Accurate Power Consumption Evaluation for Peripherals in Ultra Low-Power embedded systems

Abstract

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Cost-optimal timed trace synthesis for scheduling of intermittent embedded systems

“…The embedded energy model is based on measurements (see section 7.1) at the platform level: it is not limited to the activities of the CPU. It is close to the work of Berthou et al [16] but we do not assume the integration of a regulator so the supply voltage is not constant.…”

“…To enable the development of higher-level models, power measurement platforms have been developed [15,16]. These platforms are mainly based on current measurement in order to measure the energy consumption of the system and its different modules.…”

Estimating Overhead Performance of Supervised Machine Learning Algorithms for Intrusion Detection

“…This study estimates the energy used by both the CPU and the DRAM memory and energy usage. Moreover, Berthou et al (2020) performed a simulating to estimate the power consumption of peripheral devices for a low-power embedded micro-controller. The method was tested using the low-power MSP-EXP430FR5739 platform, which had a few peripherals and nonvolatile RAM for inconsistent processing demands.…”

Energy Harvesting Techniques for Internet of Things (IoT)

“…Several strategies have been proposed for prolonging the lifetime of wireless IoT devices, including duty-cycling [104], sleep scheduling [105], the reduction of the required transmission distance for IoT devices through efficient clustering [106], optimized strategies for adaptively setting the rates of sensor reading and data transmission depending on available energy [107], or the development of scheduling schemes that take into account power consumption when waking up the wireless sensing systems [108]. Some practical techniques for reducing the energy required by an IoT device, also used in the development of low-power embedded systems, include Dynamic Voltage Scaling (DVS) [109], the reduction of the frequency of the processing unit [110], or the appropriate selection of peripherals in the device [111] or of the type of memory involved in data processing and storage (i.e., Flash or RAM -Random access memory) [112], the adaptation of transmission power depending on required communication range and environment [113,114], or logic for deciding the moment and format for sending slow varying data [115 -117]. All these approaches for assuring low-power operation must be scheduled and further modified depending also on the amount of energy that is generated or stored by the IoT device at each moment in time [50].…”