计算机工程与应用 ›› 2018, Vol. 54 ›› Issue (3): 87-93.DOI: 10.3778/j.issn.1002-8331.1608-0366

• 网络、通信与安全 • 上一篇    下一篇

基于概率优化的水下通道感知能量优化路由

万智萍   

  1. 中山大学 新华学院,广州 510520
  • 出版日期:2018-02-01 发布日期:2018-02-07

Underwater channel sensing energy optimization routing based on probabilistic optimization

WAN Zhiping   

  1. Xinhua College of Sun Yat-Sen University, Guangzhou 510520, China
  • Online:2018-02-01 Published:2018-02-07

摘要: 针对水下传感器网络能量损耗较大,延迟较严重的问题,提出一种基于概率优化的水下通道感知能量优化路由(PPUN)。在能量优化上,针对水下节点随机覆盖存在的多余感测覆盖范围所造成的额外能量损耗问题,采用传感器节点数量的概率优化方法,在保证覆盖率和节点连通率的情况下推导出网络所需要的最小节点数目,从减少传感器数目的问题上来优化总体能量。而针对路由的能量损耗问题,在节点的链路规划上采用了通道感知路由算法,考虑了在一定能量损耗阈值条件下的最短节点路径,避免水下节点盲目选择能量损耗较大的最短路径而导致数据转发失败,消耗更多能量。延迟问题抓住主要的解码延迟问题进行了分析并利用HARQ-III方案对延迟时间加以控制。实验对比分析表明,算法采取控制传感器数目和链路规划的方法,在实现能量优化上具有一定优势,延迟控制方案也得到了较好的效果。

关键词: 水下传感器网络, 概率优化, 通道感知路由, 能量优化, 延迟控制

Abstract: For the problems about energy loss is large and delay to more serious in underwater sensor networks, a underwater channel sensing energy optimization routing based on probabilistic optimization is proposed(PPUN). On energy optimization, for additional energy loss problem caused by redundant sensing coverage, a probabilistic optimization method about the number of sensor nodes is used, which can ensure to meet the case of coverage and node connectivity rate to derive the minimum number of required network nodes and reduce the number of sensors to optimize the overall energy. For the energy loss problem of route, a channel-aware routing algorithm on the nodes link planning is used, considering the shortest node path under a certain energy loss threshold, it is necessary to avoid the shortest path of blind selection of the greater energy loss by underwater node which causes data forwarding fails and consume more energy. On the latency issues, using the main decoding delay problem, HARQ-III program is analyzed and used to control delay time. Experimental comparative analysis shows that the algorithm adopts the method of controlling sensor number and link planning, it has certain advantages in achieving energy optimization and the delay control scheme has also been good results.

Key words: underwater sensor networks, probabilistic optimization, channel-aware routing, energy optimization, delay control