基于灰预测模型的蓝牙网络切换算法

蓝牙网络接入点切换问题是构建蓝牙网络必须考虑的关键问题,而蓝牙特点给接入点切换的实现带来了极大挑战。提出了一种基于灰预测模型的蓝牙网络切换算法,该算法对链路质量信息的数量和分布特征没有苛刻要求,仅用少量样本数据就可以预测出下一时间链路质量,当预测值低于阈值时,接入点搜索网络拓扑结构找出最佳接入点集合,并实时监测切换终端与集合中接入点之间链路质量,预测出下一时刻链路质量,当切换终端链路质量预测值低于另一阈值时,接入点选择最佳接入集合中预测值最佳的接入点完成切换。该算法预测过程可以动态地调整参数,实现自适应预测,提高了预测的精度。仿真结果表明,使用该算法减少了终端切换时延以及误切换概率。

A Handoff Algorithm Based on Grey Prediction Model for Bluetooth Network

The handoff for Bluetooth network access points was a critical problem in constructing a bluetooth network.Special characteristics of bluetooth technology brought great challenges in implementing fast handoff of access points.A handoff algorithm based on grey prediction model for bluetooth network was proposed.The algorithm did not have strict requirements on the quantity and distribution characteristics of samples and needed only a few samples for prediction and made handoff decision.When the predicted value was less than a threshold,the access point searched for an optimal access points set.Then the access point supervised the link quality between the handoff terminal and the access points of the set in real time,and predicted the link quality of next time.When the predicted link quality of the handoff terminal was less than another threshold,the access point selected the optimal access point of the set according to the predicted link quality and finished the handoff procedure.A self-adaptive prediction was implemented to promote the accuracy of predicted results by using of adjusting parameters dynamically.Simulation results show that the handoff delay and probability of inaccuracy handoff has been reduced by using the algorithm.