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Jitter Propagation in Task Chains

Wang, Shumo ; Bini, Enrico ; Deng, Qingxu and Maggio, Martina LU (2025)
Abstract
Chains of tasks are ubiquitous and used in a broad spectrum of applications. In these chains, tasks execute according to their timing. Then, they communicate by writing to and reading from shared memory. The schedule of tasks and the read/write instants are naturally subject to uncertainties (variability in the execution time, interference due to shared resources of higher priority tasks, etc.). Despite the impact of uncertainties, we believe that current analysis of task chains cannot handle them properly. In this paper, we borrow the notion of jitter to model uncertainties and we propose a novel event model that explicitly captures jitter in read and write operations, decoupled from task scheduling. We develop a (linear-time complexity)... (More)
Chains of tasks are ubiquitous and used in a broad spectrum of applications. In these chains, tasks execute according to their timing. Then, they communicate by writing to and reading from shared memory. The schedule of tasks and the read/write instants are naturally subject to uncertainties (variability in the execution time, interference due to shared resources of higher priority tasks, etc.). Despite the impact of uncertainties, we believe that current analysis of task chains cannot handle them properly. In this paper, we borrow the notion of jitter to model uncertainties and we propose a novel event model that explicitly captures jitter in read and write operations, decoupled from task scheduling. We develop a (linear-time complexity) compositional analysis framework that tracks how this jitter propagates across chains and impacts metrics such as reaction time, data age, and end-to-end latency. Our model supports arbitrary communication paradigms (e.g., implicit, LET, mid-execution) and is applicable to the analysis of real-world frameworks such as ROS2 without requiring intrusive changes. (Less)
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author
; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
2025 IEEE Real-Time Systems Symposium (RTSS)
project
Trustworthy Cyber-Physical Pipelines
Intelligent Cloud Robotics for Real-Time Manipulation at Scale
language
English
LU publication?
yes
id
78518a8c-37ff-4254-83ce-e3c7bcb7cbba
date added to LUP
2025-12-02 17:58:26
date last changed
2025-12-10 14:35:35
@inproceedings{78518a8c-37ff-4254-83ce-e3c7bcb7cbba,
  abstract     = {{Chains of tasks are ubiquitous and used in a broad spectrum of applications. In these chains, tasks execute according to their timing. Then, they communicate by writing to and reading from shared memory. The schedule of tasks and the read/write instants are naturally subject to uncertainties (variability in the execution time, interference due to shared resources of higher priority tasks, etc.). Despite the impact of uncertainties, we believe that current analysis of task chains cannot handle them properly. In this paper, we borrow the notion of jitter to model uncertainties and we propose a novel event model that explicitly captures jitter in read and write operations, decoupled from task scheduling. We develop a (linear-time complexity) compositional analysis framework that tracks how this jitter propagates across chains and impacts metrics such as reaction time, data age, and end-to-end latency. Our model supports arbitrary communication paradigms (e.g., implicit, LET, mid-execution) and is applicable to the analysis of real-world frameworks such as ROS2 without requiring intrusive changes.}},
  author       = {{Wang, Shumo and Bini, Enrico and Deng, Qingxu and Maggio, Martina}},
  booktitle    = {{2025 IEEE Real-Time Systems Symposium (RTSS)}},
  language     = {{eng}},
  title        = {{Jitter Propagation in Task Chains}},
  url          = {{https://lup.lub.lu.se/search/files/235446236/964200a096.pdf}},
  year         = {{2025}},
}