Optimal Discrete Rate Adaptation for Distributed Real-Time Systems with End-to-End Tasks

Authors

Yingming Chen, Washington University in St Louis
Chenyang Lu, Washington University in St LouisFollow
Xenofon Koutsoukos, Washington University in St Louis

Document Type

Technical Report

Department

Computer Science and Engineering

Publication Date

2007

Filename

wucse-2007-15.pdf

Technical Report Number

WUCSE-2007-15

Abstract

Many distributed real-time systems face the challenge of dynamically maximizing system utility in response to fluctuations in system workload. We present the MultiParametric Rate Adaptation (MPRA) algorithm for discrete rate adaptation in distributed real-time systems with end-to-end tasks. The key novelty and advantage of MPRA is that it can efficiently produce optimal solutions in response to workload changes such as dynamic task arrivals. Through oline preprocessing MPRA transforms a NP-hard utility optimization problem to a set of simple linear functions in different regions expressed in term of CPU utilization changes caused by workload variations. At run time MPRA produces optimal solutions by evaluating the linear function for the current region. Analysis and simulation results show that MPRA maximizes system utility in the presence of varying workloads, while reducing the online computation complexity to polynomial time.

Comments

Permanent URL: http://dx.doi.org/10.7936/K72805TF

Recommended Citation

Chen, Yingming; Lu, Chenyang; and Koutsoukos, Xenofon, "Optimal Discrete Rate Adaptation for Distributed Real-Time Systems with End-to-End Tasks" Report Number: WUCSE-2007-15 (2007). All Computer Science and Engineering Research.
https://openscholarship.wustl.edu/cse_research/120