This paper proposes a probabilistic routing method with traffic density awareness ability—ECRF. ECRF uses random forwarding to select equal neighbors or near neighbors as the next-hop node of the messages with certain probability, therefore providing randomness to routing paths.
本文从分析反向追踪数据包定位源节点的攻击模式出发,提出了一种结合了流量密度感知能力的概率路由算法(ECRF),它利用随机转发策略以一定的概率选择等邻居节点或近邻居节点作为数据包的下一跳节点,增加路由路径的随机性。
参考来源 - 无线传感器网络源位置保护策略研究·2,447,543篇论文数据，部分数据来源于NoteExpress
蔓延路由和概率路由能提供较高的报文投递率，较小的投递延迟，但是开销很大。
Epidemic routing and Probabilistic routing can provide higher delivery probability and reducing delays, they cost too much network traffics.
图15 .通过较大近缓存或者关联路由，逐渐增加近缓存命中的概率，可以减少平均数据访问时间。
Figure 15. Increasing the probability of a near-cache hit, either through larger near caches or affinity routing, reduces the average data access time.
计算数据表明，采用递减转发概率将使得重路由路径长度的期望值显著降低，因而能保证良好的通信延时。
The calculation result demonstrates that descending forward probability makes the expected value of rerouting path decrease distinctly, therefore limits the communication delay.
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