With recent advances in the field of Machine Learning (ML), a multitude problems related to communication systems and networks can be solved with data-driven solutions. Since data these is mostly represented as graphs, Graph-based Neural Networks (GNNs) are good candidate for solving such problems. These GNNs used computer network modeling technique build models that accurately estimate Key Per...

This paper examines the scalability of the Linux 2.4.x scheduler as the load and number of CPUs increases. We show that the current scheduler design involving a single runqueue and lock can suffer from lock contention problems which limits its scalability. We present alternate designs using multiple runqueues and priority levels that can reduce lock contention while maintaining the same functio...