Data Recovery Approach for Fault-Tolerant IoT Node

Internet of Things (IoT) has a wide range of applications in many sectors like industries, health care, homes, militarily, and agriculture. Especially IoT-based safety and critical applications must be more securable and reliable. Such type of applications needs to be operated continuously even in t...

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Bibliographic Details
Published in:International journal of advanced computer science & applications Vol. 13; no. 1
Main Authors: Vedavalli, Perigisetty, Ch, Deepak
Format: Journal Article
Language:English
Published: West Yorkshire Science and Information (SAI) Organization Limited 2022
Subjects:
Algorithms
Clusters
Data integrity
Data loss
Data recovery
Data replication
Fault tolerance
Internet of Things
Network reliability
Nodes
Performance measurement
Safety
ISSN:2158-107X, 2156-5570
Online Access:Get full text
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Summary:Internet of Things (IoT) has a wide range of applications in many sectors like industries, health care, homes, militarily, and agriculture. Especially IoT-based safety and critical applications must be more securable and reliable. Such type of applications needs to be operated continuously even in the presence of errors and faults. In safety and critical IoT applica-tions maintaining data reliability and security is the critical task. IoT suffers from node failures due to limited resources and the nature of deployment which results in data loss consequently. This paper proposes a Data Recovery Approach for Fault Tolerant (DRAFT) IoT node algorithm, which is fully distributed, data replication and recovery implemented through redundant local database storage of other nodes in the network. DRAFT ensures high data availability even in the presence of node failures to preserve the data. When an IoT node fails in any cluster in the network data can be retrieved through redundant storage with the help of neighbor nodes in the cluster. The proposed algorithm is simulated for 100-150 IoT nodes which enhances 5% of network lifetime, and throughput. The performance metrics such as Mean Time to Data Loss (MTTDL), throughput, Network lifetime, and reliability are computed and results are found to be improved.
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ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2022.0130189