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Comparison of localisation estimation algorithms in Software Defined Wireless Sensor Networks

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dc.contributor.author Cloete, OP
dc.contributor.author Abu-Mahfouz, Adnan MI
dc.contributor.author Hancke, GP
dc.date.accessioned 2019-10-31T07:33:20Z
dc.date.available 2019-10-31T07:33:20Z
dc.date.issued 2019-06
dc.identifier.citation Cloete, O.P., Abu-Mahfouz, A.M.I., and Hancke, G.P. 2019. Comparison of localisation estimation algorithms in Software Defined Wireless Sensor Networks. 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), Vancouver, BC, Canada, 12-14 June 2019 en_US
dc.identifier.isbn 978-1-7281-3666-0
dc.identifier.isbn 978-1-7281-3667-7
dc.identifier.uri https://ieeexplore.ieee.org/abstract/document/8781276
dc.identifier.uri DOI: 10.1109/ISIE.2019.8781276
dc.identifier.uri http://hdl.handle.net/10204/11201
dc.description Copyright: 2019 IEEE. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, kindly consult the publisher's website. en_US
dc.description.abstract The strong relationship between the relevancy of sensory data and the physical location of the from which the data originates, has led to a growth in the need for efficient localisation techniques within Wireless Sensor Networks(WSN). It has been suggested that Software Defined Networking principles might be able to alleviate power draw requirements of localisation techniques. This paper discusses, compares and implements three localisation algorithms in both the data and control-plane using IT-SDN in a contiki-os environment. The three algorithms which were tested in this simulation is: Trilateration, Maximum likelihood estimation and the Linear Least Square Localisation algorithm. This experiment shows that it is possible to offload the computational requirement of localisation into the control-plane. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.ispartofseries Worklist;22660
dc.subject Localisation en_US
dc.subject IT-SDN en_US
dc.subject SDWSN en_US
dc.subject Software-Defined Wireless Sensor Network en_US
dc.subject Wireless Sensor Networks en_US
dc.subject WSN en_US
dc.title Comparison of localisation estimation algorithms in Software Defined Wireless Sensor Networks en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Cloete, O., Abu-Mahfouz, A. M., & Hancke, G. (2019). Comparison of localisation estimation algorithms in Software Defined Wireless Sensor Networks. IEEE. http://hdl.handle.net/10204/11201 en_ZA
dc.identifier.chicagocitation Cloete, OP, Adnan MI Abu-Mahfouz, and GP Hancke. "Comparison of localisation estimation algorithms in Software Defined Wireless Sensor Networks." (2019): http://hdl.handle.net/10204/11201 en_ZA
dc.identifier.vancouvercitation Cloete O, Abu-Mahfouz AM, Hancke G, Comparison of localisation estimation algorithms in Software Defined Wireless Sensor Networks; IEEE; 2019. http://hdl.handle.net/10204/11201 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Cloete, OP AU - Abu-Mahfouz, Adnan MI AU - Hancke, GP AB - The strong relationship between the relevancy of sensory data and the physical location of the from which the data originates, has led to a growth in the need for efficient localisation techniques within Wireless Sensor Networks(WSN). It has been suggested that Software Defined Networking principles might be able to alleviate power draw requirements of localisation techniques. This paper discusses, compares and implements three localisation algorithms in both the data and control-plane using IT-SDN in a contiki-os environment. The three algorithms which were tested in this simulation is: Trilateration, Maximum likelihood estimation and the Linear Least Square Localisation algorithm. This experiment shows that it is possible to offload the computational requirement of localisation into the control-plane. DA - 2019-06 DB - ResearchSpace DP - CSIR KW - Localisation KW - IT-SDN KW - SDWSN KW - Software-Defined Wireless Sensor Network KW - Wireless Sensor Networks KW - WSN LK - https://researchspace.csir.co.za PY - 2019 SM - 978-1-7281-3666-0 SM - 978-1-7281-3667-7 T1 - Comparison of localisation estimation algorithms in Software Defined Wireless Sensor Networks TI - Comparison of localisation estimation algorithms in Software Defined Wireless Sensor Networks UR - http://hdl.handle.net/10204/11201 ER - en_ZA


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