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 |