Abstract
The multi-constrained quality of service (QoS) routing in MANET considers multiple QoS parameters to route the packet from source to destination. Taking decision on which criteria different QoS parameters have to be taken into consideration is a critical task in dynamic network scenarios like MANET. The network scenario and stack parameters are aligned with different layers like application, MAC, physical change hand in hand. The set of these stack parameters has a significant impact on different QoS parameters, and trade-off point between these stack parameters is identified to estimate the significance of stack parameters in QoS parameters of the MANET. The rough set theory is used to identify trade-off point to estimate the significance of the stack parameter on different QoS parameters and QoS parameters to be considered in routing. The rough set decision rules are filtered out based on probabilistic properties like strength, certainty, and coverage of the decision rules. The positive dependency between conditions and decisions of selected decision rules is confirmed with certainty and coverage of relationships. The Rough Set Exploration System (RSES) is used for extensive analysis of QoS in data delivery under seven different stack parameter configurations like packet inter-arrival time, payload, and retry delay. The different stages of RSES like data exploration, discretization, reduction, and decision rules are applied to QoS values of different routes. The empirical model of stack parameters is derived for multi-parameter optimization to get best-effort QoS in all routes of the MAENT. The decision rules are selected based on strength and certainty, and coverage of decision rules will be used in the routing algorithm to get best QoS in MANET routing.
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Pathviraj, N., Deshpande, S.L. (2019). Rough Set-Based Analysis of Multilayer Stack Parameter on QoS of MANET. In: Chaki, N., Devarakonda, N., Sarkar, A., Debnath, N. (eds) Proceedings of International Conference on Computational Intelligence and Data Engineering. Lecture Notes on Data Engineering and Communications Technologies, vol 28. Springer, Singapore. https://doi.org/10.1007/978-981-13-6459-4_22
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DOI: https://doi.org/10.1007/978-981-13-6459-4_22
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