Next Article in Journal
Robust Object Tracking in Infrared Video via Adaptive Weighted Patches
Previous Article in Journal
Optimization of Setting Take-Profit Levels for Derivative Trading
Article Menu

Export Article

Open AccessArticle
Math. Comput. Appl. 2017, 22(1), 2;

A Novel, Energy-Aware Task Duplication-Based Scheduling Algorithm of Parallel Tasks on Clusters

Beijing Key Laboratory of Information Service Engineering, Beijing Union University, No. 97 Beisihuan East Road, Chaoyang District, Beijing 100101, China
Computer and Engineering School, Beihang University, No. 37 Xueyuanlu, Haidian District, Beijing 100191, China
Author to whom correspondence should be addressed.
Academic Editor: Fazal M. Mahomed
Received: 21 September 2016 / Revised: 9 December 2016 / Accepted: 19 December 2016 / Published: 27 December 2016
Full-Text   |   PDF [2543 KB, uploaded 27 December 2016]   |  


Increasing energy has become an important issue in high performance clusters. To balance the energy and performance, we proposed a novel, energy-aware duplication-based scheduling (NEADS). An existing energy-aware duplication-based algorithm replicates all qualified predecessor tasks in a bottom-up manner. Some tasks without direct relation may be replicated to the same processor, which cannot reduce the communication energy. Instead, the computation overhead may be increased. In contrast, the proposed algorithm only replicates the directly correlated predecessor tasks in the energy threshold range without lengthening the schedule length. The proposed algorithm is compared with the non-duplication algorithm and existing duplicated-based algorithm. Extensive experimental results show that the proposed algorithm can effectively reduce energy consumption in various applications. It has advantages over other algorithms on computation-intensive applications. View Full-Text
Keywords: task duplication; scheduling; energy-aware; clusters; Directed Acyclic Graph (DAG) task duplication; scheduling; energy-aware; clusters; Directed Acyclic Graph (DAG)

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Liang, A.; Pang, Y. A Novel, Energy-Aware Task Duplication-Based Scheduling Algorithm of Parallel Tasks on Clusters. Math. Comput. Appl. 2017, 22, 2.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Statistics



[Return to top]
Math. Comput. Appl. EISSN 2297-8747 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top