Wireless sensor networks require time synchronization, which is the coordination of events or actions to make a system operate in unison. In this work, real experiments and a theoretical analysis of the behavior of the clock sources, most used in wireless sensor networks, have been carried out. The experiments have been performed on two real platforms from two different manufacturers in real environments with sudden changes in temperature. Complementary metal-oxide-semiconductor oscillators have a low accuracy, bigger than 500 ppm, and a high dependency with temperature. External crystal oscillators have good accuracy, around 20 ppm, and are stable with temperature. Temperature-compensated crystal oscillators are very accurate, around 5 ppm, and the temperature has no influence in their drift. The use of phase-locked loop circuits minimizes the impact of temperature and stabilizes oscillators. We highlight and demonstrate the importance of the early stages of design, especially the selection of the clock source, because that decision has a great impact on the performance of the time synchronization in wireless sensor 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.

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