Summary: Energy­Aware Partitioning for Multiprocessor Real­Time Systems
Hakan Aydin, Qi Yang
Computer Science Department
George Mason University
Fairfax, VA 22030
(aydin, qyang1)@cs.gmu.edu
Abstract
In this paper, we address the problem of partitioning peri­
odic real­time tasks in a multiprocessor platform by consid­
ering both feasibility and energy­awareness perspectives: our
objective is to compute the feasible partitioning that results in
minimum energy consumption on multiple identical processors
by using variable voltage Earliest­Deadline­First scheduling.
We show that the problem is NP­Hard in the strong sense on
m # 2 processors even when feasibility is guaranteed a priori.
Then, we develop our framework where load balancing plays
a major role in producing energy­efficient partitionings. We
evaluate the feasibility and energy­efficiency performances of
partitioning heuristics experimentally.
1 Introduction

Source: Aydin, Hakan - Department of Computer Science, George Mason University

Collections: Computer Technologies and Information Sciences; Engineering