计算机应用研究
計算機應用研究
계산궤응용연구
APPLICATION RESEARCH OF COMPUTERS
2015年
9期
2737-2741
,共5页
贺然%张钢%刘春凤%舒炎泰
賀然%張鋼%劉春鳳%舒炎泰
하연%장강%류춘봉%서염태
车辆自组织网络%邻居发现%移动预测%卡尔曼滤波
車輛自組織網絡%鄰居髮現%移動預測%卡爾曼濾波
차량자조직망락%린거발현%이동예측%잡이만려파
VANET%neighbor discovery%mobility prediction%Kalman filter
车辆网络中节点的快速移动导致网络拓扑频繁变化,快速的邻居发现算法成为影响网络协议性能的重要因素。针对该问题,提出了一种新型的基于卡尔曼滤波器移动轨迹预测的Hello协议,即KFH (Kalman filter-based Hello protocol)。每个节点使用一个基于自适应卡尔曼滤波器的预测模型来预测自己的运动轨迹,当节点预测下一个时隙的位置时,同时也对邻居表中的每个邻居进行预测。如果节点的位置预测精度大于一定的阈值,将广播一个包含自己真实位置的hello消息,接收到该探测信息的节点将更新自己邻居表中相应的模型参数。仿真结果表明,KFH可以实现高效率的邻居发现,提高Hello协议的性能。在同样网络开销情况下,KFH具有最低的邻居发现错误率(只有2%)及邻居发现延迟。
車輛網絡中節點的快速移動導緻網絡拓撲頻繁變化,快速的鄰居髮現算法成為影響網絡協議性能的重要因素。針對該問題,提齣瞭一種新型的基于卡爾曼濾波器移動軌跡預測的Hello協議,即KFH (Kalman filter-based Hello protocol)。每箇節點使用一箇基于自適應卡爾曼濾波器的預測模型來預測自己的運動軌跡,噹節點預測下一箇時隙的位置時,同時也對鄰居錶中的每箇鄰居進行預測。如果節點的位置預測精度大于一定的閾值,將廣播一箇包含自己真實位置的hello消息,接收到該探測信息的節點將更新自己鄰居錶中相應的模型參數。倣真結果錶明,KFH可以實現高效率的鄰居髮現,提高Hello協議的性能。在同樣網絡開銷情況下,KFH具有最低的鄰居髮現錯誤率(隻有2%)及鄰居髮現延遲。
차량망락중절점적쾌속이동도치망락탁복빈번변화,쾌속적린거발현산법성위영향망락협의성능적중요인소。침대해문제,제출료일충신형적기우잡이만려파기이동궤적예측적Hello협의,즉KFH (Kalman filter-based Hello protocol)。매개절점사용일개기우자괄응잡이만려파기적예측모형래예측자기적운동궤적,당절점예측하일개시극적위치시,동시야대린거표중적매개린거진행예측。여과절점적위치예측정도대우일정적역치,장엄파일개포함자기진실위치적hello소식,접수도해탐측신식적절점장경신자기린거표중상응적모형삼수。방진결과표명,KFH가이실현고효솔적린거발현,제고Hello협의적성능。재동양망락개소정황하,KFH구유최저적린거발현착오솔(지유2%)급린거발현연지。
In vehicular Ad hoc networks,the rapid moving of nodes leads to the frequent changes of network topology.A fast neighbor discovery algorithm has become an important factor influencing the performance of network protocols.This paper pro-posed a novel mobility prediction Hello protocol based on adaptive Kalman filter,named KFH (Kalman filter-based Hello pro-tocol).Each node used a predict model based on adaptive Kalman filter to make mobility prediction for itself.When a node predicted its own position of the next slot,it also made position prediction for each neighbors in the neighbor table.If the pre-diction error was bigger than a preset threshold,a hello message contained the real position of the node would be broadcasted and neighbors received the message would update the corresponding parameters of predict model.Simulation results show that KFH achieves a higher efficient neighbor discovery and improves the performance of Hello protocol.KFH reaches the lowest neighbor error rate (only about 2%)and the shortest neighbor discovery delay under the same network overhead.