The ability to precisely measure and compare energy consumption and relate this to particular parts of programs is a recurring theme in sensor network research. This paper presents the Energy Bucket, a low-cost tool designed for quick empirical measurements of energy consumptions across 5 decades of current draw. The Energy Bucket provides a light-weight state API for the target system, which facilitates easy scorekeeping of energy consumption between different parts of a target program. We demonstrate how this tool can be used to discover programming errors and debug sensor network applications. Furthermore, we show how this tool, together with the target system API, offers a very detailed analysis of where energy is spent in an application, which proves to be very useful when comparing alternative implementations or validating theoretical energy consumption models.

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Given the large and sustained growth in the number of smart meters for different applications, e.g., electricity, water, heat, effective data compression has become increasingly important. Although smart meters tend to encrypt payloads using state-of-the-art solutions, the packet length variability introduced by compression of the data can be exploited in a side channel attack to gain knowledge about the consumption of individual meters. In a nutshell, a meter reporting zero (or constant) consumption can be compressed more than one reporting more erratic consumption. An attacker may gain knowledge of behavioral patterns of a household, e.g., when is no one home, or company, e.g., active periods of production. This paper analyzes the correlation between packet length and reported consumption of several signals and practical reporting periods for the DLMS standard using real (anonymized) smart meter measurements. We consider various built-in compressors and also propose new techniques that can both increase the compression and reduce this correlation. Our proposed schemes are particularly well suited for the increasingly popular case of high frequency reporting, e.g., reporting each measurement as it becomes available.

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