Functional Uncertainty in Real-Time Safety-Critical Systems

Sanjoy Baruah; Alan Burns; David Jack Griffin

Functional Uncertainty in Real-Time Safety-Critical Systems

Sanjoy Baruah, Alan Burns, David Jack Griffin

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Safety-critical cyber-physical systems increasingly use components that are unable to provide deterministic guarantees of the correctness of their functional outputs; rather, they characterize each outcome of a computation with an associated uncertainty regarding its correctness.
The problem of assuring correctness in such systems is considered. A model is proposed in which components are characterized by bounds on the degree of uncertainty under both worst-case and typical circumstances; the objective is to assure safety under all circumstances while optimizing for performance for typical circumstances.
A problem of selecting components for execution in order to obtain a result of a certain minimum uncertainty as soon as possible, while guaranteeing to do so within a specified deadline, is considered.
An optimal semi-adaptive algorithm for solving this problem is derived.
The scalability of this algorithm is investigated via simulation experiments comparing this semi-adaptive scheme with a purely static approach.

Original language	English
Title of host publication	Proceeding Real-Time Networks and Systems
Publisher	ACM
Number of pages	11
Publication status	Published - 7 Jun 2022

Bibliographical note

© 2022 Copyright held by the owner/author(s). This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

Access to Document

paper
© 2022 Copyright held by the owner/author(s). This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details
Accepted author manuscript, 832 KBLicence: Unspecified

Cite this

@inproceedings{7574926713f749878b3915323b74c982,

title = "Functional Uncertainty in Real-Time Safety-Critical Systems",

abstract = "Safety-critical cyber-physical systems increasingly use components that are unable to provide deterministic guarantees of the correctness of their functional outputs; rather, they characterize each outcome of a computation with an associated uncertainty regarding its correctness.The problem of assuring correctness in such systems is considered. A model is proposed in which components are characterized by bounds on the degree of uncertainty under both worst-case and typical circumstances; the objective is to assure safety under all circumstances while optimizing for performance for typical circumstances. A problem of selecting components for execution in order to obtain a result of a certain minimum uncertainty as soon as possible, while guaranteeing to do so within a specified deadline, is considered.An optimal semi-adaptive algorithm for solving this problem is derived. The scalability of this algorithm is investigated via simulation experiments comparing this semi-adaptive scheme with a purely static approach.",

author = "Sanjoy Baruah and Alan Burns and Griffin, {David Jack}",

note = "{\textcopyright} 2022 Copyright held by the owner/author(s). This is an author-produced version of the published paper. Uploaded in accordance with the publisher{\textquoteright}s self-archiving policy. Further copying may not be permitted; contact the publisher for details",

year = "2022",

month = jun,

day = "7",

language = "English",

booktitle = "Proceeding Real-Time Networks and Systems",

publisher = "ACM",

address = "United States",

}

TY - GEN

T1 - Functional Uncertainty in Real-Time Safety-Critical Systems

AU - Baruah, Sanjoy

AU - Burns, Alan

AU - Griffin, David Jack

N1 - © 2022 Copyright held by the owner/author(s). This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

PY - 2022/6/7

Y1 - 2022/6/7

N2 - Safety-critical cyber-physical systems increasingly use components that are unable to provide deterministic guarantees of the correctness of their functional outputs; rather, they characterize each outcome of a computation with an associated uncertainty regarding its correctness.The problem of assuring correctness in such systems is considered. A model is proposed in which components are characterized by bounds on the degree of uncertainty under both worst-case and typical circumstances; the objective is to assure safety under all circumstances while optimizing for performance for typical circumstances. A problem of selecting components for execution in order to obtain a result of a certain minimum uncertainty as soon as possible, while guaranteeing to do so within a specified deadline, is considered.An optimal semi-adaptive algorithm for solving this problem is derived. The scalability of this algorithm is investigated via simulation experiments comparing this semi-adaptive scheme with a purely static approach.

AB - Safety-critical cyber-physical systems increasingly use components that are unable to provide deterministic guarantees of the correctness of their functional outputs; rather, they characterize each outcome of a computation with an associated uncertainty regarding its correctness.The problem of assuring correctness in such systems is considered. A model is proposed in which components are characterized by bounds on the degree of uncertainty under both worst-case and typical circumstances; the objective is to assure safety under all circumstances while optimizing for performance for typical circumstances. A problem of selecting components for execution in order to obtain a result of a certain minimum uncertainty as soon as possible, while guaranteeing to do so within a specified deadline, is considered.An optimal semi-adaptive algorithm for solving this problem is derived. The scalability of this algorithm is investigated via simulation experiments comparing this semi-adaptive scheme with a purely static approach.

M3 - Conference contribution

BT - Proceeding Real-Time Networks and Systems

PB - ACM

ER -