Wireless sensor networks will suffer severe performance degradation in communication reliability and throughput when interfered by co-located Wifi devices. When multiple sensor networks with different priority are interfered by Wifi devices, it is of great significance to allocate channels according to their priority as well as take into consideration the overall communication reliability and throughput. To address this problem, a channel allocation scheme to mitigate Wifi interference, called EasiCAP (Channel Allocation for wireless sensor networks with Priority) , is presented. The scheme employs an external interference model, which is based on interference signal strength and activity ratio, to measure Wifi interference in each channel of sensor networks. In addition, a receiver-centric interference model is used to gauge internal interference amongst different sensor networks. Based on the measurements of external interference and internal interference, each sensor network independently selects its working channel in real time via alocalized greedy algorithm in order to assign channels according to priority and also reduce the overall interference of all sensor networks as much as possible. Then, the sensor network performs one of the three operations, I. E. , channel keeping, channel swapping, and channel preempting, based on the channel selection decision. Testbed experiments and simulations are conducted to verify the effectiveness of the proposed scheme. The experimental results demonstrate that EasiCAP can provide differentiated communication reliability and throughput corresponding to the network priority. Also, it has higher average communication reliability and throughput than existing schemes. Furthermore, it does not introduce significant overhead.%无线传感器网络(WSN)易受到与其共享信道的无线局域网(Wifi)干扰,造成通信可靠性及吞吐量下降. 当具有不同优先级的多个WSN受到Wifi干扰时,如何按优先级分配信道,并兼顾整体通信可靠性及吞吐量是一个重要问题.针对该问题,作者提出了一种抗Wifi干扰的信道分配机制EasiCAP(Channel Allocation for wireless sensor networks with Priority).该机制利用基于干扰强度和活跃比率的干扰特征模型(External Interference Model,EIM)度量WSN中各信道的Wifi干扰；同时,采用以接收端为中心的模型(Internal Interference Model,ⅡM)度量各WSN之间的干扰.然后,各WSN根据EIM和ⅡM度量的结果,采用局部化贪婪信道分配算法独立、实时地选择信道,通过保持信道、切换信道及抢占信道操作实现按优先级分配信道,并尽可能降低所有网络所受干扰之和.实际测量和仿真结果表明,EasiCAP可为各WSN提供与其优先级相对应的通信可靠性和吞吐量；而且该机制下的平均通信可靠性及吞吐量也比现有方法高.此外,EasiCAP未带来过大的开销.
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