DDRLD:支持局部扩散的定向扩散算法

DDRLD:directed diffusion routing supporting local detection for WSN

在定向扩散协议中,中间节点以泛洪的机制向网络中的所有邻居节点转发接收到的兴趣报文,导致网络能源的浪费。为此,提出一种支持局部扩散的定向扩散算法DDRLD。它通过设置梯度扩散深度阈值,缩小了兴趣报文扩散的范围,降低了网络中传输的数据量;通过设置节点剩余能量门限值,增加了每个节点被选取为转发节点的概率,延长了节点的平均工作时间,改善了网络负载平衡。仿真结果表明DDRLD大大缩短了数据报文端到端的平均延迟,降低了网络功耗,增加了网络生存时间。

In the directed diffusion routing protocol, the intermediate nodes retransmit their received interest message to all of the neighbor nodes by flooding, which can bring about great power consumption to the network. This paper proposed a wireless sensor network data aggregation algorithm called directed diffusion routing supporting local detection（DDRLD）. Firstly intro- duced the background of the research, then provided the analysis of DD, and pointed out the disadvantages of DD and to avoid the disadvantages, proposed DDRLD, in which by setting the maximum gradient diffusion depth and the minimum node remai- ning energy, the times for each node to retransmit interest message at the propagation stage were optimized. It focused on the simulation and the results analysis. The simulation results indicate that DDRLD greatly cuts down the average end-to-end delay of data message, reduces network power consumption and prolongs the network lifetime.