Ad-hoc On-Demand Distance Vector Routing
WMCSA '99 Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications
Ant Routing with Distributed Geographical Localization of Knowledge in Ad-Hoc Networks
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Scalable routing strategies for ad hoc wireless networks
IEEE Journal on Selected Areas in Communications
Scalable routing protocols for mobile ad hoc networks
IEEE Network: The Magazine of Global Internetworking
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We formalize and analyze a generalized model of connections in ad-hoc networks. The proposed model defines connections on the locations level rather than on the nodes level. We show how the generalized model improves the stability of connections if the ant learning mechanism is applied to solve the routing problem. Stable connections reduce the overhead generated by ant routing mechanism and improve its performance in terms of end-to-end delay and delivery ratio. Moreover, connections on the locations level reflect physical connections in ad-hoc networks very well and agree with biological inspirations of ant algorithms.