Real-Time Linux Latency Engineering: A Practical Guide to Deterministic Linux Performance (Embedded Systems Engineering Library) - Softcover

Inhaltsangabe

Real-Time Linux Latency Engineering

Have you ever watched a control loop miss its deadline by a fraction of a millisecond—and had no idea why?

If you've tuned a Linux system and still couldn't explain its worst-case latency, Real-Time Linux Latency Engineering was written for exactly that moment.

This hands-on technical guide is for engineers who need Linux to behave predictably, cycle after cycle—not just most of the time. It takes you through the full stack that determines real-time performance, from kernel preemption and CPU isolation to interrupt handling, memory locking, scheduling, tracing, and rigorous latency measurement.

Inside, you'll learn how to:

• Configure a fully preemptible kernel and understand the changes that enable more deterministic execution
• Isolate CPU cores and strategically route interrupts so critical threads can operate with minimal interference
• Lock and pre-touch memory to prevent page faults from introducing unexpected latency spikes
• Trace and diagnose latency problems using tools such as ftrace and bpftrace instead of relying on assumptions
• Build reproducible embedded Linux images using a disciplined and repeatable kernel configuration workflow
• Validate real-time behavior with measurement methodologies suitable for demanding industrial, financial, robotics, and embedded applications

Three detailed case studies bring the concepts to life: an industrial motion controller, a low-latency trading application, and a mobile robotics platform. Each one demonstrates how to investigate a latency problem, identify its root cause, implement a targeted solution, and verify the improvement with measurable results.

Who is this book for?

This book is designed for systems engineers, embedded Linux developers, controls engineers, robotics developers, and other technical professionals who need predictable system behavior. If you've ever asked, "Why did that one cycle take three times longer than every other cycle?", you'll find practical answers here—supported by working examples, diagnostic workflows, and measurable engineering techniques.

Stop guessing about your system's worst-case behavior. Start measuring it, understanding it, and engineering it for predictability.

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