Reservation frame slotted ALOHA for multi-class IOT networks

Simple item page
buir.advisorAkar, Nail
dc.contributor.authorFiaz, Mahzeb
dc.date.accessioned2019-01-30T05:36:46Z
dc.date.available2019-01-30T05:36:46Z
dc.date.copyright2019-01
dc.date.issued2019-01
dc.date.submitted2019-01-28
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (M.S.) : Bilkent University, Department of Electrical and Electronics Engineering, İhsan Doğramacı Bilkent University, 2019.en_US
dc.descriptionIncludes bibliographical references (leaves 64-68).en_US
dc.description.abstractThe Internet of Things (IoT) is a promising technology capable of revolutionizing our work and daily lives. ALOHA based medium access schemes are widely used in IoT applications due to their low complexity despite lower throughput figures. In this study, we aim to improve the performance of Frame Slotted Aloha (FSA) for a single hop IoT network without increasing the overall complexity. Duty cycling is a key concept for managing energy consumption of wireless networks with battery powered nodes having maximum duty cycle constraints. The goal of this study is to improve the performance of frame slotted Aloha by exploiting duty cycle patterns in these networks and using reservations in advance. We discuss the system model for a single class IoT network and study via simulations the performance of Reservation Frame Slotted Aloha (RFSA) as compared to FSA, as well as the performance implications of different system parameters related to traffic patterns. With the insight gained from this preliminary study, we next study a multi-class IoT network with nodes belonging to different classes with different duty cycle constraints. Adopting RFSA for such a network requires different schemes for allocating channel resources for each class. We propose several static and dynamic channel allocation schemes based on our traffic model and study their performance as compared to FSA. Static partitioning has better performance for low traffic loads but dynamic partitioning offers better throughput at higher traffic loads. Selection of an appropriate channel allocation scheme can vary according to the load as well as several system parameters of the network.en_US
dc.description.provenanceSubmitted by Betül Özen (ozen@bilkent.edu.tr) on 2019-01-30T05:36:46Z No. of bitstreams: 1 Mahzeb Fıaz Thesis.pdf: 1509125 bytes, checksum: 30544dd805b28ab63dfbfa101a21d9fe (MD5)en
dc.description.provenanceMade available in DSpace on 2019-01-30T05:36:46Z (GMT). No. of bitstreams: 1 Mahzeb Fıaz Thesis.pdf: 1509125 bytes, checksum: 30544dd805b28ab63dfbfa101a21d9fe (MD5) Previous issue date: 2019-01en
dc.description.statementofresponsibilityby Mahzeb Fiazen_US
dc.format.extentxiii, 68 leaves : illustrations, charts ; 30 cm.en_US
dc.identifier.itemidB159416
dc.identifier.urihttp://hdl.handle.net/11693/48494
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectALOHAen_US
dc.subjectInternet of thingsen_US
dc.subjectFrame slotted ALOHAen_US
dc.subjectR-ALOHAen_US
dc.subjectChannel allocationen_US
dc.titleReservation frame slotted ALOHA for multi-class IOT networksen_US
dc.title.alternativeRezervasyon tabanlı çerçeve-dilimli ALOHANIN çok-sınıflı IOT ağlar için kullanılmasıen_US
dc.typeThesisen_US
thesis.degree.disciplineElectrical and Electronic Engineering
thesis.degree.grantorBilkent University
thesis.degree.levelMaster's
thesis.degree.nameMS (Master of Science)

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Mahzeb Fıaz Thesis.pdf
Size:
1.44 MB
Format:
Adobe Portable Document Format
Description:
Full printable version
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Graduate School of Engineering and Science