Selective task scheduling for time-targeted workflow execution on cloud

In Yong Jung; Chang-Sung Jeong

doi:10.1109/HPCC.2014.177

Selective task scheduling for time-targeted workflow execution on cloud

In Yong Jung, Chang-Sung Jeong

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

With increasing demand of data-intensive applications, a workflow with multiple distributed parallel applications becomes a useful way to build various large scale data processing applications on cloud environments. However, previous scheduling approaches for executing workflows are focused on estimating minimum make span of executions on pre-configured clusters. In this paper, we present two time-targeted selective task scheduling schemes which consider malleability and rigidity of each task, named SDER (Sequential Deployment with Expanded Resources) and DDMS (Distributed Deployment on Multiple Streams). These scheduling algorithms deploy all task of workflow in sequential and distributed ways each, and estimate optimized number of resources for completing workflow execution within given deadline. We show the experimental results which compares the performance of two scheduling schemes for various workflows.

Original language	English
Title of host publication	Proceedings - 16th IEEE International Conference on High Performance Computing and Communications, HPCC 2014, 11th IEEE International Conference on Embedded Software and Systems, ICESS 2014 and 6th International Symposium on Cyberspace Safety and Security, CSS 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1055-1059
Number of pages	5
ISBN (Electronic)	9781479961238
DOIs	https://doi.org/10.1109/HPCC.2014.177
Publication status	Published - 2014 Mar 9
Event	16th IEEE International Conference on High Performance Computing and Communications, HPCC 2014, 11th IEEE International Conference on Embedded Software and Systems, ICESS 2014 and 6th International Symposium on Cyberspace Safety and Security, CSS 2014 - Paris, France Duration: 2014 Aug 20 → 2014 Aug 22

Other

Other	16th IEEE International Conference on High Performance Computing and Communications, HPCC 2014, 11th IEEE International Conference on Embedded Software and Systems, ICESS 2014 and 6th International Symposium on Cyberspace Safety and Security, CSS 2014
Country/Territory	France
City	Paris
Period	14/8/20 → 14/8/22

Keywords

cloud computing
task scheduling algorithm
workflow execution

ASJC Scopus subject areas

Computer Science Applications
Electrical and Electronic Engineering
Computer Networks and Communications

Access to Document

10.1109/HPCC.2014.177

Cite this

Jung, I. Y., & Jeong, C-S. (2014). Selective task scheduling for time-targeted workflow execution on cloud. In Proceedings - 16th IEEE International Conference on High Performance Computing and Communications, HPCC 2014, 11th IEEE International Conference on Embedded Software and Systems, ICESS 2014 and 6th International Symposium on Cyberspace Safety and Security, CSS 2014 (pp. 1055-1059). [7056874] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HPCC.2014.177

Selective task scheduling for time-targeted workflow execution on cloud. / Jung, In Yong; Jeong, Chang-Sung.

Proceedings - 16th IEEE International Conference on High Performance Computing and Communications, HPCC 2014, 11th IEEE International Conference on Embedded Software and Systems, ICESS 2014 and 6th International Symposium on Cyberspace Safety and Security, CSS 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 1055-1059 7056874.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Jung, IY & Jeong, C-S 2014, Selective task scheduling for time-targeted workflow execution on cloud. in Proceedings - 16th IEEE International Conference on High Performance Computing and Communications, HPCC 2014, 11th IEEE International Conference on Embedded Software and Systems, ICESS 2014 and 6th International Symposium on Cyberspace Safety and Security, CSS 2014., 7056874, Institute of Electrical and Electronics Engineers Inc., pp. 1055-1059, 16th IEEE International Conference on High Performance Computing and Communications, HPCC 2014, 11th IEEE International Conference on Embedded Software and Systems, ICESS 2014 and 6th International Symposium on Cyberspace Safety and Security, CSS 2014, Paris, France, 14/8/20. https://doi.org/10.1109/HPCC.2014.177

Jung IY, Jeong C-S. Selective task scheduling for time-targeted workflow execution on cloud. In Proceedings - 16th IEEE International Conference on High Performance Computing and Communications, HPCC 2014, 11th IEEE International Conference on Embedded Software and Systems, ICESS 2014 and 6th International Symposium on Cyberspace Safety and Security, CSS 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 1055-1059. 7056874 doi: 10.1109/HPCC.2014.177

Jung, In Yong ; Jeong, Chang-Sung. / Selective task scheduling for time-targeted workflow execution on cloud. Proceedings - 16th IEEE International Conference on High Performance Computing and Communications, HPCC 2014, 11th IEEE International Conference on Embedded Software and Systems, ICESS 2014 and 6th International Symposium on Cyberspace Safety and Security, CSS 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 1055-1059

@inproceedings{8cd731ae6f474eceb2455b7a01cd31d9,

title = "Selective task scheduling for time-targeted workflow execution on cloud",

abstract = "With increasing demand of data-intensive applications, a workflow with multiple distributed parallel applications becomes a useful way to build various large scale data processing applications on cloud environments. However, previous scheduling approaches for executing workflows are focused on estimating minimum make span of executions on pre-configured clusters. In this paper, we present two time-targeted selective task scheduling schemes which consider malleability and rigidity of each task, named SDER (Sequential Deployment with Expanded Resources) and DDMS (Distributed Deployment on Multiple Streams). These scheduling algorithms deploy all task of workflow in sequential and distributed ways each, and estimate optimized number of resources for completing workflow execution within given deadline. We show the experimental results which compares the performance of two scheduling schemes for various workflows.",

keywords = "cloud computing, task scheduling algorithm, workflow execution",

author = "Jung, {In Yong} and Chang-Sung Jeong",

year = "2014",

month = mar,

day = "9",

doi = "10.1109/HPCC.2014.177",

language = "English",

pages = "1055--1059",

booktitle = "Proceedings - 16th IEEE International Conference on High Performance Computing and Communications, HPCC 2014, 11th IEEE International Conference on Embedded Software and Systems, ICESS 2014 and 6th International Symposium on Cyberspace Safety and Security, CSS 2014",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "16th IEEE International Conference on High Performance Computing and Communications, HPCC 2014, 11th IEEE International Conference on Embedded Software and Systems, ICESS 2014 and 6th International Symposium on Cyberspace Safety and Security, CSS 2014 ; Conference date: 20-08-2014 Through 22-08-2014",

}

TY - GEN

T1 - Selective task scheduling for time-targeted workflow execution on cloud

AU - Jung, In Yong

AU - Jeong, Chang-Sung

PY - 2014/3/9

Y1 - 2014/3/9

N2 - With increasing demand of data-intensive applications, a workflow with multiple distributed parallel applications becomes a useful way to build various large scale data processing applications on cloud environments. However, previous scheduling approaches for executing workflows are focused on estimating minimum make span of executions on pre-configured clusters. In this paper, we present two time-targeted selective task scheduling schemes which consider malleability and rigidity of each task, named SDER (Sequential Deployment with Expanded Resources) and DDMS (Distributed Deployment on Multiple Streams). These scheduling algorithms deploy all task of workflow in sequential and distributed ways each, and estimate optimized number of resources for completing workflow execution within given deadline. We show the experimental results which compares the performance of two scheduling schemes for various workflows.

AB - With increasing demand of data-intensive applications, a workflow with multiple distributed parallel applications becomes a useful way to build various large scale data processing applications on cloud environments. However, previous scheduling approaches for executing workflows are focused on estimating minimum make span of executions on pre-configured clusters. In this paper, we present two time-targeted selective task scheduling schemes which consider malleability and rigidity of each task, named SDER (Sequential Deployment with Expanded Resources) and DDMS (Distributed Deployment on Multiple Streams). These scheduling algorithms deploy all task of workflow in sequential and distributed ways each, and estimate optimized number of resources for completing workflow execution within given deadline. We show the experimental results which compares the performance of two scheduling schemes for various workflows.

KW - cloud computing

KW - task scheduling algorithm

KW - workflow execution

UR - http://www.scopus.com/inward/record.url?scp=84983103131&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84983103131&partnerID=8YFLogxK

U2 - 10.1109/HPCC.2014.177

DO - 10.1109/HPCC.2014.177

M3 - Conference contribution

AN - SCOPUS:84983103131

SP - 1055

EP - 1059

BT - Proceedings - 16th IEEE International Conference on High Performance Computing and Communications, HPCC 2014, 11th IEEE International Conference on Embedded Software and Systems, ICESS 2014 and 6th International Symposium on Cyberspace Safety and Security, CSS 2014

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 16th IEEE International Conference on High Performance Computing and Communications, HPCC 2014, 11th IEEE International Conference on Embedded Software and Systems, ICESS 2014 and 6th International Symposium on Cyberspace Safety and Security, CSS 2014

Y2 - 20 August 2014 through 22 August 2014

ER -

Selective task scheduling for time-targeted workflow execution on cloud

Abstract

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this