Wireless Sensor Networks (WSNs) are becoming increasingly popular since they can gather information from different locations without wires. This advantage is exploited in applications such as robotic systems, telecare, domotic or smart cities, among others. To gain independence from the electricity grid, WSNs devices are equipped with batteries, therefore their operational time is determined by the time that the batteries can power on the device. As a consequence, engineers must consider low energy consumption as a critical objective to design WSNs. Several approaches can be taken to make efficient use of energy in WSNs, for instance low-duty-cycling sensor networks (LDC-WSN). Based on the LDC-WSNs, we present LOKA, a LOw power Konsumption Algorithm to minimize WSNs energy consumption using different power modes in a sensor mote. The contribution of the work is a novel algorithm called LOKA that implements two duty-cycling mechanisms using the end-device of the ZigBee protocol (of the Application Support Sublayer) and an external microcontroller (Cortex M0+) in order to minimize the energy consumption of a delay tolerant networking. Experiments show that using LOKA, the energy required by the sensor device is reduced to half with respect to the same sensor device without using LOKA.

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Measuring the consumption of electronic devices is a difficult and sensitive task. Data acquisition (DAQ) systems are often used to determine such consumption. In theory, measuring energy consumption is straight forward, just by acquiring current and voltage signals we can determine the consumption. However, a number of issues arise when a fine analysis is required. The main problem is that sampling frequencies have to be high enough to detect variations in the assessed signals over time. In that regard, some popular DAQ systems are based on RISC ARM processors for microcontrollers combined with analog-to-digital converters to meet high-frequency acquisition requirements. The efficient use of direct memory access (DMA) modules combined with pipelined processing in a microcontroller allows to improve the sample rate overcoming the processing time and the internal communication protocol limitations. This paper presents a novel approach for high-frequency energy measurement composed of a DMA rate improvement (data acquisition logic), a data processing logic and a low-cost hardware. The contribution of the paper is the combination of a double-buffered signal acquisition mechanism and an algorithm that computes the device’s energy consumption using parallel data processing. The combination of these elements enables a high-frequency (continuous) energy consumption measurement of an electronic device, improving the accuracy and reducing the cost of existing systems. We have validated our approach by measuring the energy consumed by elemental circuits and wireless sensors networks (WSNs) motes. The results indicate that the energy measurement error is less than 5% and that the proposed method is suitable to measure WSN motes even during sleep cycles, enabling a better characterization of their consumption profile.