TY - GEN
T1 - Fault-tolerant scheduling for scientific workflow with task replication method in cloud
AU - Li, Zhongjin
AU - Yu, Jiacheng
AU - Hu, Haiyang
AU - Chen, Jie
AU - Hu, Hua
AU - Ge, Jidong
AU - Chang, Victor
N1 - Publisher Copyright:
Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.
PY - 2018
Y1 - 2018
N2 - Cloud computing has become a revolutionary paradigm by provisioning on-demand and low cost computing resources for customers. As a result, scientific workflow, which is the big data application, is increasingly prone to adopt cloud computing resources. However, internal failure (host fault) is inevitable in such large distributed computing environment. It is also well studied that cloud data center will experience malicious attacks frequently. Hence, external failure (failure by malicious attack) should also be considered when executing scientific workflows in cloud. In this paper, a fault-tolerant scheduling (FTS) algorithm is proposed for scientific workflow in cloud computing environment, the aim of which is to minimize the workflow cost with the deadline constraint even in the presence of internal and external failures. The FTS algorithm, based on tasks replication method, is one of the widely used fault tolerant mechanisms. The experimental results in terms of real-world scientific workflow applications demonstrate the effectiveness and practicality of our proposed algorithm.
AB - Cloud computing has become a revolutionary paradigm by provisioning on-demand and low cost computing resources for customers. As a result, scientific workflow, which is the big data application, is increasingly prone to adopt cloud computing resources. However, internal failure (host fault) is inevitable in such large distributed computing environment. It is also well studied that cloud data center will experience malicious attacks frequently. Hence, external failure (failure by malicious attack) should also be considered when executing scientific workflows in cloud. In this paper, a fault-tolerant scheduling (FTS) algorithm is proposed for scientific workflow in cloud computing environment, the aim of which is to minimize the workflow cost with the deadline constraint even in the presence of internal and external failures. The FTS algorithm, based on tasks replication method, is one of the widely used fault tolerant mechanisms. The experimental results in terms of real-world scientific workflow applications demonstrate the effectiveness and practicality of our proposed algorithm.
KW - Cloud Computing
KW - Fault-tolerant
KW - Scientific Workflow Scheduling
UR - http://www.scopus.com/inward/record.url?scp=85051922466&partnerID=8YFLogxK
U2 - 10.5220/0006687300950104
DO - 10.5220/0006687300950104
M3 - Conference Proceeding
AN - SCOPUS:85051922466
T3 - IoTBDS 2018 - Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security
SP - 95
EP - 104
BT - IoTBDS 2018 - Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security
A2 - Munoz, Victor Mendez
A2 - Wills, Gary
A2 - Walters, Robert
A2 - Firouzi, Farshad
A2 - Chang, Victor
PB - SciTePress
T2 - 3rd International Conference on Internet of Things, Big Data and Security, IoTBDS 2018
Y2 - 19 March 2018 through 21 March 2018
ER -