The Applications of Model Driven Architecture (MDA) in Wireless Sensor Networks (WSN): Techniques and Tools

Anwar, Muhammad Waseem; Azam, Farooque; Khan, Muazzam A.; Butt, Wasi Haider

doi:10.1007/978-3-030-12388-8_2

Cited by 5 publications

(4 citation statements)

References 23 publications

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“…Figures [3][4][5][6][7][8][9][10][11] show the simulation result of the FND-RS using HO-COA for LS-WSN. Here The various evaluation metrics, like network delay, global energy, throughput and energy consumption, are analysed and compared with the existing methods, namely, FND-RS for LS-WSN in distributed intermittent fault diagnosis algorithm (NDR-WSN-DISFD), 33 FND-RS for LS-WSN in harmony search algorithm (FNDR-WSN-HAS),19 FND-RS for LS-WSN in t-distribution-based satin bowerbird optimization (FNDR-WSN-t-DSBO), 34 FND-RS for LS-WSN in optimal emperor penguin optimization (FNDR-WSN-OEPO) 35 and FND-RS for LS-WSN in particle swarm optimization algorithm (FNDR-WSN-PSO).…”

Section: Simulation Phase 1: Performance Comparison Of Various Methodsmentioning

confidence: 99%

“…In WSN, microelectrochemical system is used due to inexpensive and low power distributed devices. These devices are known as sensor nodes 2,3 . These nodes are widely used in all places because it is small in size and a portable device 4 .…”

Section: Introductionmentioning

confidence: 99%

“…These devices are known as sensor nodes. 2,3 These nodes are widely used in all places because it is small in size and a portable device. 4 These sensors are used in the security applications, like home security, surveillance, industrial monitoring, hospitals, environmental monitoring and military operations.…”

Section: Introductionmentioning

confidence: 99%

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Faulty node detection and recovery scheme for large‐scale wireless sensor network using hosted cuckoo optimization algorithm

Palanikumar¹,

Ramasamy²,

Ragavan³

2022

Int J Communication

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Summary Large‐scale wireless sensor networks (LS‐WSNs) are used for collecting and monitoring the physical state of the environment. These networks are first sending information to the base station and then the recipient. LS‐WSNs consist of several components, such as battery, sensor, transmitter, receiver and microcontroller circuits. If any one of these hardware components does not work properly, then the entire system will become faulty condition, resulting reducing network life and accuracy. To overcome these hardware node faults, this manuscript proposes an effective deep reinforcement learning (DRL)‐adopted faulty node detection and recovery scheme (FND‐RS) integrated with the hosted cuckoo‐based optimal routing scheme for LS‐WSNs. Here, the DRL process is utilized for noticing and recovering the hardware node fault on sensor. The major objective of this system is ‘to enhance the network life with least energy consumption and also enhance the accuracy of Large Scale Wireless Sensor Networks using hosted cuckoo optimization (HO‐COA) algorithms’. The simulation is done in MATLAB. The experimental results shows that the proposed method attains lower overhead 15.65%, energy loss 21.62%, average packet delivery ratio 13.13%, energy efficiency 23.25%, network lifetime 19.12%, throughput 13.5%, time complexity 19.35% and lower delay 17.55% when compared to the existing methods, like FND‐RS for LS‐WSN in distributed intermittent fault diagnosis algorithm (NDR‐WSN‐DISFD), FND‐RS for LS‐WSN in harmony search algorithm (FNDR‐WSN‐HAS), FND‐RS for LS‐WSN in t‐distribution‐based satin bowerbird optimization (FNDR‐WSN‐t‐DSBO), FND‐RS for LS‐WSN in optimal emperor penguin optimization (FNDR‐WSN‐OEPO) and FND‐RS for LS‐WSN in particle swarm optimization algorithm (FNDR‐WSN‐PSO) respectively.

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Section: Simulation Phase 1: Performance Comparison Of Various Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Faulty node detection and recovery scheme for large‐scale wireless sensor network using hosted cuckoo optimization algorithm

Palanikumar¹,

Ramasamy²,

Ragavan³

2022

Int J Communication

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“…Applying MDE to SAN has been investigated ( [30], [28], [3]), and languages such as SensorML [8] based on a metamodel, or SOSA [17] and SSN [24], based on ontologies, have been proposed. However, we don't know any MDE approach to monitor the SAN execution while analyzing and persisting measurements.…”

Section: Introductionmentioning

confidence: 99%

Model-Driven Engineering of Monitoring Application for Sensors and Actuators Networks

Fosse

Cheng

Rocheteau

et al. 2020

2020 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

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Cyber-Physical Systems (CPSs) encompass both Information Infrastructures and networks of physical devices. Applications for monitoring them are usually implemented after the physical systems that they have to monitor: the CPS has to be running in order to monitor it. Monitoring applications define communications between the elements of those systems, and are compliant with their designs. Such applications can be complicated to develop, maintain and evolve, especially if the physical system changes. This paper brings an approach for engineering CPS monitoring applications, relying on model-driven techniques for generating a platform using the MQTT communication protocol for monitoring the CPS. First, it provides a metamodel for modeling sensors and actuators networks. Second, it introduces EMIT a monitoring platform for sensors and actuators networks. Third, it presents a transformation from models of sensors and actuators networks to automatically generate EMIT monitoring configuration. We illustrate our approach on a case study and discuss its limitations and improvement points.

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The Energy Conservation and Consumption in Wireless Sensor Networks Based on Energy Efficiency Clustering Routing Protocol

Tesha

Amanul

2020

Advances in Intelligent Systems and Computing

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The Applications of Model Driven Architecture (MDA) in Wireless Sensor Networks (WSN): Techniques and Tools

Cited by 5 publications

References 23 publications

Faulty node detection and recovery scheme for large‐scale wireless sensor network using hosted cuckoo optimization algorithm

Faulty node detection and recovery scheme for large‐scale wireless sensor network using hosted cuckoo optimization algorithm

Model-Driven Engineering of Monitoring Application for Sensors and Actuators Networks

The Energy Conservation and Consumption in Wireless Sensor Networks Based on Energy Efficiency Clustering Routing Protocol

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