A Weighted Moving Average-based Approach for Cleaning Sensor Data

Nowadays, wireless sensor networks have been widely used in many monitoring applications. Due to the low quality of sensors and random effects of the environment, however, it is well known that the collected sensor data usually contain noises. Therefore, it is very critical to clean the sensor data before using them to answer queries or conduct data analysis. Popular data cleaning approaches, such as moving average, cannot meet the requirements of both energy efficiency and quick response time in many sensor related applications. In this paper, we propose a hybrid sensor data cleaning approach with confidence. Specifically, we propose a smart weighted moving average (WMA) algorithm that collects confident data from sensors and computes the weighted moving average. The rationale behind the WMA algorithm is to draw more samples for a particular value that is of great importance to the moving average, and provide a higher confidence weight for this value, such that this important va...

• Type: Conference
• Year: 2007
• Where: ICDCS
• Authors: Yongzhen Zhuang, Lei Chen 0002, Xiaoyang Sean Wang, Jie Lian
• Keywords: Distributed And Parallel Computing, ICDCS 2007, Moving Average, Sensor Data, Sensors