IoT is a rapidly growing area with products in the consumer, commercial and industrial market. Collecting data with multiple small and often battery-powered devices sets new challenges for both security and communication. There has been a distinct lack of a IoT specific communication protocols. The industry has had to use bulky interfaces not suitable for resource-constrained devices. MQTT is a standardised communication protocol made for the IoT industry. MQTT does however not have built-in security and it is up to the developers to implement a suitable security countermeasure. To evaluate how different security countermeasures impact MQTT in complexity, current consumption and security the following research questions are answered. How do you derive a measurement from the SEF that can be compared with a current consumption measurement? Which level of security, according to the SEF, will RSA, AES and TLS provide to MQTT when publishing a message to a broker? What level of complexity is added to MQTT when using chosen security countermeasure? Which of the analysed security countermeasure upholds an adequate security level while also having a low current consumption? To answer the above research questions an experiment approach has been used. Implementations of TLS, RSA and AES have been evaluated to measure how they affect the security level and current consumption of an MQTT publication, compared to no security countermeasures at all.Both RSA and AES had the same security level, but the current consumption for RSA was four times higher. The experiment showed that the security level is significantly higher for TLS, while it also has the highest current consumption. The security countermeasure evaluated differs greatly. TLS provides complete protections, while RSA and AES lacks authentication and does not ensure integrity and non-repudiation.Even if the current consumption for TLS is higher, the security it provides make it unreasonable to recommend any of the other security countermeasure implementations.

Avec l'évolution des technologies et le développement des objets connectés, la consommation des circuits est devenue un sujet important. Dans cette thèse nous nous concentrons sur la consommation des mémoires non volatiles à piégeage de charge. Afin de diminuer la consommation, différentes architectures ont vu le jour comme les mémoires 2T ou Split Gate. Nous proposons deux nouvelles architectures de mémoires permettant la diminution de la consommation par rapport à une mémoire Flash standard. La première, appelée ATW (Asymmetrical Tunnel Window), est composée d'une marche d'oxyde au niveau de son oxyde tunnel qui lui permet d'être moins consommatrice qu'une mémoire Flash standard. Une seconde architecture mémoire appelée eSTM (embedded Select Trench Memory) est aussi présentée. Son principal atout est la présence de son transistor de sélection qui est indispensable pour avoir une faible consommation. Grâce à son architecture, cette cellule est bien meilleure que l'architecture proposée précédemment (ATW). Une dernière étude a été réalisée afin d'optimiser le procédé de fabrication de la mémoire eSTM pour le rendre plus robuste. / With the evolution of technologies and the development of connected objects, the circuit consumption is becoming an important subject. In this thesis, we focus on the consumption of trap-charge non-volatile memories. To decrease the consumption, different architectures have emerged, like 2T or Split Gate memories. We propose two new memory architectures allowing to decrease the consumption compared to the standard Flash memory. The first, called ATW (Asymmetrical Tunnel Window), is composed of an oxide step in the tunnel oxide which allows to be less consumer than a standard Flash memory. A second memory architecture called eSTM (embedded Select Trench Memory) is also presented. Its main advantage is its select transistor which is essential to obtain a lower consumption. Thanks to its architecture, this cell is better than the previously proposed architecture (ATW). The last study has been performed to optimize the process flow of the eSTM memory to make it more robust.

Network lifetime is an important performance metric in Wireless Sensor Networks (WSNs). Transmission Power Control (TPC) is a well-established method to minimise energy consumption in transmission in order to extend node lifetime and, consequently, lead to solutions that help extend network lifetime. The accurate lifetime estimation of sensor nodes is useful for routing to make more energy-efficient decisions and prolong lifetime. This research proposes an Energy-Efficient TPC (EETPC) mechanism using the measured Received Signal Strength (RSS) to calculate the ideal transmission power. This includes the investigation of the impact factors on RSS, such as distance, height above ground, multipath environment, the capability of node, noise and interference, and temperature. Furthermore, a Dynamic Node Lifetime Estimation (DNLE) technique for WSNs is also presented, including the impact factors on node lifetime, such as battery type, model, brand, self-discharge, discharge rate, age, charge cycles, and temperature. In addition, an Energy-Efficient and Lifetime Aware Routing (EELAR) algorithm is designed and developed for prolonging network lifetime in multihop WSNs. The proposed routing algorithm includes transmission power and lifetime metrics for path selection in addition to the Expected Transmission Count (ETX) metric. Both simulation and real hardware testbed experiments are used to verify the effectiveness of the proposed schemes. The simulation experiments run on the AVRORA simulator for two hardware platforms: Mica2 and MicaZ. The testbed experiments run on two real hardware platforms: the N740 NanoSensor and Mica2. The corresponding implementations are on two operating systems: Contiki and TinyOS. The proposed TPC mechanism covers those investigated factors and gives an overall performance better than the existing techniques, i.e. it gives lower packet loss and power consumption rates, while delays do not significantly increase. It can be applied for single-hop with multihoming and multihop networks. Using the DNLE technique, node lifetime can be predicted more accurately, which can be applied for both static and dynamic loads. EELAR gives the best performance on packet loss rate, average node lifetime and network lifetime compared to the other algorithms and no significant difference is found between each algorithm with the packet delay.

Tracy Trackers utvecklar just nu en AI-plattform vars syfte är att övervaka hundens rörelsemönster. Plattformen består av en mikrokontroller med accelerometer, gyroskop, temperatur samt luftfuktighetssensorer som fästs på hunden. Mikrokontrollern är sedan uppkopplad till en mobil genom Bluetooth. I detta arbete undersöktes vilka batterier som finns på marknaden samt vilket som passar bäst för den prototyp som studerats. Målet med studien var att hitta ett batteri som är uppladdningsbart, har lång drifttid samt är ekonomiskt och miljömässigt hållbart för framtida produktion. Hårdvara för mätning av batterispänningens karaktäristik byggdes för att avgöra om olika batterier skilde sig åt.Strömförbrukningen hos de sensorer som var implementerade i produkten studerades med hjälp av oscilloskop och en egenkonstruerad förstärkarkrets. Vidare konstruerades ett lågpassfilter för att fastställa DC-komponenten av strömförbrukningen. Strömförbrukningen som uppmättes genom testerna i detta arbete avser det som drar ström i prototypen. Den utvecklade hårdvaran kan användas till mätningar på framtida prototyper. / Tracy Trackers is currently developing an AI platform which purpose is to monitor a dog's movement pattern. The platform consists of hardware with accelerometer, gyroscope, temperature and humidity sensors attached to the dog. The hardware is connected to a mobile through Bluetooth. A study was conducted to investigate which batteries that are available on the market and which ones that fit best for the prototype. The aim of the study was to find a rechargeable battery with long operat-ing hours that is economically and environmentally viable for future production. Hardware for monitoring the battery voltage characteristics was built to determine differences between kinds of batteries and if there was an optimal type of battery for the specific product. The sensors used by the prototype were studied using os-cilloscopes and a self-constructed circuit in order to be able to determine power consumption at different sampling frequencies. Furthermore, a circuit was built for filtering out certain frequencies to determine the current consumption of the DC-components. The current consumption measured by the tests in this study refers to what draws current in the prototype. The developed hardware can be used for measurements of future prototypes