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Evolving intuitionistic fuzzy priority classifier with bio-inspiration based scheduling scheme for WiMAX in vehicular ad-hoc networks

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Abstract

With the increase in user mobility the most challenging issues are data scheduling which premises its users high quality of service in the context of the interoperability for microwave access in WiMAX for vehicular ad-hoc network (VANET). There is no complete proof of existing techniques accessible to provide better quality as there is a starvation problem due to the uncertainty in decision process with imprecise data. In VANET for the sake of interest while vehicles started increasing more and more in network traffic this paper devised a two stage Optimized priority scheduling scheme known as Evolving Intuitionistic Fuzzy Priority Classifier with Bio-inspiration Based Scheduling Scheme. This work takes into account the hesitation degree of each factor for priority and the bio-inspiration based classification. Through our simulation, it is shown that the projected proposal can work to acclimatize and make competent to improve the existing VANET approaches in terms of high spectrum effectiveness and low outage probability.

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Kumuthini, C., Krishnakumari, P. Evolving intuitionistic fuzzy priority classifier with bio-inspiration based scheduling scheme for WiMAX in vehicular ad-hoc networks. Wireless Netw 22, 403–415 (2016). https://doi.org/10.1007/s11276-015-0978-0

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  • DOI: https://doi.org/10.1007/s11276-015-0978-0

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