MIGOU: A Low-Power Experimental Platform with Programmable Logic Resources and Software-Defined Radio Capabilities

The increase in the number of mobile and Internet of Things (IoT) devices, along with the demands of new applications and services, represents an important challenge in terms of spectral coexistence. As a result, these devices are now expected to make an efficient and dynamic use of the spectrum, and to provide processed information instead of simple raw sensor measurements. These communication and processing requirements have direct implications on the architecture of the systems. In this work, we present MIGOU, a wireless experimental platform that has been designed to address these challenges from the perspective of resource-constrained devices, such as wireless sensor nodes or IoT end-devices. At the radio level, the platform can operate both as a software-defined radio and as a traditional highly integrated radio transceiver, which demands less node resources. For the processing tasks, it relies on a system-on-a-chip that integrates an ARM Cortex-M3 processor, and a flash-based FPGA fabric, where high-speed processing tasks can be offloaded. The power consumption of the platform has been measured in the different modes of operation. In addition, these hardware features and power measurements have been compared with those of other representative platforms. The results obtained confirm that a state-of-the-art tradeoff between hardware flexibility and energy efficiency has been achieved. These characteristics will allow for the development of appropriate solutions to current end-devices' challenges and to test them in real scenarios.

A Methodology for Choosing Time Synchronization Strategies for Wireless IoT Networks

The wireless Internet of Things (IoT) family grows without interruption. Every day more applications and wireless devices are available to interconnect and help solve multiple problems in areas such as health, critical infrastructure, industry, etc. Many of the tasks to be performed by the IoT network require time synchronization for their correct operation, either to use the spectrum more efficiently, to add data from different sensors, or to carry out coordinated communications. Each of these applications has different requirements regarding time synchronization. This means that the decision of which strategy to follow to synchronize an IoT end device becomes a task that requires important prior analysis and usually, if developers are experts in the topic, ends with the implementation of an ad hoc solution. In this article, we present a methodology to choose an adequate time-synchronization strategy for any wireless IoT application. We also present a tool that executes the methodology, guiding the IoT application developer through some input forms. This combination of methodology and tool abstracts developers from the complexities of time-synchronization strategies, allowing them to choose the correct strategy regardless of their level of knowledge in wireless IoT time synchronization. As a result, the methodology offers a set of time-synchronization strategies that are adjusted to the needs of developers and applications.