research-article

A Structured Methodology for Pattern based Adaptive Scheduling in Embedded Control

Authors:

Souradeep Dutta,

Pallab DasguptaAuthors Info & Claims

ACM Transactions on Embedded Computing Systems (TECS), Volume 16, Issue 5s

Article No.: 189, Pages 1 - 22

https://doi.org/10.1145/3126514

Published: 27 September 2017 Publication History

Abstract

Software implementation of multiple embedded control loops often share compute resources. The control performance of such implementations have been shown to improve if the sharing of bandwidth between control loops can be dynamically regulated in response to input disturbances. In the absence of a structured methodology for planning such measures, the scheduler may spend too much time in deciding the optimal scheduling pattern. Our work leverages well known results in the domain of network control systems and applies them in the context of bandwidth sharing among controllers. We provide techniques that may be used a priori for computing co-schedulable execution patterns for a given set of control loops such that stability is guaranteed under all possible disturbance scenarios. Additionally, the design of the control loops optimize the average case control performance by adaptive sharing of bandwidth under time varying input disturbances.

References

[1]

Rajeev Alur and Gera Weiss. 2008. Regular specifications of resource requirements for embedded control software. In Proc. RTAS. 159--168.

Digital Library

[2]

Sanjoy Baruah and Joël Goossens. 2004. Scheduling real-time tasks: Algorithms and complexity. Handbook of Scheduling: Algorithms, Models, and Performance Analysis 3 (2004).

[3]

Michael S. Branicky, Stephen M. Phillips, and Wei Zhang. 2002. Scheduling and feedback co-design for networked control systems. In Proc. CDC, Vol. 2. 1211--1217.

[4]

Rosa Castané et al. 2006. Resource management for control tasks based on the transient dynamics of closed-loop systems. In Proc. ECRTS. 10--pp.

Digital Library

[5]

Anton Cervin, Johan Eker, Bo Bernhardsson, and Karl-Erik Årzén. 2002. Feedback feedforward scheduling of control tasks. Real-Time Systems 23, 1--2 (2002), 25--53.

Digital Library

[6]

Anton Cervin, Manel Velasco, et al. 2009. Optimal on-line sampling period assignment. Dept. Autom. Control, Tech. Univ. Catalonia, Barcelona, Spain, Tech. Rep. ESAII-RR-09-04 (2009).

[7]

Anton Cervin, Manel Velasco, Pau Martí, and Antonio Camacho. 2011. Optimal online sampling period assignment: theory and experiments. IEEE Trans. on Control Systems Technology 19, 4 (2011), 902--910.

[8]

Christian Choffrut and Juhani Karhumäki. 1997. Combinatorics of words, Handbook of formal languages. (1997).

[9]

Daniele Fontanelli, Luca Greco, and Luigi Palopoli. 2013. Soft real-time scheduling for embedded control systems. Automatica 49, 8 (2013), 2330--2338.

Digital Library

[10]

Daniele Fontantelli, Luigi Palopoli, and Luca Greco. 2013. Optimal CPU allocation to a set of control tasks with soft real time execution constraints. In Proc. Hybrid Systems: Computation and Control. 233--242.

Digital Library

[11]

Simon Fürst and AUTOSAR Spokesperson. 2015. Autosar the next generation--the adaptive platform. CARS@ EDCC2015 (2015).

[12]

MEM Ben Gaid, Arben Cela, Yskandar Hamam, and Cosmin Ionete. 2006. Optimal scheduling of control tasks with state feedback resource allocation. In 2006 American Control Conference. 6--pp.

[13]

Vijay Gupta. 2010. On a control algorithm for time-varying processor availability. In Proc. HSCC. 81--90.

Digital Library

[14]

Arash Hassibi et al. 1999. Control of asynchronous dynamical systems with rate constraints on events. In Proc. CDC, Vol. 2. 1345--1351.

[15]

Dan Henriksson and Anton Cervin. 2005. Optimal on-line sampling period assignment for real-time control tasks based on plant state information. In Proc. CDC. 4469--4474.

[16]

Qiang Ling and Michael D. Lemmon. 2002. Robust performance of soft real-time networked control systems with data dropouts. In Proc. CDC, Vol. 2. 1225--1230.

[17]

Chung Laung Liu and James W. Layland. 1973. Scheduling algorithms for multiprogramming in a hard-real-time environment. J. ACM 20, 1 (1973), 46--61.

Digital Library

[18]

Patrizia Marti et al. 2009. Draco: Efficient resource management for resource-constrained control tasks. IEEE Trans. Comput. 58, 1 (2009), 90--105.

Digital Library

[19]

Johan Nilsson, Bo Bernhardsson, et al. 1996. Analysis of real-time control systems with time delays. In Proc. CDC, Vol. 3. 3173--3172.

[20]

Jia Ning, Song YeQiong, and Simonot-Lion Francoise. 2007. Graceful degradation of the quality of control through data drop policy. In Proc. ECC. 4324--4331.

[21]

Debayan Roy et al. 2016. Multi-objective co-optimization of FlexRay-based distributed control systems. In Proc. RTAS. 1--12.

[22]

Danbing Seto, John P. Lehoczky, Lui Sha, and Kang G. Shin. 1996. On task schedulability in real-time control systems. In Proc. RTSS. 13--21.

Digital Library

[23]

Damoon Soudbakhsh, Linh T.X. Phan, et al. 2013. Co-design of control and platform with dropped signals. In Proc. ICCPS. 129--140.

Digital Library

[24]

Gera Weiss and Rajeev Alur. 2007. Automata based interfaces for control and scheduling. In Proc. HSCC. 601--613.

Digital Library

[25]

Wei Zhang, Michael S. Branicky, and Stephen M. Phillips. 2001. Stability of networked control systems. IEEE Control Systems 21, 1 (2001), 84--99.

Cited By

Baruah SHosseinzadeh MKolmanovsky ISinopoli B(2024)Adaptive Scheduling for Real-Time ControlProceedings of the 32nd International Conference on Real-Time Networks and Systems10.1145/3696355.3696357(165-174)Online publication date: 6-Nov-2024
https://dl.acm.org/doi/10.1145/3696355.3696357
Adhikary SKoley IGhosh SGhosh SDey S(2024)Revisiting Dynamic Scheduling of Control Tasks: A Performance-Aware Fine-Grained ApproachIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2024.344300743:11(3662-3673)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TCAD.2024.3443007
Ghosh S(2023)Delay-Aware Control for Autonomous Systems2023 36th International Conference on VLSI Design and 2023 22nd International Conference on Embedded Systems (VLSID)10.1109/VLSID57277.2023.00018(1-6)Online publication date: Jan-2023
https://doi.org/10.1109/VLSID57277.2023.00018
Show More Cited By

Index Terms

A Structured Methodology for Pattern based Adaptive Scheduling in Embedded Control
1. Computer systems organization
  1. Dependable and fault-tolerant systems and networks
    1. Redundancy
  2. Embedded and cyber-physical systems
    1. Embedded systems
    2. Robotics
2. Networks
  1. Network properties
    1. Network reliability

Recommendations

Pattern Guided Integrated Scheduling and Routing in Multi-Hop Control Networks

Executing a set of control loops over a shared multi-hop (wireless) control network (MCN) requires careful co-scheduling of the control tasks and the routing of sensory/actuation messages over the MCN. In this work, we establish pattern guided aperiodic ...
Advanced Embedded Control of Electrohydraulic Power Steering System
Abstract
The article presents a developed embedded system for control of electrohydraulic power steering based on multivariable uncertain plant model and advanced control techniques. The plant model is obtained by identification procedure via “black box” ...
Scheduling of Embedded Controllers Under Timing Contracts
HSCC '17: Proceedings of the 20th International Conference on Hybrid Systems: Computation and Control

Timing contracts for embedded controller implementation specify the constraints on the time instants at which certain operations are performed such as sampling, actuation, computation, etc. Several previous works have focused on stability analysis of ...

Comments

Information & Contributors

Information

Published In

cover image ACM Transactions on Embedded Computing Systems

ACM Transactions on Embedded Computing Systems Volume 16, Issue 5s

Special Issue ESWEEK 2017, CASES 2017, CODES + ISSS 2017 and EMSOFT 2017

October 2017

1448 pages

ISSN:1539-9087

EISSN:1558-3465

DOI:10.1145/3145508

Editor:
Sandeep K. Shukla
Indian Institute of Technology, India

Issue’s Table of Contents

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Journal Family

ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 27 September 2017

Accepted: 01 June 2017

Revised: 01 June 2017

Received: 01 April 2017

Published in TECS Volume 16, Issue 5s

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

9
Total Citations
View Citations
249
Total Downloads

Downloads (Last 12 months)18
Downloads (Last 6 weeks)0

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Baruah SHosseinzadeh MKolmanovsky ISinopoli B(2024)Adaptive Scheduling for Real-Time ControlProceedings of the 32nd International Conference on Real-Time Networks and Systems10.1145/3696355.3696357(165-174)Online publication date: 6-Nov-2024
https://dl.acm.org/doi/10.1145/3696355.3696357
Adhikary SKoley IGhosh SGhosh SDey S(2024)Revisiting Dynamic Scheduling of Control Tasks: A Performance-Aware Fine-Grained ApproachIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2024.344300743:11(3662-3673)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TCAD.2024.3443007
Ghosh S(2023)Delay-Aware Control for Autonomous Systems2023 36th International Conference on VLSI Design and 2023 22nd International Conference on Embedded Systems (VLSID)10.1109/VLSID57277.2023.00018(1-6)Online publication date: Jan-2023
https://doi.org/10.1109/VLSID57277.2023.00018
Adhikary SKoley IMaity SDey S(2022)Work-in-Progress: Control Skipping Sequence Synthesis to Counter Schedule-based Attacks2022 IEEE Real-Time Systems Symposium (RTSS)10.1109/RTSS55097.2022.00049(491-494)Online publication date: Dec-2022
https://doi.org/10.1109/RTSS55097.2022.00049
Ghosh SMondal ARoy DKindt PDey SChakraborty SHung CHong JBechini ASong E(2021)Proactive feedback for networked CPSProceedings of the 36th Annual ACM Symposium on Applied Computing10.1145/3412841.3441897(164-173)Online publication date: 22-Mar-2021
https://dl.acm.org/doi/10.1145/3412841.3441897
Ghosh SDey SDasgupta P(2020)Performance-Driven Post-Processing of Control Loop Execution SchedulesACM Transactions on Design Automation of Electronic Systems10.1145/342150526:2(1-27)Online publication date: 19-Oct-2020
https://dl.acm.org/doi/10.1145/3421505
Ghosh SDey SDasgupta P(2020)Pattern Guided Integrated Scheduling and Routing in Multi-Hop Control NetworksACM Transactions on Embedded Computing Systems10.1145/337213419:2(1-28)Online publication date: 10-Feb-2020
https://dl.acm.org/doi/10.1145/3372134
Roy DGhosh SZhu QCaccamo MChakraborty S(2020)GoodSpread: Criticality-Aware Static Scheduling of CPS with Multi-QoS Resources2020 IEEE Real-Time Systems Symposium (RTSS)10.1109/RTSS49844.2020.00026(178-190)Online publication date: Dec-2020
https://doi.org/10.1109/RTSS49844.2020.00026
Ghosh SDey SDasgupta P(2019)Synthesizing Performance-Aware (m, k)-Firm Control Execution Patterns Under Dropped Samples2019 32nd International Conference on VLSI Design and 2019 18th International Conference on Embedded Systems (VLSID)10.1109/VLSID.2019.00019(1-6)Online publication date: Jan-2019
https://doi.org/10.1109/VLSID.2019.00019

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Issue’s Table of Contents