基于语境集群的光虫群优化 (GSO) 结合智能城市的无线传感器网络
P S Ramesh1, P Srivani2, Miroslav Mahdal3
1Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology, Chennai 600062, India.
Sensors (Basel, Switzerland)
|July 29, 2023
概括
使用光优化的新型路由方案平衡无线传感器网络 (WSN) 中的能量. 虽然提高了网络寿命,但由于特定的数据包类型和路由路径,它比某些协议的能耗更高.
科学领域:
- 无线传感器网络 (WSN) 是一种无线传感器网络.
- 优化技术 优化技术
- 在沟通中提高能源效率
背景情况:
- 基于集群的路由在WSN中很常见,使用集群头 (CH) 来汇总和传输来自集群成员 (CM) 的数据.
- 现有的CH功能,如路由,压缩和聚合,可能会导致快速耗电,影响网络寿命.
- 需要异质的高功率节点 (HPN) 和改进的算法来平衡能源消耗,特别是在基站附近的CHS.
研究的目的:
- 为WSN提出一个新的路由方案,以提高能源平衡和网络寿命.
- 调查基于集群的光虫优化技术对WSN路由的有效性.
- 在拟议模型中评估网络寿命,能源消耗和吞吐量之间的权衡.
主要方法:
- 使用基于集群的光虫优化技术,涉及随机集群,分布式集群领导者选择和基于链接的路由.
- 在CH实现多节点通信和数据聚合,以减少网络负载和节能.
- 在260节点网络中模拟了拟议的路由方案,以评估吞吐量和能源效率.
主要成果:
- 与标准方法相比,拟议的算法证明了更好的能源利用率和更快的融合速度.
- 该技术通过优化路由和集群构建,成功地平衡了WSN的能源消耗.
- 该模型的能量消耗高于TPGF和其他特定数据包类型的协议 (0或1转发) 由于INFO数据包短且跳数增加.
结论:
- 基于集群的优化和多跳转路由的结合方法有效地延长了WSN网络的寿命,并平衡了能源.
- 虫优化技术在汇聚速度和WSN路由的多参数选择方面具有优势.
- 需要进一步的研究来解决与特定数据包场景的邻居发现和路由路径相关的已识别的能源消耗问题.
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