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<p>The Wireless Sensor Network (WSN) is developing technology for various communication to access different services in sensor medium. WSN provides edge services and communication in the fastest data delivery to make speed and effective communication. The main problem is that unbalanced energy constraints take more optimality in bandwidth consideration to break the communication link and reduce the lifetime. To resolve this problem, a Proactive Self-Scheduling Energy Balancing Routing Approach (PSSEBRA) is applied to select the strong communication link to progress the lifetime maximization of the network. The Node Response Communication Rate (NRCR) is initially estimated based on the behavior node performance ratio. Then, the Transition Flow Intake Energy Consumption and Traffic Intensity (TFIEC-TI) is estimated by utilizing marginal feature limits. Cluster Control Fragmentation Routing (CCFR) is applied to enrich the routing corporation to find the best routes from the feature-supportive measures. Finally, the Proactive Self-Scheduling Energy Balancing Routing Approach (PSS-EBRA) is applied to select the strong communication link to expand the lifetime maximization of the network. The proposed system achieves a higher energy balancing performance rate, optimized lower latency, throughput, and lower bandwidth consideration to deliver data transfer speed as well compared to the other routing approach. The proposed simulation achieves a throughput of 366kbps, a Packet Delivery Ratio (PDR) performance of 93%, and a network lifetime of 92%. The enhanced level improves the communication in a better standalone to increase the path performance.</p>

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Proactive Self-Scheduling Energy Balancing Routing Approach Based Lifetime Maximization Using Cluster Control Fragmentation in WSN

  • 期刊论文

  • 发表日期：

    2025年6月14日

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  • Sangeetha Dharmapuri Patel,
  • Shivakumar Rangasamy

摘要

The Wireless Sensor Network (WSN) is developing technology for various communication to access different services in sensor medium. WSN provides edge services and communication in the fastest data delivery to make speed and effective communication. The main problem is that unbalanced energy constraints take more optimality in bandwidth consideration to break the communication link and reduce the lifetime. To resolve this problem, a Proactive Self-Scheduling Energy Balancing Routing Approach (PSSEBRA) is applied to select the strong communication link to progress the lifetime maximization of the network. The Node Response Communication Rate (NRCR) is initially estimated based on the behavior node performance ratio. Then, the Transition Flow Intake Energy Consumption and Traffic Intensity (TFIEC-TI) is estimated by utilizing marginal feature limits. Cluster Control Fragmentation Routing (CCFR) is applied to enrich the routing corporation to find the best routes from the feature-supportive measures. Finally, the Proactive Self-Scheduling Energy Balancing Routing Approach (PSS-EBRA) is applied to select the strong communication link to expand the lifetime maximization of the network. The proposed system achieves a higher energy balancing performance rate, optimized lower latency, throughput, and lower bandwidth consideration to deliver data transfer speed as well compared to the other routing approach. The proposed simulation achieves a throughput of 366kbps, a Packet Delivery Ratio (PDR) performance of 93%, and a network lifetime of 92%. The enhanced level improves the communication in a better standalone to increase the path performance.