Ultra-Low Cost GSM Phones Enabled by Baseband-Radios with Integrated Power-Management

Author(s):  
Christian Kranz ◽  
Markus Hammes ◽  
Jens Kissing ◽  
Dietolf Seippel ◽  
Vincent Rezard ◽  
...  
Keyword(s):  
Low Cost ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 19
Author(s):  
Alfio Di Mauro ◽  
Hamed Fatemi ◽  
Jose Pineda de Gyvez ◽  
Luca Benini

Power management is a crucial concern in micro-controller platforms for the Internet of Things (IoT) edge. Many applications present a variable and difficult to predict workload profile, usually driven by external inputs. The dynamic tuning of power consumption to the application requirements is indeed a viable approach to save energy. In this paper, we propose the implementation of a power management strategy for a novel low-cost low-power heterogeneous dual-core SoC for IoT edge fabricated in 28 nm FD-SOI technology. Ss with more complex power management policies implemented on high-end application processors, we propose a power management strategy where the power mode is dynamically selected to ensure user-specified target idleness. We demonstrate that the dynamic power mode selection introduced by our power manager allows achieving more than 43% power consumption reduction with respect to static worst-case power mode selection, without any significant penalty in the performance of a running application.


2015 ◽  
Vol 4 (1) ◽  
pp. 104
Author(s):  
Valentina Markova ◽  
Teodora Trifonova ◽  
Venceslav Draganov

This paper presents the design and implementation of universal low cost data collection module (DCM), which is an essential part of remote monitoring system based on wireless sensor network. The proposed module expands the capabilities of a measuring node for collecting data from greater number of sensors. The DCM includes four parts: one group multiplexers for data acquisition, second group multiplexers for power management, voltage to current converters and DC/DC converters. The universal DC/DC converters provide autonomous power supply for the sensors and the multiplexers, which can be turned on or off for a certain period of time. The data collecting, monitoring and logging functions are realized through a LabVIEW project.The proper operation and the reliable performance of the system were proved by practical experiment. The proposed module makes the WSN-based system a versatile solution for a variety of monitoring applications.


2016 ◽  
Vol 3 (3) ◽  
Author(s):  
T. Chailloux ◽  
A. Capitaine ◽  
B. Erable ◽  
G. Pillonnet

AbstractMicrobial fuel cells (MFC’s) are promising energy harvesters to constantly supply energy to sensors deployed in aquatic environments where solar, thermal and vibration sources are inadequate. In order to show the ready-to-use MFC potential as energy scavengers, this paper presents the association of a durable benthic MFC with a few dollars of commercially-available power management units (PMU’s) dedicated to other kinds of harvesters. With 20 cm


2004 ◽  
Vol 15 (03) ◽  
pp. 485-506 ◽  
Author(s):  
Mitali Singh ◽  
Viktor K. Prasanna

In-network collaborative computation is essential for implementation of a large number of sensor applications. We approach the problem of computation in sensor networks from a parallel and distributed system's perspective. We define COSMOS, the Cluster-based, heterOgeneouSMOdel for Sensor networks. The model abstracts the key features of the class of cluster-based sensor applications. It assumes a hierarchical network architecture comprising of a large number of low cost sensors with limited computation capability, and fewer number of powerful clusterheads, uniformly distributed in a two dimensional terrain. The sensors are organized into single hop clusters, each managed by a distinct clusterhead. The clusterheads are organized in a mesh-like topology. All sensors in a cluster are time synchronized, whereas the clusterheads communicate asynchronously. The sensors are assumed to have multiple power states and a wakeup mechanism to facilitate power management. To illustrate algorithm design using our model, we discuss implementation of algorithms for sorting and summing in sensor networks.


Sign in / Sign up

Export Citation Format

Share Document