Back to Week 5 CPU Scheduling
Lecture 6 Introduction to CPU Scheduling
Lecture 8 Introduction to Concurrency
Lecture 7 on "Multi-Level Feedback Queue (MLFQ)" explores a sophisticated approach to CPU scheduling, designed to optimize both turnaround time and responsiveness without prior knowledge of job lengths. Introduced by Corbato et al. in 1962, MLFQ has been a cornerstone in the evolution of scheduling algorithms, earning the Turing Award for its contribution. MLFQ addresses the challenge of scheduling in a dynamic environment where job behaviors and requirements vary significantly. It operates on a system of multiple queues, each with a different priority level, employing a set of rules that adjust a job's priority based on its observed behavior. This adaptive mechanism allows MLFQ to prioritize short-running and interactive jobs for responsiveness, while also ensuring fairness and progress for longer, CPU-intensive tasks. Through its feedback system, MLFQ learns from job execution patterns, striving for an optimal balance between responsiveness and efficiency. The approach has been refined over the years, demonstrating its flexibility and effectiveness in modern operating systems by adjusting to the ever-changing nature of computing workloads.
This is a short video which briefly summarizes what we cover in this lecture. It may help you solidify your understanding of MLFQ by listening to a different person. Give it a go!
https://youtu.be/O3q3Su47q5g?si=eE6htQwts6tnYw4m
https://docs.google.com/presentation/d/1HHYqEH9Sb5-6EzYXQqEhWO0eJkPsPuYPA8zv_BbRKA4/edit?usp=sharing
No example code for this lecture.
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