Sensor networks simulation framework for target tracking applications: SN-SiFTTA

This work presents a new simulation framework for wireless sensor networks dedicated for target tracking applications named: SN-SiFTTA. SiFTTA does not address routing protocols as they have been studied extensively in the literature. Two scheduling finite state machine models are proposed to contro...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Rababaah, Aaron (author)
منشور في: 2021
الوصول للمادة أونلاين:https://dspace.auk.edu.kw/handle/11675/9613
https://www.inderscience.com/info/inarticle.php?artid=117767
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author Rababaah, Aaron
author_facet Rababaah, Aaron
author_role author
dc.creator.none.fl_str_mv Rababaah, Aaron
dc.date.none.fl_str_mv 2021-09-23
2023-04-09T10:32:27Z
2023-04-09T10:32:27Z
dc.identifier.none.fl_str_mv Rababaah, A. R. (2021). Sensor networks simulation framework for target tracking applications: SN-SiFTTA. International Journal of Web Engineering and Technology, 16(2), 113-138.
https://dspace.auk.edu.kw/handle/11675/9613
https://www.inderscience.com/info/inarticle.php?artid=117767
dc.publisher.none.fl_str_mv International Journal Web Engineering and Technology - IJWET
dc.relation.none.fl_str_mv College of Engineering & Applied Sciences
dc.title.none.fl_str_mv Sensor networks simulation framework for target tracking applications: SN-SiFTTA
dc.type.none.fl_str_mv Peer Reviewed
Journal Article
info:eu-repo/semantics/publishedVersion
description This work presents a new simulation framework for wireless sensor networks dedicated for target tracking applications named: SN-SiFTTA. SiFTTA does not address routing protocols as they have been studied extensively in the literature. Two scheduling finite state machine models are proposed to control the behaviour of the sensor nodes and cluster heads. Four different deployment methods are proposed and investigated using four performance metrics: target tracking accuracy (TTA), energy efficiency index (EEI), quality of clustering index (QCI) and deployment feasibility. A simulator with friendly and interactive graphical user interface was developed using Matlab integrated development environment. The simulator provides rich environment that allows the user to customized wide varieties of scenarios. Among these, we focus on deployment method effects on the aforementioned four performance metrics. Four hundred experiments were conducted 100 per each deployment method of global random, local random, grid random and uniform grid. After analysing the experimental results, the study suggested a weighted-criteria formula to select the best deployment method considering all performance metrics to avoid bias and to ensure problem context relevance.
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identifier_str_mv Rababaah, A. R. (2021). Sensor networks simulation framework for target tracking applications: SN-SiFTTA. International Journal of Web Engineering and Technology, 16(2), 113-138.
network_acronym_str AUKR
network_name_str AU Kuwait Rep
oai_identifier_str oai:dspace.auk.edu.kw:11675/9613
publishDate 2021
publisher.none.fl_str_mv International Journal Web Engineering and Technology - IJWET
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling Sensor networks simulation framework for target tracking applications: SN-SiFTTARababaah, AaronThis work presents a new simulation framework for wireless sensor networks dedicated for target tracking applications named: SN-SiFTTA. SiFTTA does not address routing protocols as they have been studied extensively in the literature. Two scheduling finite state machine models are proposed to control the behaviour of the sensor nodes and cluster heads. Four different deployment methods are proposed and investigated using four performance metrics: target tracking accuracy (TTA), energy efficiency index (EEI), quality of clustering index (QCI) and deployment feasibility. A simulator with friendly and interactive graphical user interface was developed using Matlab integrated development environment. The simulator provides rich environment that allows the user to customized wide varieties of scenarios. Among these, we focus on deployment method effects on the aforementioned four performance metrics. Four hundred experiments were conducted 100 per each deployment method of global random, local random, grid random and uniform grid. After analysing the experimental results, the study suggested a weighted-criteria formula to select the best deployment method considering all performance metrics to avoid bias and to ensure problem context relevance.International Journal Web Engineering and Technology - IJWET2023-04-09T10:32:27Z2023-04-09T10:32:27Z2021-09-23Peer ReviewedJournal Articleinfo:eu-repo/semantics/publishedVersionRababaah, A. R. (2021). Sensor networks simulation framework for target tracking applications: SN-SiFTTA. International Journal of Web Engineering and Technology, 16(2), 113-138.https://dspace.auk.edu.kw/handle/11675/9613https://www.inderscience.com/info/inarticle.php?artid=117767College of Engineering & Applied Sciencesoai:dspace.auk.edu.kw:11675/96132023-04-09T10:32:27Z
spellingShingle Sensor networks simulation framework for target tracking applications: SN-SiFTTA
Rababaah, Aaron
status_str publishedVersion
title Sensor networks simulation framework for target tracking applications: SN-SiFTTA
title_full Sensor networks simulation framework for target tracking applications: SN-SiFTTA
title_fullStr Sensor networks simulation framework for target tracking applications: SN-SiFTTA
title_full_unstemmed Sensor networks simulation framework for target tracking applications: SN-SiFTTA
title_short Sensor networks simulation framework for target tracking applications: SN-SiFTTA
title_sort Sensor networks simulation framework for target tracking applications: SN-SiFTTA
url https://dspace.auk.edu.kw/handle/11675/9613
https://www.inderscience.com/info/inarticle.php?artid=117767