Underground WSN Optimization By Sleep, Awake Mode And Genetic Clustering.

Along with the goals of safe and efficient underground mining operations, reliable communication is a high- stakes problem in the mining industry, which is a tough place to work. Automation through remote and automatic systems has led to improvements in the health and safety of the workplace for wor...

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Published in:Journal of Namibian Studies Vol. 33; pp. 4488 - 4503
Main Authors: Sharma, Mukesh, Gupta, Sanjeev Kumar
Format: Article
Published: Society of Cultural Studies & Social Sciences 2023 Supplement
Subjects:
Online Access:View this record in EBSCOhost
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      dt: 2023 Supplement
      vid: 33
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      pub: Society of Cultural Studies & Social Sciences
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        atl: Underground WSN Optimization By Sleep, Awake Mode And Genetic Clustering.
      aug:
        au:
          Sharma, Mukesh
          Gupta, Sanjeev Kumar
        affil: Ravindra Nath Tagore University Department of Electronics & Communication Engineering Bhopal, MP, India.
      su:
        Mines & mineral resources
        Wireless sensor networks
        Sleep
        Genetic algorithms
        Swarm intelligence
        Life spans
      sug:
        subj:
          Mines & mineral resources
          Wireless sensor networks
          Sleep
          Genetic algorithms
          Swarm intelligence
          Life spans
      keyword:
        Clustering
        Energy Optimization
        Routing
        UWSN
      ab: Along with the goals of safe and efficient underground mining operations, reliable communication is a high- stakes problem in the mining industry, which is a tough place to work. Automation through remote and automatic systems has led to improvements in the health and safety of the workplace for workers, the control of operations, the use of energy and money, and the ability to respond to events in real time. In this situation, Wireless Sensor Networks (WSNs) have been used a lot in underground monitoring and communication systems to track workers and tools, watch operations, and keep an eye on the environment. This paper has proposed a model that works in sleep and awake mode to increase the life span of network. Further paper has proposed a modified bio-geographical optimization genetic algorithm for the clustering of the nodes as per energy and distance of nodes. Both of the approach increases the performance of the underground WSN network. Experiment was done on different situation of the WSN and results that proposed model has improved various evaluation parameters values.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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