InDP: In-Network Data Processing for Wireless Sensor Networks

Wireless sensor networks have emerged as an important information collection and monitoring tool. The data collected is typically uploaded to a central gateway for processing and analysis. However, the approach of forwarding all the sensed data to a sink for processing is not always practical due to the high communication cost. In this paper, we present InDP, a framework that is designed to support data dissemination and processing in the edge. InDP has a communication component and a computation component. The communication component supports a low duty cycle mode for an infrequent status update and a high throughput mode to support distributed computation. The computation component implements a distributed version of Principal Component Analysis (PCA). As an application, we have implemented an outlier detection component over InDP. InDP and the outlier detection application have been implemented on Contiki using a modified version of Codecast as the underlying many-to-many communication protocol. Our evaluations show that InDP can terminate as fast as 100ms and 1.3s on the average running on a testbed with more than 70 nodes. In terms of PCA computation, InDP's computation uses 91.6% less data than a centralized approach and is able to detect anomalies using a fraction of the sensed data.