[[File:KHOPCA 3D example 1.png|thumb|KHOPCA in a 3-D environment.]]
'''KHOPCA''' is a [[clustering algorithm]] designed for dynamic networks. KHOPCA provides a fully [[Distributed computing|distributed]] and localized approach to group elements such as nodes in a network according to their distance tofrom 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 (<math display="inline">k</math>-hop clustering algorithm) 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 performsalso equallyperforms in static networks.<ref name=":0" />
Besides applications in ad hoc and [[wireless sensor network]]s, KHOPCA can be used in localization and navigation problems, networked [[Swarm intelligence|swarming]], and real-time data clustering.
