Comparison and analysis of eight scheduling heuristics for the optimization of energy consumption and makespan in large-scale distributed systems

In this paper, we study the problem of scheduling tasks on a distributed system, with the aim to simultaneously minimize energy consumption and makespan subject to the deadline constraints and the tasks’ memory requirements. A total of eight heuristics are introduced to solve the task scheduling pro...

Full description

Saved in:
Bibliographic Details
Published inThe Journal of supercomputing Vol. 59; no. 1; pp. 323 - 360
Main Authors Lindberg, Peder, Leingang, James, Lysaker, Daniel, Khan, Samee Ullah, Li, Juan
Format Journal Article
LanguageEnglish
Published Boston Springer US 01.01.2012
Subjects
Compilers
Computer Science
Interpreters
Processor Architectures
Programming Languages
Large-scale systems
Distributed systems
Energy-efficiency
Optimization
Online AccessGet full text

Cover

More Information
Summary:In this paper, we study the problem of scheduling tasks on a distributed system, with the aim to simultaneously minimize energy consumption and makespan subject to the deadline constraints and the tasks’ memory requirements. A total of eight heuristics are introduced to solve the task scheduling problem. The set of heuristics include six greedy algorithms and two naturally inspired genetic algorithms. The heuristics are extensively simulated and compared using an simulation test-bed that utilizes a wide range of task heterogeneity and a variety of problem sizes. When evaluating the heuristics, we analyze the energy consumption, makespan, and execution time of each heuristic. The main benefit of this study is to allow readers to select an appropriate heuristic for a given scenario.
ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-010-0439-6