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<p>Multiple attribute decision-making (MADM) approaches give an ordinary performance in cluster head (CH) selection of wireless sensor network (WSN). These approaches work with the values of the attributes of the particular domain. In this article, we pass the minimum number of relevant parameters of WSN as an input to the modified MADM approaches to give a better CH set to achieve proper load balancing in WSN. We studied a total of twelve such parameters in this work and made a coordination to choose the best CHs from among them to achieve a balanced load clustering in WSN. The modified MADM approach is applied to identify the best set of CHs from the available options that can efficiently fulfill the coordination criterion. The distance between the CH and the base station (BS), the distance from a node to CH, the maximum residual energy of CHs, which is an essential factor for cluster load-balanced, and other factors play a significant role in optimal CH selection. The synchronization of these parameters can ensure optimal power utilization by lowering power consumption and balancing the load between nodes and CHs. The experiments show that the synchronization of these twelve criteria produces one of the most exemplary demonstrations for selecting the best CHs.</p>

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An improved approach based on multiple attribute decision making by passing minimum number of relevant parameters for clustering in wireless sensor networks

  • 期刊论文

  • 发表日期：

    2026年6月19日

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  • Lekhraj,
  • Anoj Kumar

摘要

Multiple attribute decision-making (MADM) approaches give an ordinary performance in cluster head (CH) selection of wireless sensor network (WSN). These approaches work with the values of the attributes of the particular domain. In this article, we pass the minimum number of relevant parameters of WSN as an input to the modified MADM approaches to give a better CH set to achieve proper load balancing in WSN. We studied a total of twelve such parameters in this work and made a coordination to choose the best CHs from among them to achieve a balanced load clustering in WSN. The modified MADM approach is applied to identify the best set of CHs from the available options that can efficiently fulfill the coordination criterion. The distance between the CH and the base station (BS), the distance from a node to CH, the maximum residual energy of CHs, which is an essential factor for cluster load-balanced, and other factors play a significant role in optimal CH selection. The synchronization of these parameters can ensure optimal power utilization by lowering power consumption and balancing the load between nodes and CHs. The experiments show that the synchronization of these twelve criteria produces one of the most exemplary demonstrations for selecting the best CHs.