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Generally, for all computing systems (from embedded hand-held systems to large supercomputers), memory systems primarily dictate power consumption, application performance, and reliability.
The MCIoT system performance is estimated in terms of the normalized energy consumption, application execution time, and QoS satisfaction probability under various offered computation loads.
Then, considering power consumption, application quality of service (QoS) profiles, and corresponding cost functions, a multi-objective optimization approach using an event-based finite state model and dynamic constraint programming method has been used to determine the appropriate transmission power, process power, cloud offloading and optimum QoS profiles.
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Tunneling field-effect transistor (TFET) has become a kind of potential electric device for the ultralow power consumption applications [1 3].
LTE/4G is delivered as a silicon component called a baseband modem that pushes SoC designers to the limits of innovation to design and fabricate for low-power consumption applications, such as mobile devices.
Low power consumption applications like for the ROSITA X-ray astronomy mission with low frame rates of, e.g. 20 images/s, as well as high frame rate applications, e.g. 200 images/s, are possible with the same device.
Due to its simplicity and low power, this data processing system is especially suitable for portable applications, reducing the disadvantage of FPGAs against ASICS in low power consumption applications [A. Amara, F. Amiel, T. Ea, FPGA vs. ASIC for low power applications, Microelectronics Journal 37 (8) (2006) 669 677].
Using a low energy-consumption application, we have used the smartphones inertial sensor as an accelerograph.
Another approach to achieve configurability without sacrificing power consumption is to use application specific instruction-set processors (ASIP) [2 4].
It has been widely utilized in WSN applications since it is designed for low data rate, short distance and low-power-consumption applications in conformity with the constraints of WSN systems [10].
In this subsection, we use Application Energy Graphing Tool[40], which can measure the battery power consumption of an application over time, log and graph the resulting data.
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