Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
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Qos routing protocol design for mobile ad-hoc networks is more challenging than wire lane network. Mainly due to node mobility, multi hop communications, contention for channel access and lack of central ordination.QoS guarantees are required by the most of the applications. Most optimal route has to be selected from source to destination by using QoS routing protocol. Many routing protocols are designed for single QoS metric. If it requires to design routing protocol for multi constrained routing path, normal algorithms can be failed. In this paper we proposed genetic algorithm based route selection protocol to solve the multi constrained QoS route. Genetic algorithm finds the optimal route with population initialization, cross over, mutation and fitness function calculation. QoS constraints consists of end to end delay, band width, packet loss rate, node connectivity index (Ni) and dynamic resource availability. Simulations have been performed in ns-2. Performance of genetic algorithm is compared with AOMDV and results shows that genetic algorithm is giving efficient results for different metrics (delay, throughput and Delivery ratio).
M.L.Ravi Chandra. 2014. \u201cQoS Routing solution based on Genetic Algorithm for MANETs\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 14 (GJCST Volume 14 Issue E4): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Neural Networks and Rules-based Systems used to Find Rational and
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Qos routing protocol design for mobile ad-hoc networks is more challenging than wire lane network. Mainly due to node mobility, multi hop communications, contention for channel access and lack of central ordination.QoS guarantees are required by the most of the applications. Most optimal route has to be selected from source to destination by using QoS routing protocol. Many routing protocols are designed for single QoS metric. If it requires to design routing protocol for multi constrained routing path, normal algorithms can be failed. In this paper we proposed genetic algorithm based route selection protocol to solve the multi constrained QoS route. Genetic algorithm finds the optimal route with population initialization, cross over, mutation and fitness function calculation. QoS constraints consists of end to end delay, band width, packet loss rate, node connectivity index (Ni) and dynamic resource availability. Simulations have been performed in ns-2. Performance of genetic algorithm is compared with AOMDV and results shows that genetic algorithm is giving efficient results for different metrics (delay, throughput and Delivery ratio).
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