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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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/ |
work_keys_str_mv |
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