The trade-off between the centralized and mobile edge-based cloud solutions for IoT applications

2021 ◽  
Author(s):  
Tianru Li ◽  
Zhili Sun ◽  
Haitham Cruickshank
Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 904 ◽  
Author(s):  
Adnan Sabovic ◽  
Carmen Delgado ◽  
Dragan Subotic ◽  
Bart Jooris ◽  
Eli De Poorter ◽  
...  

Billions of Internet of Things (IoT) devices rely on batteries as the main power source. These batteries are short-lived, bulky and harmful to the environment. Battery-less devices provide a promising alternative for a sustainable IoT, where energy harvested from the environment is stored in small capacitors. This constrained energy storage and the unpredictable energy harvested result in intermittent on–off behavior of the device. Measuring and understanding the current consumption and execution time of different tasks of IoT applications is crucial to properly operate these battery-less devices. In this paper, we study how to properly schedule sensing and transmission tasks on a battery-less LoRaWAN device. We analyze the trade-off between sleeping and allowing the device to turn off between the execution of application tasks. This study allows us to properly define the device configuration (i.e., capacitor size) based on the application tasks (i.e., sensing and sending) and environmental conditions (i.e., harvesting rate). We define an optimization problem that determines the optimal capacitor voltage at which the device should start performing its tasks. Our results show that a device using LoRaWAN Class A can measure the temperature and transmit its data at least once every 5 s if it can harvest at least 10 mA of current and uses a relatively small capacitor of 10 mF or less. At harvesting rates below 3 mA, it is necessary to turn off the device between application cycles and use a larger supercapacitor of at least 140 mF. In this case, the device can transmit a temperature measurement once every 60–100 s.


2018 ◽  
Vol 6 ◽  
pp. 55-62 ◽  
Author(s):  
Carlos Couso ◽  
Javier Martin-Martinez ◽  
Marc Porti ◽  
Montserrat Nafria

2018 ◽  
Vol 13 (3) ◽  
pp. 1-8
Author(s):  
Felipe Makara ◽  
Lucas Mangini da Silva ◽  
Luis Henrique Assumpção Lolis ◽  
Andre Mariano

In this paper, an energy-efficient SAR ADC for IoT applications is presented. The proposed ADC relies on a built-in calibration circuit to improve accuracy and introduces an original DAC that merges the concepts of binary-weighted and C/2C arrays in order to achieve a favorable trade-off between area, accuracy and power consumption. The system consumes 58 µW per conversion cycle sampling at a frequency of 6.66 MHz with an SNDR of 49.78 dB for a 1MHz input signal. With an ENOB of 8 bits, the resulting FOM is 34fJ/conversion-step.


2013 ◽  
Vol 3 (2) ◽  
pp. 1
Author(s):  
Marina Okawa ◽  
Takafumi Taketomi ◽  
Goshiro Yamamoto ◽  
Makoto Fujisawa ◽  
Toshiyuki Amano ◽  
...  

This paper addresses the problem of tracking texturelessrigid curved objects. A common approach uses polygonalmeshes to represent curved objects inside an edge-based trackingsystem. However, in order to accurately recover their shape,high quality meshes are required, creating a trade-off betweencomputational efficiency and tracking accuracy. To solve thisissue, we suggest the use of quadrics calculated for each patchin the mesh to give local approximations of the object contour.This representation reduces considerably the level of detail of thepolygonal mesh while maintaining tracking accuracy. The noveltyof our research lies in using curves to represent the quadrics’projection in the current viewpoint for distance evaluation insteadof comparing directly the edges from the mesh and detectededges in the video image. In our tracking framework, we alsoinclude a method to calculate the measurable Degrees of Freedom(DoF) of the target object. This is used to recover the poseparameters when the object has less than 6DoF. Experimentalresults compare our approach to the traditional method ofusing sparse and dense meshes. Finally, we present a potentialAugmented Reality application of the proposed method.


2021 ◽  
pp. 282-296
Author(s):  
Massimo Ficco ◽  
Daniele Granata ◽  
Massimiliano Rak ◽  
Giovanni Salzillo

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