A novel hierarchical fault management framework for wireless sensor networks: HFMF

Moridi, Elham; Haghparast, Majid; Hosseinzadeh, Mehdi; Jassbi, Somayyeh Jafarali

doi:10.1007/s12083-021-01226-y

Cited by 8 publications

(1 citation statement)

References 36 publications

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“…In Reference 27, a novel Hierarchical Fault Management (HFM) model has been presented to address the intermittent faults and energy dissipation issues in IWSN. The nodes were divided into virtual cells in which sensor nodes were positioned in these virtual cells.…”

Section: Related Workmentioning

confidence: 99%

An energy‐aware software fault detection system based on hierarchical rule approach for enhancing quality of service in internet of things‐enabled wireless sensor network

Balraj,

Prasanth

2024

Trans Emerging Tel Tech

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Of late, the Internet of Things (IoT) has progressed in its pervasiveness across the globe for diverse applications. Wireless Sensor Network (WSN) is one of the prominent technologies employed in IoT environments where multiple tiny sensor nodes are distributed to sense real‐time observations about unforeseeable areas for control and managerial purposes. Owing to the presence of sensors in inaccessible regions and their battery restrictions, different types of software faults occur in IoT‐enabled WSNs (IWSNs). These faults create uncertainty in data reading which causes serious damage to the sensor network. Hence, the IWSN necessitates an effective fault‐detection methodology to continue optimal activity despite the existence of software faults. This work proposes a novel Energy‐Aware Hierarchical Rule‐based Software Fault Detection (HRSFD) model to identify various software faults with minimum energy depletion in the IWSN environment. Primarily, the proposed model extracts antecedent attributes from the characteristics of the sensed data. Its abnormal values can be identified based on the obtained antecedent attributes. Subsequently, the category of the software fault is determined by applying a hierarchical rule strategy. Finally, from the simulation results, it is apparent that the fault detection accuracy rate of the proposed HRSFD model attains 99.12% for dense networks. The lifetime of the network is also prolonged by 18% as compared to the existing state‐of‐the‐art models.

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Section: Related Workmentioning

confidence: 99%

An energy‐aware software fault detection system based on hierarchical rule approach for enhancing quality of service in internet of things‐enabled wireless sensor network

Balraj,

Prasanth

2024

Trans Emerging Tel Tech

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Fuzzy Boosted Sooty Tern Optimization (FBSTO): Fault Detection and Node Recovery Approach for WSN

Chakraborty,

Raghuvanshi

2024

Int J Communication

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The fault node detection and recovery is essential in WSN for improving the network lifetime and node connectivity. Ensuring the tradeoff between energy consumption and node recovery is challenged due to redundant nodes. Hence, a novel approach is developed based on the objective of automatic recovery from failure, redundant node elimination, fault node replacement, and minimalizing energy consumption. In this approach, the fuzzy boosted sooty tern optimization (FBSTO) technique is proposed for fault node detection and replacement. Based on the node density and distance, the nodes are clustered. Then, the cluster head selection process can be accomplished with a fuzzy logic approach based on distance calculation, energy consumption, and Quality of service (QoS) nodes. The node replacement is carried out through cascaded movement, which minimizes energy utilization. The efficiency of the FBSTO approach is estimated with packet delivery ratio, packet loss ratio, end‐to‐end delay, and energy consumption. The proposed approach reduces the end‐to‐end delay to 10 ms for random deployment of 100 nodes. Also, the packet delivery ratio performance of the proposed approach is 143 for 100 SNs. For existing Multi‐objective Cluster Head Based Energy‐aware Optimized Routing (MCH‐EOR), Ant Lion Optimization (ALO), Particle swarm Optimization (PSO), Gray Wolf Optimization (GWO), and Genetic approach (GA), the packet delivery ratio is reduced to 130, 60, 50, and 100. Compared with the existing approaches, the proposed approach provides better performance.

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Automated Fault Diagnosis in Wireless Sensor Networks: A Comprehensive Survey

Swain

Dash²,

Khilar³

2022

Wireless Pers Commun

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A novel hierarchical fault management framework for wireless sensor networks: HFMF

Cited by 8 publications

References 36 publications

An energy‐aware software fault detection system based on hierarchical rule approach for enhancing quality of service in internet of things‐enabled wireless sensor network

An energy‐aware software fault detection system based on hierarchical rule approach for enhancing quality of service in internet of things‐enabled wireless sensor network

Fuzzy Boosted Sooty Tern Optimization (FBSTO): Fault Detection and Node Recovery Approach for WSN

Automated Fault Diagnosis in Wireless Sensor Networks: A Comprehensive Survey

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