Optimum communication paths for mobile WSNs using genetic algorithms

Cirstea, Cosmin; Davidescu, Roxana; Jianu, Alexandru

doi:10.1109/tsp.2013.6613940

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…These way points are optimized using genetic algorithms for minimizing ME's tour. An approach for determining optimized path from source to destination was proposed in [8].…”

Section: Clusteringmentioning

confidence: 99%

“…In this case neither ME has to visit the exact location of EN 1 nor there is a need of identifying HL for EN 1 since ME can collect the data while it is moving, hence HLIT modifies HLI based on this criterion as per (8). Criterion 3: en i+1 is at a distance > T r from the path en i to en i+2 Let us assume the node deployment scenario as per Fig.…”

Section: Halting Location Based Path Optimizationmentioning

confidence: 99%

See 1 more Smart Citation

A Cluster–based Approach for Minimizing Energy Consumption by Reducing Travel Time of Mobile Element in WSN

Prashanth

Nandury

2020

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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Envoy Node Identification (ENI) and Halting Location Identifier (HLI) algorithms have been developed to reduce the travel time of Mobile Element (ME) by determining Optimal Path(OP) in Wireless Sensor Networks. Data generated by cluster members will be aggregated at the Cluster Head (CH) identified by ENI for onward transmission to the ME and it likewise decides an ideal path for ME by interfacing all CH/Envoy Nodes (EN). In order to reduce the tour length (TL) further HLI determines finest number of Halting Locations that cover all ENs by taking transmission range of CH/ENs into consideration. Impact of ENI and HLI on energy consumption and travel time of ME have been examined through simulations.

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“…These way points are optimized using genetic algorithms for minimizing ME's tour. An approach for determining optimized path from source to destination was proposed in [8].…”

Section: Clusteringmentioning

confidence: 99%

Section: Halting Location Based Path Optimizationmentioning

confidence: 99%

A Cluster–based Approach for Minimizing Energy Consumption by Reducing Travel Time of Mobile Element in WSN

Prashanth

Nandury

2020

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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Cluster-based rendezvous points selection for reducing tour length of mobile element in WSN

Prashanth

Nandury

2015

2015 IEEE International Advance Computing Conference (IACC)

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Congestion Controlled WSN using Genetic Algorithm with different Source and Sink Mobility Scenarios

Verma¹,

Mittal²

2014

IJCA

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Wireless Sensor Networks are extremely densely populated and have to handle large bursts of data during high activity periods giving rise to congestion which may disrupt normal operation. It usually occurs when most of the data packets follow one route to reach from source to destination. Thus, there is a need of some new approach which could control congestion to meet increasing traffic demand and improved utilization of existing resources. Chance of congestion increases when both source and sink node are mobile. Due to mobility of source or sink, there is a need of determining optimal path every time when source or sink changes its position. So selection of optimal path is necessary in order to mitigate chance of congestion in the network. This paper employs new genetic algorithm based approach to determine an optimal path from source to destination for different scenarios of source or/and sink node mobility. Concept of connection value and localization region has been employed to determine an optimal path each time the data packet is being sent. An optimal path is the path that has minimum number of connections. In order to send the data packet from source to destination, there is requirement of genetic algorithm that automatically controls congestion. Simulations are performed for different scenarios of source or/and sink mobility. Significant improvements have been observed in terms of congestion value for genetic algorithm. Simulations results determine best route with minimum connection value by incorporating genetic algorithm.

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Optimum communication paths for mobile WSNs using genetic algorithms

Cited by 3 publications

References 11 publications

A Cluster–based Approach for Minimizing Energy Consumption by Reducing Travel Time of Mobile Element in WSN

A Cluster–based Approach for Minimizing Energy Consumption by Reducing Travel Time of Mobile Element in WSN

Cluster-based rendezvous points selection for reducing tour length of mobile element in WSN

Congestion Controlled WSN using Genetic Algorithm with different Source and Sink Mobility Scenarios

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