Abstract:
Missing value of sensory data often occurs in Wireless Sensor Networks(WSN). This paper proposes a distributed algorithm named SC, which consists of two approaches named SRS and CNI. The algorithm SC chooses CNI or SRS dynamically according to the number of child node of current node. The theory analysis shows that SC does not increase extra energy. Simulation results show that SC can get perfect accuracy and adaptability in different topology.
Key words:
Wireless Sensor Networks(WSN),
missing value,
estimation approach
摘要: 针对无线传感器网络中经常存在的感知数据缺失的问题,提出一个分布式算法SC,其中包括2种缺失数据估计的方法,即SRS和CNI。算法SC根据当前节点的子节点数对SRS和CNI进行动态选择。理论分析表明,SC不增加额外的通信能量消耗。模拟实验结果表明,SC对缺失数据的估计具有较好的准确性,对于不同的拓扑结构有较好的适应性。
关键词:
传感器网络,
缺失数据,
估计方法
CLC Number:
FU Hui-Juan, LIN Mei-Rui, LI Jin-Bao, GUO Long-Jiang. Missing Value Estimation in Wireless Sensor Networks[J]. Computer Engineering, 2011, 37(01): 90-92.
付惠娟, 任美睿, 李金宝, 郭龙江. 无线传感器网络中缺失数据的估计[J]. 计算机工程, 2011, 37(01): 90-92.