Embedded System | Module 7: Week 7 - Real-Time Scheduling Algorithms by Prakhar Chauhan | Learn Smarter
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Module 7: Week 7 - Real-Time Scheduling Algorithms

The module on real-time scheduling algorithms covers fundamental principles and taxonomies crucial for ensuring timely and predictable behavior in embedded systems. It establishes concepts of real-time systems, differentiating between hard, firm, and soft timelines, and delves into various scheduling paradigms including fixed and dynamic priorities. The challenges of resource sharing, especially priority inversion, and techniques for integrating aperiodic tasks while maintaining schedulability are also addressed, culminating in a discussion on multiprocessor real-time scheduling complexities.

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Sections

  • 7

    Week 7 - Real-Time Scheduling Algorithms

    This section explores real-time scheduling algorithms, covering definitions, task models, scheduling paradigms, and key algorithms for embedded systems.

    Learning Practice

  • 7.1

    Fundamentals Of Real-Time Systems And Scheduling

    This section defines real-time systems, explores their types, and introduces key concepts and goals of real-time scheduling.

    Learning Practice

  • 7.1.1

    Defining Real-Time Systems And Their Types

    This section defines real-time systems and classifies them into hard, firm, and soft categories based on deadline criticality.

    Learning Practice

  • 7.1.2

    Core Concepts In Real-Time Scheduling

    This section introduces essential terminology and key concepts in real-time scheduling, highlighting the importance of task properties in embedded systems.

    Learning Practice

  • 7.1.3

    Goals Of Real-Time Scheduling

    The goals of real-time scheduling focus on ensuring that all tasks meet their deadlines while utilizing system resources efficiently and predictably.

    Learning Practice

  • 7.2

    Real-Time Task Models

    This section explains the different real-time task models—periodic, aperiodic, and sporadic—which are crucial for understanding scheduling in embedded systems.

    Learning Practice

  • 7.2.1

    Periodic Tasks

    Periodic tasks are regularly scheduled tasks in real-time systems with defined execution times and deadlines, making them crucial for ensuring timely operations.

    Learning Practice

  • 7.2.2

    Aperiodic Tasks

    Aperiodic tasks are unpredictable and irregularly released tasks in real-time systems, lacking fixed periods and often exhibiting soft or firm deadlines.

    Learning Practice

  • 7.2.3

    Sporadic Tasks

    Sporadic tasks are a type of aperiodic task characterized by a minimum inter-arrival time and a deadline, allowing them to be integrated into hard real-time systems.

    Learning Practice

  • 7.3

    Real-Time Scheduling Paradigms

    Real-time scheduling paradigms categorize algorithms based on key characteristics, including their timing, control mechanisms, and execution behavior.

    Learning Practice

  • 7.3.1

    Static (Offline) Vs. Dynamic (Online) Scheduling

    This section contrasts static scheduling, where task schedules are pre-computed, with dynamic scheduling, where decisions are made in real-time based on system state.

    Learning Practice

  • 7.3.2

    Clock-Driven Vs. Event-Driven Scheduling

    This section distinguishes between clock-driven and event-driven scheduling paradigms in real-time systems, highlighting their characteristics, advantages, and use cases.

    Learning Practice

  • 7.3.3

    Preemptive Vs. Non-Preemptive Scheduling

    This section explains the two main types of scheduling in real-time systems: preemptive and non-preemptive scheduling, detailing their concepts, advantages, and disadvantages.

    Learning Practice

  • 7.4

    Fixed-Priority Preemptive Scheduling Algorithms

    This section covers fixed-priority preemptive scheduling algorithms, focusing on Rate Monotonic Scheduling and its characteristics, including schedulability analysis and challenges.

    Learning Practice

  • 7.4.1

    Rate Monotonic (Rm) Scheduling

    Rate Monotonic Scheduling is a widely accepted fixed-priority algorithm where tasks are prioritized based on their periods, with shorter periods receiving higher priority.

    Learning Practice

  • 7.4.1.1

    Schedulability Analysis For Rate Monotonic

    This section discusses the methods used to determine if a set of tasks is schedulable under the Rate Monotonic (RM) scheduling algorithm.

    Learning Practice

  • 7.4.1.2

    Challenges And Limitations Of Rate Monotonic

    This section discusses the key challenges and limitations associated with the Rate Monotonic scheduling algorithm in real-time systems.

    Learning Practice

  • 7.5

    Dynamic-Priority Preemptive Scheduling Algorithms

    This section introduces dynamic-priority preemptive scheduling algorithms, emphasizing Earliest Deadline First (EDF) and Least Laxity First (LLF) algorithms, along with their principles, benefits, and challenges.

    Learning Practice

  • 7.5.1

    Earliest Deadline First (Edf) Scheduling

    The Earliest Deadline First (EDF) scheduling algorithm dynamically selects tasks based on their deadlines to optimize real-time task execution.

    Learning Practice

  • 7.5.1.1

    Schedulability Analysis For Edf

    This section covers the schedulability analysis for the Earliest Deadline First (EDF) scheduling algorithm, highlighting its principles and limitations.

    Learning Practice

  • 7.5.1.2

    Challenges And Limitations Of Edf

    This section discusses the challenges and limitations associated with the Earliest Deadline First (EDF) scheduling algorithm used in real-time systems.

    Learning Practice

  • 7.5.2

    Least Laxity First (Llf) Scheduling

    Least Laxity First (LLF) Scheduling is a dynamic priority scheduling algorithm where tasks with the smallest laxity are prioritized for execution, ensuring effective utilization of CPU resources.

    Learning Practice

  • 7.6

    Handling Aperiodic And Sporadic Tasks In Real-Time Systems

    This section focuses on methods for incorporating aperiodic and sporadic tasks into real-time systems without compromising the timely execution of critical periodic tasks.

    Learning Practice

  • 7.6.1

    Background Scheduling

    Background scheduling allows aperiodic tasks to run when the processor is idle, but lacks guaranteed response times.

    Learning Practice

  • 7.6.2

    Server-Based Approaches

    Server-based approaches improve the handling of aperiodic and sporadic tasks in real-time systems.

    Learning Practice

  • 7.6.2.1

    Polling Server

    A polling server is a scheduling mechanism used in real-time systems to manage aperiodic tasks efficiently by polling for tasks at regular intervals within its defined period and budget.

    Learning Practice

  • 7.6.2.2

    Deferrable Server

    The Deferrable Server is a type of server-based approach used in real-time systems to allow for efficient handling of aperiodic tasks without significantly affecting the schedulability of periodic tasks.

    Learning Practice

  • 7.6.2.3

    Sporadic Server

    A sporadic server is a more sophisticated approach for integrating sporadic tasks within real-time systems, allowing them to meet deadlines while maintaining the schedulability of periodic tasks.

    Learning Practice

  • 7.7

    Resource Sharing And Priority Inversion

    This section discusses the critical issue of priority inversion in real-time systems and explores various solutions to mitigate its effects.

    Learning Practice

  • 7.7.1

    What Is Priority Inversion?

    Priority inversion occurs when a higher-priority task is blocked by a lower-priority task, leading to potential deadline misses.

    Learning Practice

  • 7.7.2

    Solutions To Priority Inversion

    This section discusses several methods to mitigate the issue of priority inversion in real-time scheduling systems.

    Learning Practice

  • 7.7.2.1

    Priority Inheritance Protocol (Pip)

    The Priority Inheritance Protocol (PIP) addresses priority inversion by temporarily elevating the priority of a lower-priority task holding a shared resource needed by a higher-priority task.

    Learning Practice

  • 7.7.2.2

    Priority Ceiling Protocol (Pcp)

    The Priority Ceiling Protocol (PCP) is a synchronization mechanism designed to prevent priority inversion in real-time scheduling by assigning a ceiling priority to shared resources.

    Learning Practice

  • 7.7.3

    Other Considerations For Resource Sharing

    This section addresses critical sections in real-time systems and emphasizes the importance of minimizing critical section lengths to improve resource sharing efficiency.

    Learning Practice

  • 7.8

    Introduction To Multiprocessor Real-Time Scheduling

    This section introduces the complexities of scheduling in multiprocessor real-time systems, highlighting the challenges and common approaches to effective task management.

    Learning Practice

  • 7.8.1

    Challenges In Multiprocessor Scheduling

    Multiprocessor scheduling presents unique challenges including load balancing, inter-core communication, cache coherency, and NP-hard problem complexity.

    Learning Practice

  • 7.8.2

    Common Approaches (Brief Overview)

    This section provides an overview of two key approaches to multiprocessor real-time scheduling: Partitioned Scheduling and Global Scheduling.

    Learning Practice

  • 7.8.2.1

    Partitioned Scheduling

    Partitioned scheduling assigns tasks to specific processors statically and uses a single-processor scheduling algorithm on each processor.

    Learning Practice

  • 7.8.2.2

    Global Scheduling

    Global scheduling manages tasks across multiple processors to achieve better resource utilization and load balancing, but comes with complexity and overhead challenges.

    Learning Practice

References

Untitled document (19).pdf

Class Notes

Memorization

What we have learnt

  • Real-time systems must fulf...
  • Different task models (peri...
  • Fixed-priority and dynamic-...

Final Test

Revision Tests