Advanced Techniques for Efficient Scheduling
( 30 Modules )

Module #1
Introduction to Advanced Scheduling Techniques
Overview of the importance of efficient scheduling, course objectives, and outline of advanced techniques to be covered

Module #2
Scheduling Fundamentals Review
Review of basic scheduling concepts, including process scheduling, thread scheduling, and synchronization

Module #3
Rate Monotonic Scheduling (RMS)
Introduction to RMS, including scheduling algorithm, priority assignment, and deadline monotonic scheduling

Module #4
Earliest Deadline First (EDF) Scheduling
Introduction to EDF, including scheduling algorithm, deadline-based scheduling, and application scenarios

Module #5
Least Laxity First (LLF) Scheduling
Introduction to LLF, including scheduling algorithm, laxity calculation, and examples

Module #6
Proportional Share Scheduling
Introduction to proportional share scheduling, including Generalized Processor Sharing (GPS) and Stride Scheduling

Module #7
Multi-Level Feedback Queue (MLFQ) Scheduling
Introduction to MLFQ, including scheduling algorithm, queue management, and performance evaluation

Module #8
Feedback-Based Scheduling
Introduction to feedback-based scheduling, including adaptive scheduling, feedback control, and autonomous systems

Module #9
Real-Time Scheduling for Multi-Core Systems
Overview of real-time scheduling techniques for multi-core systems, including partitioned scheduling and global scheduling

Module #10
Scheduling for Heterogeneous Systems
Introduction to scheduling for heterogeneous systems, including asymmetric multi-processing and heterogeneous multi-core systems

Module #11
Energy-Aware Scheduling
Introduction to energy-aware scheduling, including dynamic voltage and frequency scaling, and power management

Module #12
Thermal-Aware Scheduling
Introduction to thermal-aware scheduling, including thermal management, temperature-aware scheduling, and thermal modeling

Module #13
Scheduling for Distributed Systems
Overview of scheduling techniques for distributed systems, including distributed real-time systems and cloud computing

Module #14
Scheduling for Cyber-Physical Systems
Introduction to scheduling for cyber-physical systems, including CPS architecture, timing analysis, and control systems

Module #15
Advanced Scheduling for Machine Learning Workloads
Introduction to scheduling for machine learning workloads, including GPU scheduling, deep learning, and AI applications

Module #16
Scheduling for Edge Computing
Introduction to scheduling for edge computing, including edge computing architecture, real-time edge computing, and edge AI

Module #17
Scheduling for Robotics and Autonomous Systems
Introduction to scheduling for robotics and autonomous systems, including ROS, autonomous vehicles, and robotic operating systems

Module #18
Case Studies in Advanced Scheduling
Real-world case studies of advanced scheduling techniques, including industrial automation, healthcare, and finance

Module #19
Scheduling for 5G and 6G Networks
Introduction to scheduling for 5G and 6G networks, including network slicing, URLLC, and mMTC

Module #20
Scheduling for Database Systems
Introduction to scheduling for database systems, including database management, query optimization, and data warehousing

Module #21
Scheduling for Real-Time Data Analytics
Introduction to scheduling for real-time data analytics, including streaming analytics, IoT analytics, and edge analytics

Module #22
Advanced Scheduling for Embedded Systems
Introduction to advanced scheduling techniques for embedded systems, including SoC, NoC, and embedded Linux

Module #23
Scheduling for HPC and Exascale Computing
Introduction to scheduling for HPC and exascale computing, including HPC architecture, job scheduling, and resource management

Module #24
Scheduling for Scientific Computing
Introduction to scheduling for scientific computing, including scientific workflows, task scheduling, and resource allocation

Module #25
Advanced Scheduling for Cloud Computing
Introduction to advanced scheduling techniques for cloud computing, including cloud architecture, resource allocation, and cloud bursting

Module #26
Scheduling for Fog Computing
Introduction to scheduling for fog computing, including fog architecture, edge-fog-cloud continuum, and fog-enabled IoT

Module #27
Scheduling for Artificial Intelligence and Machine Learning
Introduction to scheduling for AI and ML, including AI-driven scheduling, ML-based scheduling, and AI-MKL convergence

Module #28
Scheduling for Cybersecurity
Introduction to scheduling for cybersecurity, including threat detection, intrusion detection, and cybersecurity analytics

Module #29
Advanced Scheduling for 5G and Beyond Networks
Introduction to advanced scheduling techniques for 5G and beyond networks, including network slicing, URLLC, and mMTC

Module #30
Course Wrap-Up & Conclusion
Planning next steps in Advanced Techniques for Efficient Scheduling career

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Advanced Techniques for Efficient Scheduling ( 30 Modules )

Advanced Techniques for Efficient Scheduling
( 30 Modules )