
dc.keywords | Power control | |
dc.keywords | Scheduling | |
dc.language | English | |
dc.publisher | IEEE | |
dc.source | 2019 IEEE 20th International Workshop On Signal Processing Advances In Wireless Communications (Spawc 2019) | |
dc.subject | Engineering | |
dc.subject | Electrical and electronic engineering | |
dc.subject | Telecommunications | |
dc.title | Optimal power control and scheduling for energy harvesting wireless networked control systems | |
dc.type | Conference proceeding | |
dspace.entity.type | Publication | |
local.contributor.authorid | 0000-0002-4596-0983 | |
local.contributor.authorid | 0000-0002-7502-3122 | |
local.contributor.kuauthor | Karadağ, Göksu | |
local.contributor.kuauthor | Ergen, Sinem Çöleri | |
relation.isOrgUnitOfPublication | 21598063-a7c5-420d-91ba-0cc9b2db0ea0 | |
relation.isOrgUnitOfPublication.latestForDiscovery | 21598063-a7c5-420d-91ba-0cc9b2db0ea0 |