Characterization of Traffic in Wireless Sensor Networks

We present an analysis of traffic collected from different topologies of wireless sensor networks. Specifically, over 2.1 million packets were analyzed from two different and commonly used network topologies, namely a direct connection to a base station and a daisy-chained connection to the base. The data traffic between the nodes was captured over a composite period of 180 hours. Using the captured information, analysis was performed to categorize and identify the information through anomalies and variations of traffic patterns. Data was also be analyzed for self-similarity and statistical distribution. The results have shown that by monitoring the traffic distribution and types of message sent, traffic analysis is able to distinguish between the two topology setups. The status of the nodes can also be determined with the traffic collected. Examples include new nodes joining the network and operational status of the nodes. Statistical analysis has also been done and found that wireless sensor network traffic is not self-similar except for the interarrival time of the direct connection mode.