Optimizing Energy Consumption in Cloud Computing: A Machine Learning-Based Intelligent Load Balancer

A machine learning-based intelligent load balancer that optimises energy consumption in cloud computing.

A machine learning-based intelligent load balancer that optimises energy consumption in cloud computing. This reference project walks through the whole job, from the problem and the design to the build and the evaluation, so that a developer can study how it works, run it and extend it.

It suits learners who want to understand networks and cloud systems: building or simulating the environment, measuring performance and comparing approaches.

The main parts are a simulated or deployed environment, the algorithm or mechanism being studied, performance measurement against baselines, and charts that compare the results. The reference build uses Docker, Python, Linux, and Prometheus, with a clear project structure, setup instructions and sample data so that it can be run and extended.