Pratit Santiprabhob

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The future generation wireless networks will demand more intelligent and adaptive handover decision mechanisms to fulfill users' expectations in terms of seamless mobility over extensive area, minimum usage cost, high data rate and adequate QoS provision and so on. The use of fuzzy logic is one of the methods to enhance system intelligence. Most fuzzy logic(More)
Future generation wireless networks will demand more intelligent and adaptive handover decision mechanisms to fulfil users' expectations in terms of seamless mobility over extensive area, min imu m price, high data rate, adequate QoS provision and so on. For such a demanding networking environment the handover decision system (HDS) need to be highly(More)
Intelligent decision engine is necessary to support seamless handover and multimedia services in heterogeneous wireless mobile networks. In this paper, a matched monolithic fuzzy decision engine (FDE), which is tailored to match the QoS and data rate requirements of video streaming traffic, is presented. The proposed decision engine helps to improve the(More)
|Many diierent \and"-and \or"-operations have been proposed for use in fuzzy logic; ; see, e.g., 4], 13]. It is therefore important to select, for each particular application, the operations which are the best for this particular application. Several papers discuss the optimal choice of \and"-and \or"-operations for fuzzy control, when the main criterion is(More)
An intelligent handover decision system (HDS) is essential to heterogeneous wireless mobile networks in order to fulfill user's expectations in terms of universal and seamless services. With emerging real-time services in heterogeneous networking environment, including multiple QoS parameters in handover decision process seems essential. In this paper,(More)
Numerous fuzzy-based algorithms have been suggested to enhance the intelligence of handover decision system for wireless mobile networks. However, most existing algorithms are based on a monolithic fuzzy engine design resulting in a large algorithm execution time, if a number of decision parameters is large and gives a poorer network selection performance,(More)