A survey on subjecting electronic product code and non-ID objects to IP identification

Over the last decade, both research on the Internet of Things (IoT) and real-world IoT applications have grown exponentially. The IoT provides us with smarter cities, intelligent homes, and generally more comfortable lives. However, the introduction of these devices has led to several new challenges that must be addressed. One of the critical challenges facing interacting with IoT devices is to address billions of devices (things) around the world, including computers, tablets, smartphones, wearable devices, sensors, and embedded computers, and so on. This article provides a survey on subjecting Electronic Product Code and non-ID objects to IP identification for IoT devices, including their advantages and disadvantages thereof. Different metrics are here proposed and used for evaluating these methods. In particular, the main methods are evaluated in terms of their: (i) computational overhead, (ii) scalability, (iii) adaptability, (iv) implementation cost, and (v) whether applicable to already ID-based objects and presented in tabular format. Finally, the article proves that this field of research will still be ongoing, but any new technique must favorably offer the mentioned five evaluative parameters.Comment: 112 references, 8 figures, 6 tables, Journal of Engineering Reports, Wiley, 2020 (Open Access

Energy harvesting schemes for radio technologies used in IoT: overview and suitability study

The number of devices connected to the Internet increases day by day. Moreover people start using the network in their everyday life to shopping, to control the house by remote, to check news or the weather forecast, to check the traffic, to call their friend or their family and so on. Their phones are interconnected all the time with other devices and sensors to gather all the information the users need. This network of object and the exchange of data are described with the Internet of Things idea. With the Internet of Thing concept all object are connected to the Internet and they are able to transmit data to each other. Thanks to sensors, inanimate object are able to understand the environment around them and to make decision and to interact with it. With this scenario the amount of data exchanged is huge. The main two challenges of the Internet of Things concept are the energy consumption and the portability of a given sensor or node in the network. In this way all the object and people can be connected everywhere and all the time. To reach those aims it is important that the devices implement specific communication standards that require low energy to work and that guaranty, at the same time, quality and security to the transmission of the data. Batteries or cable are not suitable to satisfy the IoT requirements and new energy sources using energy harvesting schemes, are needed to power the devices. Moreover the communication protocols have to be faster and have to use as less power as possible to work. In this thesis an overview on multiple energy harvesting schemes given and different communication standards used in the Wireless Sensor Networks are analyzed. The main focus is on the energy consumption of the Wireless Sensor Networks that implements the communication standard IEEE 802.11ah. The aim was to understand whether it could be possible to power one node network or even a more complex one, only with the energy harvesting schemes described in the thesis. Networks of different sizes are simulated and analyzed. All the networks present only one AP but they differentiate from each other by the number of nodes (STAs). Moreover two different scenarios are simulated to better understand the energy consumption in different traffic case. Both saturated and non-saturated traffic scenario were simulated and analyzed. To enhance the throughput and to decrease the energy needed to power the sensors, different Modulation and Code Schemes where implemented. To assess the performance of simulated scenarios, the throughput and the energy consumption where analyzed. The results have showed that different networks required a small amount of energy to send and receive data. Therefore it is technically possible to power them only with some existing energy harvesting schemes