Sensor node failure detection using check point recovery algorithm

Singh, Sandeep; Jinila, Y. Bevish

doi:10.1109/icrtit.2016.7569585

Cited by 12 publications

(5 citation statements)

References 6 publications

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“…During the second phase of the protocol the failure is detected, where each node sends heart-beat periodically to the cluster head and finally in the third phase faulty cluster heads are replaced. Sandeep Saurav Singh et al [15] also have proposed similar protocol which is based on check pointing algorithm, in which while transferring the data among the nodes, the nodes send a heartbeat message. The energy level of the node is considered low and it is leading towards failure, if it does not respond with its heartbeat.…”

Section: Related Workmentioning

confidence: 99%

Energy efficient secured cluster based distributed fault diagnosis protocol for IoT

Ara

2022

Int. j. commun. netw. inf. secur.

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The rapid growth of internet and internet services provision offers wide scope to the industries to couple the various network models to design a flexible and simplified communication infrastructure. A significant attention paid towards Internet of things (IoT), from both academics and industries. Connecting and organizing of communication over wireless IoT network models are vulnerable to various security threats, due to the lack of inappropriate security deployment models. In addition to this, these models have not only security issues; they also have many performance issues. This research work deals with an IoT security over WSN model to overcome the security and performance issues by designing a Energy efficient secured cluster based distributed fault diagnosis protocol (EESCFD) Model which combines the self-fault diagnosis routing model using cluster based approach and block cipher to organize a secured data communication and to identify security fault and communication faults to improve communication efficiency. In addition we achieve an energy efficiency by employing concise block cipher which identifies the ideal size of block, size of key, number of rounds to perform the key operations in the cipher.

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Section: Related Workmentioning

confidence: 99%

Energy efficient secured cluster based distributed fault diagnosis protocol for IoT

Ara

2022

Int. j. commun. netw. inf. secur.

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“…The possible solution to restore the connectivity (Essam et al, 2018;Jahanshahi and Maddah, 2018;Feng et al, 2019;Joshi and Younis, 2016) can be through node relocation by cascaded node movement as mentioned in (Mahmood et al, 2018). But in this method, the leaf node replaces the failed node and hence there is a coverage hole at the place of the leaf node and also only a single node failure (Singh and Jinila, 2016) can be recovered by cascaded movement. Thus, this solution can address only single node failure and also needs reconstruction of the topology by node movement.…”

Section: Introductionmentioning

confidence: 99%

Fault Node Detection and Connectivity Restoration with Mobile Relay Node in Wireless Sensor Networks

Anuradha¹,

Swetha²,

Doraipandian³

2020

Journal of Computer Science

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In Wireless Sensor Network (WSN), node failure is an imperative concern in a hostile environment. These node failures create disjoints in the network and leads to a network partitioning problem. It is important for the nodes to be alive and communicate with each other to check the network connectivity. Replacement of Mobile Relay Nodes (MRN) in the location of faulty nodes is the best solutions to ree stablish the network connectivity. In this paper, a diverse mechanism is proposed to restore the network connectivity, in the first approach the gateway node takes the responsibility of identifying the faulty node and corresponding communication is to be given to MRN. In the second approach, the residual energy of each node will play a major role in determining the faulty node. Further, performance analysis was performed using a hardware setup with Node MCU and Raspberry Pi3, which proves that this work is mainly suitable for resource constrained devices and provides better results in restoring network connectivity. The performance was validated using experimental analysis and better performance was achieved.

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“…Another approach, mainly for wireless sensor networks, is the check-point recover algorithm which measures the energy level of a sensor and sends that information through all the network. If one sensor is not able to send this energy level, then it is assumed as a fault [ 21 ]. In literature [ 19 , 20 , 21 , 22 ], some proposal for failure detection in sensors through neural networks learning algorithms and support vector machines have been reported.…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Failure Detection on a Wireless Sensor Network for Indoor Climate Conditions

Gutiérrez

Ponce

2019

Sensors

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Wireless sensor networks (WSN) involve large number of sensor nodes distributed at diverse locations. The collected data are prone to be inaccurate and faulty due to internal or external influences, such as, environmental interference or sensor aging. Intelligent failure detection is necessary for the effective functioning of the sensor network. In this paper, we propose a supervised learning method that is named artificial hydrocarbon networks (AHN), to predict temperature in a remote location and detect failures in sensors. It allows predicting the temperature and detecting failure in sensor node of remote locations using information from a web service comparing it with field temperature sensors. For experimentation, we implemented a small WSN to test our sensor in order to measure failure detection, identification and accommodation proposal. In our experiments, 94.18% of the testing data were recovered and accommodated allowing of validation our proposed approach that is based on AHN, which detects, identify and accommodate sensor failures accurately.

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Sensor node failure detection using check point recovery algorithm

Cited by 12 publications

References 6 publications

Energy efficient secured cluster based distributed fault diagnosis protocol for IoT

Energy efficient secured cluster based distributed fault diagnosis protocol for IoT

Fault Node Detection and Connectivity Restoration with Mobile Relay Node in Wireless Sensor Networks

An Intelligent Failure Detection on a Wireless Sensor Network for Indoor Climate Conditions

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