GloMoSim: a library for parallel simulation of large-scale wireless networks
PADS '98 Proceedings of the twelfth workshop on Parallel and distributed simulation
Scenario-based performance analysis of routing protocols for mobile ad-hoc networks
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Fuzzy Modeling for Control
GPS-Free Positioning in Mobile ad-hoc Networks
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 9 - Volume 9
Ad-hoc On-Demand Distance Vector Routing
WMCSA '99 Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications
Access and mobility of wireless PDA users
ACM SIGMOBILE Mobile Computing and Communications Review
A Mobility Prediction Architecture Based on Contextual Knowledge and Spatial Conceptual Maps
IEEE Transactions on Mobile Computing
A Reliable Routing Algorithm Based on Fuzzy Applicability of F sets in MANET
PRDC '05 Proceedings of the 11th Pacific Rim International Symposium on Dependable Computing
QoS provisioning in cellular networks based on mobility prediction techniques
IEEE Communications Magazine
Mobility modeling, location tracking, and trajectory prediction in wireless ATM networks
IEEE Journal on Selected Areas in Communications
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Mobile ad hoc networks (MANETs) are recognised as one of the key infrastructures in ambient intelligence (AmI) due to their promising ubiquitous connectivity. Key factors for reliable performance of service protocols in MANETs are the manner in which they adapt to route changes caused by mobility and communicating traffic patterns. Our main idea to support AmI ubiquitous communications is to use fuzzy C-mean clustering as data mining technique to extract knowledge and dependencies from high-level information of the application scenario. We use the resulting knowledge to predict the upcoming context and make MANETs services context-aware. Thus, a mobile node builds dynamic models determined by IF-THEN rules for its various environments and adapts its service protocols. We propose a methodology for storing and processing MANETs context, online fuzzy reasoning about it and improving the performance of underlying service protocols based on simple distributed, unobtrusive and handling different scenarios intelligent algorithm.