中文摘要：

高斯-马尔科夫移动模型（GM模型）是一种比较符合现实场景的节点运动模型，但是GM模型参数选择复杂，如果参数选择不当，移动节点会超出仿真区域，进而影响模型的性能。本文对GM模型的参数进行了仿真分析，结果表明初始速度对节点的超界率和覆盖率影响不大，而随着仪值的增大，节点超界率增大，覆盖率呈先增大后减小的趋势；随着边界阈值入的增大，超界率减小，但覆盖率也减小。在实际应用中，应当确保超界率在可接受范围之内的前提下，尽量提高节点的覆盖率。

英文摘要：

Gauss-Markov mobility model（GM model） is extremely suitable to model the characteris- tics of the node＇ s motions in real-world environments or scenarios. However, complex parameter selection exists in GM model. If the parameter selection is improper, node will beyond the boundary, which will in- duce a bad effect on the performance of the model. Research results of parameter characteristics show that the initial velocity value has little influence on the probability of out-boundary as well as the coverage rate. With α value increasing, the node out-boundary probability increases. The coverage rate of node in the simulation area first increases and then decreases. With border threshold 3, increasing, the node out-bound- ary probability and the coverage rate decrease. In practical application, the coverage rate of a node should be improved as much as possible after ensuring that out-boundary rate is in the acceptable range.