Work

A Fully Polynomial Time Approximation Scheme for Adaptive Variable Rate Task Demand

Year: 2024

Type: conference-paper

Abstract: The Adaptive Variable Rate (AVR) task model defines a task where job WCET and period are a function of engine speed. Motivated by a lack of tractable AVR task demand methods, this work uses predefined job sequences for the Bounded Precedence Constraint Knapsack Problem inherent in AVR task demand calculation instead of enumerating all considered speeds as in existing work. A new, exact approach is proposed and approximated, enabling the derivation of a Fully Polynomial Time Approximation Scheme that outperforms the state-of-the-art in runtime (7,800x improvement) and RAM use (99% reduction) with less than 8% demand overestimate.

Source: International Conference on Real-Time Networks and Systems (RTNS)

DOI: 10.1145/3696355.3696367

Authors: Aaron Willcock, Nathan Fisher, Thidapat (Tam) Chantem

Institutions: Wayne State University, Virginia Tech

Language: English

Topic: Real-Time Systems Scheduling

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funder: National Science Foundation

Awards: Collaborative Research: CPS: Medium: Timeliness vs. Trustworthiness: Balancing Predictability and Security in Time-Sensitive CPS Design, S&AS: INT: Autonomous Battery Operating System (ABOS): An Adaptive and Comprehensive Approach to Efficient, Safe, and Secure Battery System Management, Collaborative Research: CPS: Medium: Timeliness vs. Trustworthiness: Balancing Predictability and Security in Time-Sensitive CPS Design, Collaborative Research: CNS Core: Medium: Parallel and Real-Time Multicore Scheduling for an Efficiently-Used Cache (PARSEC)