KHOPCA clustering algorithm - Revision history

JJMC89 bot III: Moving :Category:Algorithms in graph theory to :Category:Graph algorithms per Wikipedia:Categories for discussion/Log/2024 October 4

2024-10-12T19:56:47Z

Moving Category:Algorithms in graph theory to Category:Graph algorithms per Wikipedia:Categories for discussion/Log/2024 October 4

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	{{DEFAULTSORT:KHOPCA clustering algorithm}}		{{DEFAULTSORT:KHOPCA clustering algorithm}}
	[[Category:~~Algorithms~~ ~~in graph theory~~]]		[[Category:Graph algorithms]]

JJMC89 bot III: Moving :Category:Graph algorithms to :Category:Algorithms in graph theory per Wikipedia:Categories for discussion/Log/2024 October 4#Category:Graph algorithms

2024-10-12T02:24:00Z

Moving Category:Graph algorithms to Category:Algorithms in graph theory per Wikipedia:Categories for discussion/Log/2024 October 4#Category:Graph algorithms

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	{{DEFAULTSORT:KHOPCA clustering algorithm}}		{{DEFAULTSORT:KHOPCA clustering algorithm}}
	[[Category:~~Graph~~ ~~algorithms~~]]		[[Category:Algorithms in graph theory]]

Frap: /* Examples */

2024-03-14T13:08:21Z

Examples

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	== Examples ==		== Examples ==

	=== ~~1-D~~ ===		=== 1D ===
	An exemplary sequence of state transitions applying the described four rules is illustrated below.		An exemplary sequence of state transitions applying the described four rules is illustrated below.

	[[File:KHOPCA 1D example 1.png\|frameless]]		[[File:KHOPCA 1D example 1.png\|frameless]]

	=== ~~2-D~~ ===		=== 2D ===
	KHOPCA acting in a dynamic ~~2-D~~ simulation. The geometry is based on a geometric random graph; all existing links are drawn in this network.		KHOPCA acting in a dynamic 2D simulation. The geometry is based on a geometric random graph; all existing links are drawn in this network.

	[[File:KHOPCA 2D k3a.jpg\|frameless]]		[[File:KHOPCA 2D k3a.jpg\|frameless]]

	=== ~~3-D~~ ===		=== 3D ===
	KHOPCA also works in a dynamic ~~3-D~~ environment. The cluster connections are illustrated with bold lines.		KHOPCA also works in a dynamic 3D environment. The cluster connections are illustrated with bold lines.

	[[File:KHOPCA 3D example 2.png\|frameless]]		[[File:KHOPCA 3D example 2.png\|frameless]]

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← Previous revision		Revision as of 19:39, 7 August 2023
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	[[File:KHOPCA 3D example 1.png\|thumb\|KHOPCA running in a 3-D environment.]]		[[File:KHOPCA 3D example 1.png\|thumb\|KHOPCA running in a 3-D environment.]]
	'''KHOPCA''' is an adaptive [[clustering algorithm]] originally developed for dynamic networks. KHOPCA (<math display="inline">k</math>-hop clustering algorithm) provides a fully [[Distributed computing\|distributed]] and localized approach to group elements such as nodes in a network according to their distance from each other.<ref>{{Cite ~~journal~~\|~~last~~=Brust\|~~first~~=Matthias R.\|last2=Frey\|first2=Hannes\|last3=Rothkugel\|first3=Steffen~~\|date=2007-01-01~~\|title~~=Adaptive Multi-hop Clustering in Mobile Networks\|journal~~=Proceedings of the 4th ~~International~~ ~~Conference~~ on ~~Mobile~~ ~~Technology~~, ~~Applications~~, and ~~Systems~~ and the 1st ~~International~~ ~~Symposium~~ on Computer ~~Human~~ ~~Interaction~~ in ~~Mobile~~ ~~Technology~~\|series=Mobility '07\|location=New York, NY, USA\|publisher=ACM\|pages=132–138\|doi=10.1145/1378063.1378086\|isbn=9781595938190}}</ref><ref name=":0">{{Cite ~~journal~~\|~~last~~=Brust\|~~first~~=Matthias R.\|last2=Frey\|first2=Hannes\|last3=Rothkugel\|first3=Steffen~~\|date=2008-01-01~~\|title~~=Dynamic Multi-hop Clustering for Mobile Hybrid Wireless Networks\|journal~~=Proceedings of the 2nd ~~International~~ ~~Conference~~ on Ubiquitous ~~Information~~ ~~Management~~ and ~~Communication~~\|series=ICUIMC '08\|location=New York, NY, USA\|publisher=ACM\|pages=130–135\|doi=10.1145/1352793.1352820\|isbn=9781595939937}}</ref> KHOPCA operates proactively through a simple set of rules that defines clusters, which are optimal with respect to the applied distance function.		'''KHOPCA''' is an adaptive [[clustering algorithm]] originally developed for dynamic networks. KHOPCA (<math display="inline">k</math>-hop clustering algorithm) provides a fully [[Distributed computing\|distributed]] and localized approach to group elements such as nodes in a network according to their distance from each other.<ref>{{Cite book\|last1=Brust\|first1=Matthias R.\|last2=Frey\|first2=Hannes\|last3=Rothkugel\|first3=Steffen\|title=Proceedings of the 4th international conference on mobile technology, applications, and systems and the 1st international symposium on Computer human interaction in mobile technology \|chapter=Adaptive multi-hop clustering in mobile networks \|date=2007-01-01\|series=Mobility '07\|location=New York, NY, USA\|publisher=ACM\|pages=132–138\|doi=10.1145/1378063.1378086\|isbn=9781595938190\|s2cid=33469900 }}</ref><ref name=":0">{{Cite book\|last1=Brust\|first1=Matthias R.\|last2=Frey\|first2=Hannes\|last3=Rothkugel\|first3=Steffen\|title=Proceedings of the 2nd international conference on Ubiquitous information management and communication \|chapter=Dynamic multi-hop clustering for mobile hybrid wireless networks \|date=2008-01-01\|series=ICUIMC '08\|location=New York, NY, USA\|publisher=ACM\|pages=130–135\|doi=10.1145/1352793.1352820\|isbn=9781595939937\|s2cid=15200455 }}</ref> KHOPCA operates proactively through a simple set of rules that defines clusters, which are optimal with respect to the applied distance function.

	KHOPCA's clustering process explicitly supports joining and leaving of nodes, which makes KHOPCA suitable for highly dynamic networks. However, it has been demonstrated that KHOPCA also performs in static networks.<ref name=":0" />		KHOPCA's clustering process explicitly supports joining and leaving of nodes, which makes KHOPCA suitable for highly dynamic networks. However, it has been demonstrated that KHOPCA also performs in static networks.<ref name=":0" />

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2022-08-24T03:22:00Z

top: task, replaced: 2Nd → 2nd

← Previous revision		Revision as of 03:22, 24 August 2022
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	[[File:KHOPCA 3D example 1.png\|thumb\|KHOPCA running in a 3-D environment.]]		[[File:KHOPCA 3D example 1.png\|thumb\|KHOPCA running in a 3-D environment.]]
	'''KHOPCA''' is an adaptive [[clustering algorithm]] originally developed for dynamic networks. KHOPCA (<math display="inline">k</math>-hop clustering algorithm) provides a fully [[Distributed computing\|distributed]] and localized approach to group elements such as nodes in a network according to their distance from each other.<ref>{{Cite journal\|last=Brust\|first=Matthias R.\|last2=Frey\|first2=Hannes\|last3=Rothkugel\|first3=Steffen\|date=2007-01-01\|title=Adaptive Multi-hop Clustering in Mobile Networks\|journal=Proceedings of the 4th International Conference on Mobile Technology, Applications, and Systems and the 1st International Symposium on Computer Human Interaction in Mobile Technology\|series=Mobility '07\|location=New York, NY, USA\|publisher=ACM\|pages=132–138\|doi=10.1145/1378063.1378086\|isbn=9781595938190}}</ref><ref name=":0">{{Cite journal\|last=Brust\|first=Matthias R.\|last2=Frey\|first2=Hannes\|last3=Rothkugel\|first3=Steffen\|date=2008-01-01\|title=Dynamic Multi-hop Clustering for Mobile Hybrid Wireless Networks\|journal=Proceedings of the ~~2Nd~~ International Conference on Ubiquitous Information Management and Communication\|series=ICUIMC '08\|location=New York, NY, USA\|publisher=ACM\|pages=130–135\|doi=10.1145/1352793.1352820\|isbn=9781595939937}}</ref> KHOPCA operates proactively through a simple set of rules that defines clusters, which are optimal with respect to the applied distance function.		'''KHOPCA''' is an adaptive [[clustering algorithm]] originally developed for dynamic networks. KHOPCA (<math display="inline">k</math>-hop clustering algorithm) provides a fully [[Distributed computing\|distributed]] and localized approach to group elements such as nodes in a network according to their distance from each other.<ref>{{Cite journal\|last=Brust\|first=Matthias R.\|last2=Frey\|first2=Hannes\|last3=Rothkugel\|first3=Steffen\|date=2007-01-01\|title=Adaptive Multi-hop Clustering in Mobile Networks\|journal=Proceedings of the 4th International Conference on Mobile Technology, Applications, and Systems and the 1st International Symposium on Computer Human Interaction in Mobile Technology\|series=Mobility '07\|location=New York, NY, USA\|publisher=ACM\|pages=132–138\|doi=10.1145/1378063.1378086\|isbn=9781595938190}}</ref><ref name=":0">{{Cite journal\|last=Brust\|first=Matthias R.\|last2=Frey\|first2=Hannes\|last3=Rothkugel\|first3=Steffen\|date=2008-01-01\|title=Dynamic Multi-hop Clustering for Mobile Hybrid Wireless Networks\|journal=Proceedings of the 2nd International Conference on Ubiquitous Information Management and Communication\|series=ICUIMC '08\|location=New York, NY, USA\|publisher=ACM\|pages=130–135\|doi=10.1145/1352793.1352820\|isbn=9781595939937}}</ref> KHOPCA operates proactively through a simple set of rules that defines clusters, which are optimal with respect to the applied distance function.

	KHOPCA's clustering process explicitly supports joining and leaving of nodes, which makes KHOPCA suitable for highly dynamic networks. However, it has been demonstrated that KHOPCA also performs in static networks.<ref name=":0" />		KHOPCA's clustering process explicitly supports joining and leaving of nodes, which makes KHOPCA suitable for highly dynamic networks. However, it has been demonstrated that KHOPCA also performs in static networks.<ref name=":0" />

John of Reading: Typo/general fixes, replaced: coincidently → coincidentally

2020-08-25T19:00:35Z

Typo/general fixes, replaced: coincidently → coincidentally

← Previous revision		Revision as of 19:00, 25 August 2020
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	=== Rule 2 ===		=== Rule 2 ===
	[[File:KHOPCA rule 2 a.png\|thumb\|KHOPCA rule 2]]		[[File:KHOPCA rule 2 a.png\|thumb\|KHOPCA rule 2]]
	The second rule deals with the situation where nodes in a neighborhood are on the minimum weight level. This situation can happen if, for instance, the initial configuration assigns the minimum weight to all nodes. If there is a neighborhood with all nodes having the minimum weight level, the node <math display="inline">n</math> declares itself as cluster center. Even if ~~coincidently~~ all nodes declare themselves as cluster centers, the conflict situation will be resolved by one of the other rules.<syntaxhighlight lang="java" line="1">		The second rule deals with the situation where nodes in a neighborhood are on the minimum weight level. This situation can happen if, for instance, the initial configuration assigns the minimum weight to all nodes. If there is a neighborhood with all nodes having the minimum weight level, the node <math display="inline">n</math> declares itself as cluster center. Even if coincidentally all nodes declare themselves as cluster centers, the conflict situation will be resolved by one of the other rules.<syntaxhighlight lang="java" line="1">
	if max(W(N(n)) == MIN & w_n == MIN		if max(W(N(n)) == MIN & w_n == MIN
	w_n = MAX;		w_n = MAX;
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	== References ==		== References ==
	{{Reflist}}		{{Reflist}}



	{{DEFAULTSORT:KHOPCA clustering algorithm}}		{{DEFAULTSORT:KHOPCA clustering algorithm}}

Geysirhead: removed Category:Algorithms; added Category:Graph algorithms using HotCat

2020-05-02T08:46:06Z

removed Category:Algorithms; added Category:Graph algorithms using HotCat

← Previous revision		Revision as of 08:46, 2 May 2020
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	{{DEFAULTSORT:KHOPCA clustering algorithm}}		{{DEFAULTSORT:KHOPCA clustering algorithm}}
	[[Category:~~Algorithms~~]]		[[Category:Graph algorithms]]

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← Previous revision		Revision as of 02:45, 14 July 2019
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	[[File:KHOPCA 3D example 1.png\|thumb\|KHOPCA running in a 3-D environment.]]		[[File:KHOPCA 3D example 1.png\|thumb\|KHOPCA running in a 3-D environment.]]
	'''KHOPCA''' is an adaptive [[clustering algorithm]] originally developed for dynamic networks. KHOPCA (<math display="inline">k</math>-hop clustering algorithm) provides a fully [[Distributed computing\|distributed]] and localized approach to group elements such as nodes in a network according to their distance from each other.<ref>{{Cite journal\|last=Brust\|first=Matthias R.\|last2=Frey\|first2=Hannes\|last3=Rothkugel\|first3=Steffen\|date=2007-01-01\|title=Adaptive Multi-hop Clustering in Mobile Networks~~\|url=http://doi.acm.org/10.1145/1378063.1378086~~\|journal=Proceedings of the 4th International Conference on Mobile Technology, Applications, and Systems and the 1st International Symposium on Computer Human Interaction in Mobile Technology\|series=Mobility '07\|location=New York, NY, USA\|publisher=ACM\|pages=132–138\|doi=10.1145/1378063.1378086\|isbn=9781595938190}}</ref><ref name=":0">{{Cite journal\|last=Brust\|first=Matthias R.\|last2=Frey\|first2=Hannes\|last3=Rothkugel\|first3=Steffen\|date=2008-01-01\|title=Dynamic Multi-hop Clustering for Mobile Hybrid Wireless Networks~~\|url=http://doi.acm.org/10.1145/1352793.1352820~~\|journal=Proceedings of the 2Nd International Conference on Ubiquitous Information Management and Communication\|series=ICUIMC '08\|location=New York, NY, USA\|publisher=ACM\|pages=130–135\|doi=10.1145/1352793.1352820\|isbn=9781595939937}}</ref> KHOPCA operates proactively through a simple set of rules that defines clusters, which are optimal with respect to the applied distance function.		'''KHOPCA''' is an adaptive [[clustering algorithm]] originally developed for dynamic networks. KHOPCA (<math display="inline">k</math>-hop clustering algorithm) provides a fully [[Distributed computing\|distributed]] and localized approach to group elements such as nodes in a network according to their distance from each other.<ref>{{Cite journal\|last=Brust\|first=Matthias R.\|last2=Frey\|first2=Hannes\|last3=Rothkugel\|first3=Steffen\|date=2007-01-01\|title=Adaptive Multi-hop Clustering in Mobile Networks\|journal=Proceedings of the 4th International Conference on Mobile Technology, Applications, and Systems and the 1st International Symposium on Computer Human Interaction in Mobile Technology\|series=Mobility '07\|location=New York, NY, USA\|publisher=ACM\|pages=132–138\|doi=10.1145/1378063.1378086\|isbn=9781595938190}}</ref><ref name=":0">{{Cite journal\|last=Brust\|first=Matthias R.\|last2=Frey\|first2=Hannes\|last3=Rothkugel\|first3=Steffen\|date=2008-01-01\|title=Dynamic Multi-hop Clustering for Mobile Hybrid Wireless Networks\|journal=Proceedings of the 2Nd International Conference on Ubiquitous Information Management and Communication\|series=ICUIMC '08\|location=New York, NY, USA\|publisher=ACM\|pages=130–135\|doi=10.1145/1352793.1352820\|isbn=9781595939937}}</ref> KHOPCA operates proactively through a simple set of rules that defines clusters, which are optimal with respect to the applied distance function.

	KHOPCA's clustering process explicitly supports joining and leaving of nodes, which makes KHOPCA suitable for highly dynamic networks. However, it has been demonstrated that KHOPCA also performs in static networks.<ref name=":0" />		KHOPCA's clustering process explicitly supports joining and leaving of nodes, which makes KHOPCA suitable for highly dynamic networks. However, it has been demonstrated that KHOPCA also performs in static networks.<ref name=":0" />

Speng dahl at 09:57, 25 October 2017

2017-10-25T09:57:18Z

← Previous revision		Revision as of 09:57, 25 October 2017
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	[[File:KHOPCA 3D example 1.png\|thumb\|KHOPCA running in a 3-D environment.]]		[[File:KHOPCA 3D example 1.png\|thumb\|KHOPCA running in a 3-D environment.]]
	'''KHOPCA''' is a [[clustering algorithm]] ~~designed~~ for dynamic networks. KHOPCA (<math display="inline">k</math>-hop clustering algorithm) provides a fully [[Distributed computing\|distributed]] and localized approach to group elements such as nodes in a network according to their distance from each other.<ref>{{Cite journal\|last=Brust\|first=Matthias R.\|last2=Frey\|first2=Hannes\|last3=Rothkugel\|first3=Steffen\|date=2007-01-01\|title=Adaptive Multi-hop Clustering in Mobile Networks\|url=http://doi.acm.org/10.1145/1378063.1378086\|journal=Proceedings of the 4th International Conference on Mobile Technology, Applications, and Systems and the 1st International Symposium on Computer Human Interaction in Mobile Technology\|series=Mobility '07\|location=New York, NY, USA\|publisher=ACM\|pages=132–138\|doi=10.1145/1378063.1378086\|isbn=9781595938190}}</ref><ref name=":0">{{Cite journal\|last=Brust\|first=Matthias R.\|last2=Frey\|first2=Hannes\|last3=Rothkugel\|first3=Steffen\|date=2008-01-01\|title=Dynamic Multi-hop Clustering for Mobile Hybrid Wireless Networks\|url=http://doi.acm.org/10.1145/1352793.1352820\|journal=Proceedings of the 2Nd International Conference on Ubiquitous Information Management and Communication\|series=ICUIMC '08\|location=New York, NY, USA\|publisher=ACM\|pages=130–135\|doi=10.1145/1352793.1352820\|isbn=9781595939937}}</ref> KHOPCA operates proactively through a simple set of rules that defines clusters, which are optimal with respect to the applied distance function.		'''KHOPCA''' is an adaptive [[clustering algorithm]] originally developed for dynamic networks. KHOPCA (<math display="inline">k</math>-hop clustering algorithm) provides a fully [[Distributed computing\|distributed]] and localized approach to group elements such as nodes in a network according to their distance from each other.<ref>{{Cite journal\|last=Brust\|first=Matthias R.\|last2=Frey\|first2=Hannes\|last3=Rothkugel\|first3=Steffen\|date=2007-01-01\|title=Adaptive Multi-hop Clustering in Mobile Networks\|url=http://doi.acm.org/10.1145/1378063.1378086\|journal=Proceedings of the 4th International Conference on Mobile Technology, Applications, and Systems and the 1st International Symposium on Computer Human Interaction in Mobile Technology\|series=Mobility '07\|location=New York, NY, USA\|publisher=ACM\|pages=132–138\|doi=10.1145/1378063.1378086\|isbn=9781595938190}}</ref><ref name=":0">{{Cite journal\|last=Brust\|first=Matthias R.\|last2=Frey\|first2=Hannes\|last3=Rothkugel\|first3=Steffen\|date=2008-01-01\|title=Dynamic Multi-hop Clustering for Mobile Hybrid Wireless Networks\|url=http://doi.acm.org/10.1145/1352793.1352820\|journal=Proceedings of the 2Nd International Conference on Ubiquitous Information Management and Communication\|series=ICUIMC '08\|location=New York, NY, USA\|publisher=ACM\|pages=130–135\|doi=10.1145/1352793.1352820\|isbn=9781595939937}}</ref> KHOPCA operates proactively through a simple set of rules that defines clusters, which are optimal with respect to the applied distance function.

	KHOPCA's clustering process explicitly supports joining and leaving of nodes, which makes KHOPCA suitable for highly dynamic networks. However, it has been demonstrated that KHOPCA also performs in static networks.<ref name=":0" />		KHOPCA's clustering process explicitly supports joining and leaving of nodes, which makes KHOPCA suitable for highly dynamic networks. However, it has been demonstrated that KHOPCA also performs in static networks.<ref name=":0" />

Rathfelder: removed Category:Clustering algorithms using HotCat

2016-10-09T20:02:24Z

removed Category:Clustering algorithms using HotCat

← Previous revision		Revision as of 20:02, 9 October 2016
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	{{DEFAULTSORT:KHOPCA clustering algorithm}}		{{DEFAULTSORT:KHOPCA clustering algorithm}}
	[[Category:Clustering algorithms]]
	[[Category:Algorithms]]		[[Category:Algorithms]]