Leonardo Steinfeld

An evaluation of free/open source static analysis tools applied to embedded software

Static analysis can be a valuable strategy to improve the quality of embedded software at a lower development cost. In this paper, we have surveyed ten different free/open source tools that perform static software analysis and evaluated their use in embedded software. Experimental results show that the studied tools present widely different results, and most of them are not ready to be applied to embedded systems. Furthermore, we discuss possible directions to improve the use of static analysis tools in the embedded domain.

Low-Power Self-Energy Meter for Wireless Sensor Network

Real-time measurement of the energy consumption of wireless sensor network nodes in the field has many interesting applications that range from predicting the remaining battery charge to the energy efficiency assessment of communication protocols. However, designing such a system presents many challenges. In this work we present a measurement method and circuit, named Self-Energy Meter (SEM), that easily adds to a sensor node the capability of measuring its own energy consumption. The SEM developed has very low power consumption, ensuring an almost negligible impact in the battery lifetime. It also solves the problem of handling a dynamic range of five decades. Results from simulations show that the SEM is highly linear, with a coefficient of determination of 0.996, presenting a very low temperature drift, and is almost independent of the power supply.

Low-Power Processors Require Effective Memory Partitioning

The ever increasing complexity of embedded systems demands for rising memory size, and larger memories increase the power drain. In this work, we exploit banked memories with independent low-leakage retention mode in event-driven applications. The resulting energy saving for a given number of banks is close to the maximum achievable value, since the memory banks access pattern of event-driven applications presents a high temporal locality, leading to a low saving loss due to wake-up transitions. Results show an energy reduction up to 77.4% for a memory of ten banks with a partition overhead of 1%.

Fabrication and characterization of a directional SPIDA antenna for wireless sensor networks

This paper presents the simulation, fabrication and complete characterization of a 2.4 GHz directional antenna designed for Wireless Sensor Network (WSN) nodes, named SPIDA. The use of this kind of antennas empowers the performance of sensor nodes, as they increase the communication range without compromising the power consumption. The antenna was simulated and the results were compared with measurements, obtaining a gain of 6.8 dBi. Also future optimization options for this antenna are discussed, including the use of switched beamforming.

An implementation of a home energy management platform for Smart Grid

In recent years a great number of Smart Grid home monitor and control strategies have been proposed and many optimization algorithms were developed. However, many of them have only been tested by simulations, in part due to the absence of an open and versatile testing platform. We thus present a design and implementation of an open home energy management system platform. This implementation is based on Contiki OS, CoAP as application protocol, and IPv6 over 802.15.4 (6lowPAN) for communication. An optimization algorithm was implemented for a platform test. Experiments verified a good performance for the proposed architecture.

Average Power Consumption Breakdown of Wireless Sensor Network Nodes Using IPv6 over LLNs

This paper presents a simple but still powerful approach for the analysis of the average power consumption of a sensor node using the IPv6 over Low power and Lossy Networks (LLN) stack, which is one of the most widely adopted and promising communication stacks. Power consumption is broken down according to the node states (i.e. CPU, IRQ, LPM, Tx, Rx) and according to the network protocols (e.g. CoAP, RPL, 6LoWPAN, Contiki MAC), identifying the relative weight of each protocol in the total energy consumption for several configurations. Results show that the Low Power Listening (LPL) mechanism of the radio duty cycling layer and RPL control messages have the highest impact on the total energy consumption, while the applications report rate has a very low impact for periods over 60 seconds.

Antenna Characterization without Using Anechoic Chambers or TEM Cells

One of the accustomed procedures to characterize an antenna is evaluating the radiation pattern in an anechoic chamber or at least in a TEM cell. Besides avoiding the reflections, these devices allow a very precise measure of the radiation pattern by isolating the external interference. In this paper an alternative to characterize antennas without using anechoic chambers or TEM cells is discussed. An example of measures obtained by using this method is shared to show the potential of this technique. Additionally the measures are compared with the simulations results obtained with the simulation tool Computer Simulation Technology (CST).

DC-DC switching converter as on-field self energy meter

A DC-DC switching converter, originally included to reduce the power consumption of a Wireless Sensor Networks (WSN) node, has been proposed as the core of an on-field self-energy meter. In this paper we present a method and circuit that improves the electronics proposed by previous work by conditioning the signal from the switching converter that is connected to the microcontrollers counter. A software module that allows a WSN node to measure its own charge and current consumption was also implemented. The proposed method allows to measure the current consumption in a wide range, from 0 to 30mA, is highly linear and is ultra-low-power (the maximum current consumption is 8μA). Finally, we present a case study in which the proposed method is used to power profile a WSN node. Results show that a time-based estimation (Energest) overestimates the Clear Channel Assessment consumption for more than 10%.

Wearable EEG via lossless compression

This work presents a wearable multi-channel EEG recording system featuring a lossless compression algorithm. The algorithm, based in a previously reported algorithm by the authors, exploits the existing temporal correlation between samples at different sampling times, and the spatial correlation between different electrodes across the scalp. The low-power platform is able to compress, by a factor between 2.3 and 3.6, up to 300sps from 64 channels with a power consumption of 176μW/ch. The performance of the algorithm compares favorably with the best compression rates reported up to date in the literature.This work presents a wearable multi-channel EEG recording system featuring a lossless compression algorithm. The algorithm, based in a previously reported algorithm by the authors, exploits the existing temporal correlation between samples at different sampling times, and the spatial correlation between different electrodes across the scalp. The low-power platform is able to compress, by a factor between 2.3 and 3.6, up to 300sps from 64 channels with a power consumption of 176μW/ch. The performance of the algorithm compares favorably with the best compression rates reported up to date in the literature.

Self-energy meter in duty-cycle battery operated sensor nodes

Reduced levels of energy consumption is one of the major goals in Wireless Sensor Networks (WSNs), making the design of a sensor node a challenging task. On-field real-time measurement of the energy consumption of sensor nodes could have a major impact on developing wireless networks. It could be applied to predict the remaining battery charge or to asses the energy efficiency of communication protocols. However, designing such a system presents many challenges that will be discussed in this work. Moreover, we present a measurement method and circuit, named self-energy meter (SEM), that easily adds to a sensor node the capability of measuring its own energy consumption. SEM is a novel approach focused in solving the problem of covering a dynamic range of five decades in duty-cycle battery operated sensor nodes. Experimental results show that SEM has very low power consumption, ensuring an almost negligible impact in the battery lifetime, is highly linear, presents a very low temperature drift, and is almost independent of the power supply.