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
