无线传感器网络中的节点关联规则挖掘

信息处理是无线传感器网络的核心技术,必须采取简单、高效的处理策略.本文通过对传统Apriori算法的改进,提出了一种节点关联规则挖掘方法来发现大量节点之间的有用关联或相关联系,以此消除节点之间信息的冗余.这种方法可以帮助用户对数据进行有效的融合、分类、查询、分析、理解和决策.仿真结果表明该方法能够有效减少信息处理中通信和计算所消耗的能量,缩短数据查询响应的时间,从而延长整个网络的寿命.

Node Association Rule Mining in Wireless Sensor Networks

Information processing is the main issue of wireless sensor networks, which is attracting more and more attention recently. Based on modified Apriori algorithm, this paper proposes a novel node association rule mining algorithm for exploiting the inherent correlations between sensor readings. This approach can help users to manage data efficiently during aggregation, classification, prediction, query, understanding and decision-making. The simulation results show that the proposed method can reduce computation and communication energy in information processing effectively, shorten data query response time and then prolong the network lifetime.