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<p>Scheduling and routing problems for maximizing the lifetime of wireless sensor networks (WSN) have been well studied. WSNs provide many previously described algorithms to support lifetime maximization and node scheduling. However, it is difficult to achieve a higher performance to maximize the lifetime of sensor nodes. Among these, the additive weight-based dynamic scheduling algorithm (HAWDS) adjusts the weights according to the average queue size and adaptively changes the weights of the scheduling scheme in a manner that favours premium services. This study explores an active queue buffer management technique for efficiently handling the cluster head (CH) buffer queues. This approach involves dynamically allocating the CH buffer size to neighboring nodes based on the quantity of received packets, thereby mitigating the risk of packet loss. Additionally, this research examines the Acknowledgement encounter strategy, which evaluates two methods of acknowledgment delivery: explicit and implicit. Substantial advancements were observed across all evaluation criteria. The study revealed a 42% increase in the packet delivery ratio (PDR), an 87% enhancement in throughput, and an 86% improvement in scheduling effectiveness. The proposed framework outperformed MCAR in terms of energy efficiency by 13.33% and extended network durability to 98%, exceeding DHRP by 4.87% and EEBS by 8.86%. Illustrating its effectiveness, the proposed method delivered outstanding results: 98.4% PDR, 8300 packets throughput, 98% scheduling efficiency, and 98% network durability. These metrics highlight the superior performance and operational excellence of the framework.</p>

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A Novel Predict Earliest Finish Time Algorithm with Flower Pollination Algorithm for Effective Communication in Ad-Hoc Network

  • 期刊论文

  • 发表日期：

    2025年4月29日

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  • A. Manikandan,
  • G. C. Madhu,
  • Chandrasekar Venkatachalam,
  • S. Ramalingam,
  • M. Baritha Begum,
  • S. Gnanamurugan

摘要

Scheduling and routing problems for maximizing the lifetime of wireless sensor networks (WSN) have been well studied. WSNs provide many previously described algorithms to support lifetime maximization and node scheduling. However, it is difficult to achieve a higher performance to maximize the lifetime of sensor nodes. Among these, the additive weight-based dynamic scheduling algorithm (HAWDS) adjusts the weights according to the average queue size and adaptively changes the weights of the scheduling scheme in a manner that favours premium services. This study explores an active queue buffer management technique for efficiently handling the cluster head (CH) buffer queues. This approach involves dynamically allocating the CH buffer size to neighboring nodes based on the quantity of received packets, thereby mitigating the risk of packet loss. Additionally, this research examines the Acknowledgement encounter strategy, which evaluates two methods of acknowledgment delivery: explicit and implicit. Substantial advancements were observed across all evaluation criteria. The study revealed a 42% increase in the packet delivery ratio (PDR), an 87% enhancement in throughput, and an 86% improvement in scheduling effectiveness. The proposed framework outperformed MCAR in terms of energy efficiency by 13.33% and extended network durability to 98%, exceeding DHRP by 4.87% and EEBS by 8.86%. Illustrating its effectiveness, the proposed method delivered outstanding results: 98.4% PDR, 8300 packets throughput, 98% scheduling efficiency, and 98% network durability. These metrics highlight the superior performance and operational excellence of the framework.