混合型信息系统的邻域粗糙集模型动态更新算法

Dynamic updating algorithm of neighborhood rough set model for hybrid information system

针对实际应用中混合型信息系统不断动态变化的情形,提出一种邻域粗糙集模型的动态更新算法.首先针对邻域粗糙集中对象邻域类的计算,文中将信息系统论域构造出一个对象子集族,然后利用该对象子集族可以快速地计算对象的邻域类,并用于论域增加后邻域类的增量式更新,从而进一步地动态更新邻域粗糙集的上下近似集,最后给出了相应的邻域粗糙集动态更新算法.通过实验分析证明了该算法的有效性和优越性.

Aiming at the threshold collusion and probabilistic connectivity problems in the process of wireless sensor network(WSN)key pre-distribution,an scheme based on matrix eigenvector(EBSC)is proposed.By using a generating matrix A,2N secret matrices can be dynamically generated according to the different types of application nodes.The problem of threshold collusion in classical BLOM scheme and probabilistic connectivity in probabilistic is sloved.Full connectivity of WSN network(that is,any two nodes in the network can communicate directly)can be realized.Moreover,utilizing the properties of eigenvalues and eigenvectors in the EBSC scheme,a single authentication is used in the application of nodes,which greatly improves the security performance of the network.The comparison analysis shows that the new scheme has advantages in node storage,computation and network communication energy consumption.Especially,in the case of large network updates,the new scheme can realize the whole network updates of scale N by simple assignment operation and lightweight communication consumption,avoiding complex matrix expansion operation.This shows that EBSC algorithm is more suitable for energyconstrained WSN networks.