Uncertainty-aware workflow migration among edge nodes based on blockchain

Abstract Workflow is one of the most typical applications in distributed computing, which makes a variety of complex computing work orderly. However, assigning workflow tasks to nodes in the process of multi-node collaboration is still a challenge, because there are some unpredictable emergencies, i...

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Main Authors: Zhanyang Xu, Qingfan Geng, Hao Cao, Chuanjian Wang, Xihua Liu
Format: Article
Language:English
Published: SpringerOpen 2019-11-01
Series:EURASIP Journal on Wireless Communications and Networking
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13638-019-1583-1
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spelling doaj-e90af4cb1ce34f45ae8e4e9b6d11a8a72020-11-25T04:08:30ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14992019-11-012019111210.1186/s13638-019-1583-1Uncertainty-aware workflow migration among edge nodes based on blockchainZhanyang Xu0Qingfan Geng1Hao Cao2Chuanjian Wang3Xihua Liu4School of Computer and Software, Nanjing University of Information Science and TechnologySchool of Computer and Software, Nanjing University of Information Science and TechnologySchool of Computer and Software, Nanjing University of Information Science and TechnologyCollege of Information Science and Technology, Shihezi UniversitySchool of Computer and Software, Nanjing University of Information Science and TechnologyAbstract Workflow is one of the most typical applications in distributed computing, which makes a variety of complex computing work orderly. However, assigning workflow tasks to nodes in the process of multi-node collaboration is still a challenge, because there are some unpredictable emergencies, i.e., uncertainty, in the process of workflow scheduling. The paper proposes a blockchain-powered resource provisioning (BPRP) method to solve the above problems. Technically, we use the directed acyclic graph in the graph theory to represent the workflow task and optimize the workflow scheduling strategy in the presence of uncertainty. The processing time and energy consumption of workflow tasks are also optimized by using non-dominated sorting genetic algorithm III (NSGA-III). Finally, we carry out experimental simulations to verify the effectiveness of the proposed method.http://link.springer.com/article/10.1186/s13638-019-1583-1BlockchainUncertainty-awareEdge computingWorkflowNSGA-III
collection DOAJ
language English
format Article
sources DOAJ
author Zhanyang Xu
Qingfan Geng
Hao Cao
Chuanjian Wang
Xihua Liu
spellingShingle Zhanyang Xu
Qingfan Geng
Hao Cao
Chuanjian Wang
Xihua Liu
Uncertainty-aware workflow migration among edge nodes based on blockchain
EURASIP Journal on Wireless Communications and Networking
Blockchain
Uncertainty-aware
Edge computing
Workflow
NSGA-III
author_facet Zhanyang Xu
Qingfan Geng
Hao Cao
Chuanjian Wang
Xihua Liu
author_sort Zhanyang Xu
title Uncertainty-aware workflow migration among edge nodes based on blockchain
title_short Uncertainty-aware workflow migration among edge nodes based on blockchain
title_full Uncertainty-aware workflow migration among edge nodes based on blockchain
title_fullStr Uncertainty-aware workflow migration among edge nodes based on blockchain
title_full_unstemmed Uncertainty-aware workflow migration among edge nodes based on blockchain
title_sort uncertainty-aware workflow migration among edge nodes based on blockchain
publisher SpringerOpen
series EURASIP Journal on Wireless Communications and Networking
issn 1687-1499
publishDate 2019-11-01
description Abstract Workflow is one of the most typical applications in distributed computing, which makes a variety of complex computing work orderly. However, assigning workflow tasks to nodes in the process of multi-node collaboration is still a challenge, because there are some unpredictable emergencies, i.e., uncertainty, in the process of workflow scheduling. The paper proposes a blockchain-powered resource provisioning (BPRP) method to solve the above problems. Technically, we use the directed acyclic graph in the graph theory to represent the workflow task and optimize the workflow scheduling strategy in the presence of uncertainty. The processing time and energy consumption of workflow tasks are also optimized by using non-dominated sorting genetic algorithm III (NSGA-III). Finally, we carry out experimental simulations to verify the effectiveness of the proposed method.
topic Blockchain
Uncertainty-aware
Edge computing
Workflow
NSGA-III
url http://link.springer.com/article/10.1186/s13638-019-1583-1
work_keys_str_mv AT zhanyangxu uncertaintyawareworkflowmigrationamongedgenodesbasedonblockchain
AT qingfangeng uncertaintyawareworkflowmigrationamongedgenodesbasedonblockchain
AT haocao uncertaintyawareworkflowmigrationamongedgenodesbasedonblockchain
AT chuanjianwang uncertaintyawareworkflowmigrationamongedgenodesbasedonblockchain
AT xihualiu uncertaintyawareworkflowmigrationamongedgenodesbasedonblockchain
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