Post-processing in wireless sensor networks: Benchmarking sensor trace files for in-network data aggregation

Wireless sensor network research usually focuses on the reliable and efficient collection of data. In this paper we target on the next step in the lifetime of traces: we aim at investigating and evaluating, by qualitative and quantitative means, data repositories of already collected measurements. Concerning the collected datasets, several important topics arise like the need of exchanging traces between researchers using a common representation of the traces and the need for common classification of the traces based on a commonly agreed set of statistical characteristics for in retrospect utilization. In order to qualitatively address these issues, we propose the use of a novel set of metrics focusing on the in-network data-aggregation problem class. These metrics enable reliable evaluation of algorithms using the same benchmark traces (both in average cases and ''stressful'' setups) removing the need for running algorithms in a real testbed, at least in the initial development stage. We present the results of our research as a first approach for addressing this problem, and in order to confirm our method, we characterized several traces with the proposed metrics. We validate the metrics by predicting the performance of three data-aggregation schemes using the available traces and checking the results by actually running the algorithms.