A Method for Reducing Wireless Sensor Network Nodes Using Genetic Algorithm and Dempster Shafer

Authors : Zari Valikhani , Hadi Asharioun

Keywords :– Routing Improvement, Wireless Sensor, Genetics, and Objective Functions.
Published Online : 14 December 2019

  • View Full Abstract

    In recent years, the use of wireless sensor networks in various sectors is rapidly expanding. In direct
    transmission, each sensor sends information directly to the center. Due to the large distance, sensors from the center consume a lot of energy. Designs that shorten communication intervals can lengthen network lifetimes. Therefore, optimal layout and power consumption directly affect the lifetime of the sensor network. In contrast to designs that shorten communication intervals, they can extend the life of the network. Therefore, optimal layout and power consumption directly affect the lifetime of the sensor network.
    Congestion control is defined as one of the most important challenges in wireless sensor networks. Limitations and problems that cause this first of all, there is the essence of sensor networks, and secondly, the transmission of multimedia information and applications that use this information are causing congestion. For this purpose, it is necessary to analyze the layers of this network properly and introduce the appropriate mechanisms for transmitting multimedia information in the sensor network for each layer.
    One of these layers is the transfer layer. Shift detection is essential to efficiently utilize network resources to balance traffic loads. In this research, a method for routing with knowledge of congestion control and interference in wireless sensor networks has been presented. In the proposed method, the congestion control scheme using the genetic algorithm and the definition of the two target functions reduced the latency of packet forwarding and the expected transfer number for reaching the destination. The simulation
    results indicate that the algorithm’s response the suggestion can be close to the optimal answer.
  • View References

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