Active Data Replica Recovery for Quality-Assurance Big Data Analysis in IC-IoT

QoS-aware big data analysis is critical in Information-Centric Internet of Things (IC-IoT) system to support various applications like smart city, smart grid, smart health, intelligent transportation systems, and so on. The employment of non-volatile memory (NVM) in cloud or edge system provides goo...

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Main Authors: Songyun Wang, Jiabin Yuan, Xin Li, Zhuzhong Qian, Fabio Arena, Ilsun You
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
NVM
Online Access:https://ieeexplore.ieee.org/document/8782595/
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spelling doaj-097b6d69f4634d7b8a44f4f4c275a1a62021-04-05T17:08:00ZengIEEEIEEE Access2169-35362019-01-01710699710700510.1109/ACCESS.2019.29322598782595Active Data Replica Recovery for Quality-Assurance Big Data Analysis in IC-IoTSongyun Wang0Jiabin Yuan1Xin Li2https://orcid.org/0000-0002-1450-9241Zhuzhong Qian3Fabio Arena4Ilsun You5https://orcid.org/0000-0002-0604-3445College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, ChinaCollege of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, ChinaCollege of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, ChinaState Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, ChinaFaculty of Engineering and Architecture, Kore University of Enna, Enna, ItalyDepartment of Information Security Engineering, Soonchunhyang University, Asan, South KoreaQoS-aware big data analysis is critical in Information-Centric Internet of Things (IC-IoT) system to support various applications like smart city, smart grid, smart health, intelligent transportation systems, and so on. The employment of non-volatile memory (NVM) in cloud or edge system provides good opportunity to improve quality of data analysis tasks. However, we have to face the data recovery problem led by NVM failure due to the limited write endurance. In this paper, we investigate the data recovery problem for QoS guarantee and system robustness, followed by proposing a rarity-aware data recovery algorithm. The core idea is to establish the rarity indicator to evaluate the replica distribution and service requirement comprehensively. With this idea, we give the lost replicas with distinguishing priority and eliminate the unnecessary replicas. Then, the data replicas are recovered stage by stage to guarantee QoS and provide system robustness. From our extensive experiments and simulations, it is shown that the proposed algorithm has significant performance improvement on QoS and robustness than the traditional direct data recovery method. Besides, the algorithm gives an acceptable data recovery time.https://ieeexplore.ieee.org/document/8782595/Big data analysisdata recoveryIC-IoTNVMQoS improvement
collection DOAJ
language English
format Article
sources DOAJ
author Songyun Wang
Jiabin Yuan
Xin Li
Zhuzhong Qian
Fabio Arena
Ilsun You
spellingShingle Songyun Wang
Jiabin Yuan
Xin Li
Zhuzhong Qian
Fabio Arena
Ilsun You
Active Data Replica Recovery for Quality-Assurance Big Data Analysis in IC-IoT
IEEE Access
Big data analysis
data recovery
IC-IoT
NVM
QoS improvement
author_facet Songyun Wang
Jiabin Yuan
Xin Li
Zhuzhong Qian
Fabio Arena
Ilsun You
author_sort Songyun Wang
title Active Data Replica Recovery for Quality-Assurance Big Data Analysis in IC-IoT
title_short Active Data Replica Recovery for Quality-Assurance Big Data Analysis in IC-IoT
title_full Active Data Replica Recovery for Quality-Assurance Big Data Analysis in IC-IoT
title_fullStr Active Data Replica Recovery for Quality-Assurance Big Data Analysis in IC-IoT
title_full_unstemmed Active Data Replica Recovery for Quality-Assurance Big Data Analysis in IC-IoT
title_sort active data replica recovery for quality-assurance big data analysis in ic-iot
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2019-01-01
description QoS-aware big data analysis is critical in Information-Centric Internet of Things (IC-IoT) system to support various applications like smart city, smart grid, smart health, intelligent transportation systems, and so on. The employment of non-volatile memory (NVM) in cloud or edge system provides good opportunity to improve quality of data analysis tasks. However, we have to face the data recovery problem led by NVM failure due to the limited write endurance. In this paper, we investigate the data recovery problem for QoS guarantee and system robustness, followed by proposing a rarity-aware data recovery algorithm. The core idea is to establish the rarity indicator to evaluate the replica distribution and service requirement comprehensively. With this idea, we give the lost replicas with distinguishing priority and eliminate the unnecessary replicas. Then, the data replicas are recovered stage by stage to guarantee QoS and provide system robustness. From our extensive experiments and simulations, it is shown that the proposed algorithm has significant performance improvement on QoS and robustness than the traditional direct data recovery method. Besides, the algorithm gives an acceptable data recovery time.
topic Big data analysis
data recovery
IC-IoT
NVM
QoS improvement
url https://ieeexplore.ieee.org/document/8782595/
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AT jiabinyuan activedatareplicarecoveryforqualityassurancebigdataanalysisiniciot
AT xinli activedatareplicarecoveryforqualityassurancebigdataanalysisiniciot
AT zhuzhongqian activedatareplicarecoveryforqualityassurancebigdataanalysisiniciot
AT fabioarena activedatareplicarecoveryforqualityassurancebigdataanalysisiniciot
AT ilsunyou activedatareplicarecoveryforqualityassurancebigdataanalysisiniciot
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