Neural Network Based Optimized Buffer Allocation In Future Networks

4G LTE networks have made it extremely easy for different wireless networks to be connected with internet in a seamless way. The future network 5G is mainly popular for data speed by providing fast and quality services. Further it can improve the network efficiency and QoS parameters by implementing optimized buffer allocation to requested node in the network. Implementation of optimized buffer allocation is done based on embedded neural network. The outcome of neural network is produced based on input applied to it. Once the source node expect the neighbor nodes to share buffer based on availability of resource at router. The neural network computes the optimized buffer allocation based on network parameters like buffer availability and distance among the registered nodes in the network. Our proposed work is aimed to provide better solution to resource allocation. The results shows that the significant improvement in the data failure rate and network overall performance.