En.605.704 【DIRECT ◉】

EN.605.704: A Comprehensive Guide to Johns Hopkins’ Real-World Data & Medical Device Regulatory Science

Overruns on Aperiodic Servers

Problem: Your sporadic server fails to replenish budget correctly.
Solution: Re-read the sporadic server algorithm in Buttazzo’s textbook—it is subtle.

Example Lab Structure:

Lab 1: Implementing a periodic task set using POSIX timers (clock_nanosleep). Measuring scheduler jitter.
Lab 2: Simulating priority inversion and fixing it with pthread_mutexattr_setprotocol.
Lab 3: Building a watchdog system that monitors task deadlines and escalates missed deadlines.
Final Project: Students choose a domain (e.g., drone flight controller, patient vital-sign monitor) and implement a fully schedulable system with documentation.

Assessment: Grading is based on code correctness (35%), schedulability analysis report (35%), and a live demo (30%). en.605.704

4. Real-Time Operating Systems (RTOS)

Comparing RTOS kernels (FreeRTOS, VxWorks, QNX, RT-Linux).
Interrupt handling: First-level vs. Second-level interrupt handlers.
Memory management: Memory pools, avoiding dynamic allocation in critical sections.

1. Fundamentals of Real-Time Computing

Definitions: Hard vs. Soft real-time systems.
Terminology: Release time, deadline, period, execution time, jitter.
Workload models: Periodic, sporadic, aperiodic tasks.

Prerequisites and Target Audience

EN.605.704 is a graduate-level course (typically 3 credits). Given its technical nature, Johns Hopkins recommends the following prerequisites: Lab 1: Implementing a periodic task set using

EN.605.601 (Probability and Statistics) or equivalent graduate-level statistics.
Familiarity with a statistical programming language (R, SAS, or Python with statsmodels) is highly encouraged, though the course is not a pure programming bootcamp.
A basic understanding of the US medical device regulatory environment.

Ideal students include:

Regulatory affairs professionals transitioning from pharmaceuticals to devices.
Biomedical engineers working on Class II or Class III devices.
Clinical research coordinators managing post-market registries.
Data scientists entering the health technology sector.