智能楼宇网络中冗余信息并行采集方法仿真  

Simulation of Redundant Information Parallel Acquisition Method in Intelligent Building Network

作　　者：郑恒河 ZHENG Heng-he(Jining University,Qufu Shandong 273155 China)

机构地区：[1]济宁学院

出　　处：《计算机仿真》2019年第6期455-458,共4页Computer Simulation

摘　　要：针对当前方法进行智能楼宇网络中冗余信息并行采集时,普遍存在着采集时间代价较大、错误率较高、成本耗费较大等问题。提出基于云计算的网络中冗余信息并行采集方法。为获取智能楼宇网络中的冗余信息,对整个楼宇网络冗余信息集合进行划分,获得若干个相同几何大小的子空间格;利用K近邻算法对各子空间格内的楼宇网络冗余信息记录进行搜索,得到智能楼宇网络冗余信息的部分拓扑数据,完成冗余信息的特征提取,构建网络冗余信息处理模型,获取样本信息特征矢量,将冗余信息特征和正常信息特征进行比较,引入云计算方法对网络中冗余信息进行采集。实验结果表明,所提出方法在智能楼宇网络中冗余信息并行采集时,能够有效提高采集过程中时间代价、降低错误率,减少一定的成本耗费。When the current method was used to collect redundant information in intelligent building network,the collection time cost and error rate were high.Therefore,a method to parallel collect redundant information based on cloud computing was proposed.In order to obtain redundant information in intelligent building network,the set of building network redundancy information was divided to get several Subspace lattices with the same geometrical size.K-nearest neighbor algorithm was used to search record the redundant information record of building network in each subspace lattice,so as to obtain partial topology data of intelligent building network redundancy information.Thus,the feature extraction of redundancy information was completed.Moreover,network redundant information processing model was constructed to obtain sample information feature vectors.Finally,redundant information features were compared with normal information features,and the cloud computing method was introduced to collect the redundant information in network.Simulation results show that the proposed method can effectively improve the time cost,reduce the error rate and the cost during parallel collection of redundant information in intelligent building network.

关 键 词：目标网络 冗余信息 采集 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]