• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Industrial Informatics, IEEE Transactions on >Efficient Route Update and Maintenance for Reliable Routing in Large-Scale Sensor Networks
【24h】

Efficient Route Update and Maintenance for Reliable Routing in Large-Scale Sensor Networks

机译：大型传感器网络中有效路由更新和维护，以实现可靠路由

获取原文
获取原文并翻译 | 示例
       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Reliable data transmissions are challenging in industrial wireless sensor networks as channel conditions change over time. Rapid changes in channel conditions require accurate estimation of the routing path performance and timely update of the routing information. However, this is not well fulfilled in existing routing approaches. Addressing this problem, this paper presents combined global and local update processes for efficient route update and maintenance, and incorporates them with a hierarchical proactive routing framework. While the global process updates the routing path with a relatively long period, the local process with a shorter period checks potential routing path problems. A theoretical modeling is developed to describe the processes. Through simulations, the presented approach is shown to reduce end-to-end delay up to 30 times for large networks, while improving packet reception ratio (PRR) in comparison with hierarchical and proactive routing protocols ROL/NDC, DSDV, and DSDV with IPv6 Routing Protocol for Low-Power and Lossy Networks’ Trickle algorithm. Compared with reactive routing protocols AODV and Ad Hoc On-demand Multipath Distance Vector, it provides similar PRR while reducing end-to-end delay over 15 times.
机译：在工业无线传感器网络中，可靠的数据传输面临挑战，因为信道条件会随着时间而变化。信道条件的快速变化要求对路由路径性能进行准确估计，并及时更新路由信息。但是，这在现有的路由方法中不能很好地实现。为了解决这个问题，本文提出了组合的全局和本地更新过程，以进行有效的路由更新和维护，并将它们与分层的​​主动路由框架结合在一起。全局进程以相对较长的时间更新路由路径时，而较短周期的本地进程则检查潜在的路由路径问题。建立了理论模型来描述过程。通过仿真，所展示的方法可以将大型网络的端到端延迟降低多达30倍，同时与采用IPv6的分层和主动路由协议ROL / NDC，DSDV和DSDV相比，可以提高数据包接收率（PRR）低功耗有损网络的Tri流算法的路由协议。与反应式路由协议AODV和Ad Hoc按需多路径距离矢量相比，它提供了相似的PRR，同时减少了15倍的端到端延迟。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号