A novel approach of Load Balancing in Content Delivery Networks by optimizing the surrogate server
Pulkit Varshney, Sanchit Gaur, Satya Pal · 2021
The new load balancing methods plan to disseminate the load to the proxy servers ideally and amplify usage of the network, avoiding traffic and delay along the way. In this paper, we are proposing a novel approach for optimizing the router request time to minimize the delay, which exploits the adaptability and programmability of Software-Defined Networking. It is done by creating CDNs and balancing load using surrogate networks. It will lower the load on the original server. The load balancing is done using shortest path selection through the utilization of neural networks as a machine learning technique to choose the node with the highest energy level and determine the fastest route for data transfer. This enhancement work in this paper is done for specific types of networks like wireless networks during the session layer transmission. In the selection process of the node for data transfer, we could use a neural network instead of a decision tree. The paper concludes with the evaluation of achieved results and the comparison against the of performance metrics of other pre-existing approaches.