During the last decade, the exponential growth of mobile devices and wireless services created a huge demand for radio frequency-based technologies. Meanwhile, the lighting industry has been revolutionized due to the popularization of LED light bulbs, which are more economical and efficient. In that context, Visible Light Communication (VLC) is a disruptive technology based on LEDs that offers a free spectrum and high data rate, which can potentially serve as a complementary technology to the current radio frequency standards. In this work, we present a comprehensive state-of-the-art survey of Visible Light Communication, as well as the main concepts and challenges related to this emergent area. We overview VLC technology, from its physical aspects and communication architecture to its main applications and research challenges. Finally, we present the main research platforms available today, along with a deep analysis of the system design and future directions in the field.

Despite the growing interest in cryptocurrencies, the delays incurred to confirm transactions are one of the factors that hamper the wide adoption of systems such as Bitcoin. Bitcoin transactions usually are confirmed in short periods (minutes), but still much larger than conventional credit card systems (seconds). In this work, we propose a framework encompassing machine learning and a queueing theory model to (i) identify which transactions will be confirmed; and (ii) characterize the confirmation time of confirmed transactions. The proposed queueing theory model accounts for factors such as the activity time of blocks and the mean time between transactions. We parameterize the model for transactions that are confirmed within minutes, suggesting that its integration into a more general framework is a step towards building scalability to Bitcoin.

In the literature, the majority of research efforts in power line communication (PLC) has been focused on the physical layer in order to deal with issues such as time varying behavior of loads in electric power systems, the presence of high power impulsive noise, the occurrence of impedance mismatching, widespread use of unshielded power cables and coupling losses. While some work has also been done on the PLC Medium access control (MAC) sublayer, there is scope for further research to address the novel demands associated with cyber physical systems that need to mitigate unfairness in resource sharing, collisions and starvation, among other issues which may degrade data communication quality. In this paper we provide a comprehensive survey regarding the state of the art of MAC protocols for PLC systems, including an overview of existing PLC MAC research results and an organization of current PLC MAC protocols in terms of type of protocols, applications, and main research focus. Moreover, we present modern PLC technologies and standards, highlighting their MAC sublayer characteristics and providing a detailed comparative analysis of PLC MAC protocols in the context of current and emerging PLC applications. Finally, we identify future trends within the scope of the MAC sublayer for PLC systems with a view to stimulating additional research efforts on PLC MAC design.

In this paper we focus on knowledge extraction from large-scale wireless networks through stream processing. We present the primary methods for sampling, data collection, and monitoring of wireless networks and we characterize knowledge extraction as a machine learning problem on big data stream processing. We show the main trends in big data stream processing frameworks. Additionally, we explore the data preprocessing, feature engineering, and the machine learning algorithms applied to the scenario of wireless network analytics. We address challenges and present research projects in wireless network monitoring and stream processing. Finally, future perspectives, such as deep learning and reinforcement learning in stream processing, are anticipated.