With wireless signals, it is possible to send all kind of data through a communication system. Many companies today having problems implementing wireless communication system because of big areas and many obstacles that blocks the wireless signals. Recent releases of mesh network standards that has the main objective to provide a network over a large area. Toyota Material Handling Europe (TMHE) that develops and produce trucks is one company that wants to use this new network topology to get to the next level of communication. TMHE is developing a new communication system between their trucks and the goal is to be independent of Wi-Fi and fixed structures in an industry. The aim is to establish communication through Bluetooth and create a mesh network between the trucks at a site. This kind of communication can create many new possibilities for new features, which can make the daily work easier. The problem with obstacles and interferences is still a problem and TMHE created a thesis to research Bluetooth mesh networks to see if this kind of implementation is suitable for the environments that exists in an industry. This thesis research the architecture of a Bluetooth mesh network and different setups of a network and tests how it stands in an industry with many different surrounding.

This thesis presents a framework for collecting network traffic data usable in performance evaluations of Bluetooth Mesh networks. The framework is designed to be adaptive, effective, and efficient. These design goals are intended to minimize resource usage and thereby take constraints in Bluetooth Mesh into account. An implementation of the framework, based on the Bluetooth Mesh model concept, is also presented. The implementation is then validated and evaluated to analyse to what degree it fulfills the requirements of adaptive, effective, and efficient data collection. The evaluation demonstrates the importance of minimizing the size of the reports sent in the framework since larger messages sent with short intervals have a noticeable effect on both the packet delivery ratio of user traffic and the reporting latency. It is also shown that the adaptive reporting feature, that aims to reduce the effect of the framework on user traffic by postponing reporting during high traffic loads, has a positive effect on neighboring nodes overall packet delivery ratio.

Monitoring of the carbon dioxide concentration in the building is carried out for several reasons. One is to ensure hygiene conditions. With the advent of Bluetooth 5.0 came the support of mesh network technology, which is defined by the Bluetooth Mesh standard. By implementing this standard, we can create an extensive network of devices monitoring the concentration of carbon dioxide in the building. Based on the monitored concentration, we can control the air conditioning and ventilation of the spaces, ensuring that the hygiene conditions are met. Thanks to the compatibility of Bluetooth Mesh with Bluetooth Low Energy, it is possible to access individual nodes, e.g. from a mobile phone. The aim of this work is to design and implement a measuring system whose elements will communicate with each other using Bluetooth Mesh wireless technology.

Dagens smarta enheter bygger nuförtiden allt mer på att ständigt hålla sig uppkopplade till allt inom dess omgivning. Industrier och hem innehåller alltmer små batteridrivna sensorer samt enheter som kommunicerar med varandra, dock är detta en begränsning när det gäller räckvidden av en enhet. Målet med denna uppsatsen är att undersöka användarbarhet av nya funktioner inom Bluetooth, samt belysa fördelar och nackdelar vilket kan uppstå med respektive teknologi när det gäller förlängd räckvidd. Vidare utfördes en jämförelsestudie, med målet att framföra skillnader för hur Bluetooth Mesh skiljer sig gentemot de andra Mesh teknologierna.Resultatet av denna uppsatsen visar att Bluetooth Mesh och Long-range har diverse svagheter och styrkor när det gäller olika användningsområden. Överföring av data med en högre hastighet och ett måttligt avstånd skulle vara tillräckligt för Long-range, medan Bluetooth Mesh anpassar sig mer för en större täckning och lättare dataöverföringar. / The smart devices of today are more and more dependent on being constantly connected to everything in its surrounding. Industries and homes contain more and more small battery powered sensors and devices, communicating with each other. However, there is a limitation when it comes to the range coverage of a device. The purpose of this thesis is to investigate the usefulness of the new features mesh networking and extended range for Bluetooth, as well as highlight the pros and cons that may exist with respective extended range technologies. Furthermore, a theoretical comparative study was conducted, with the aim of presenting some of the differences between Bluetooth Mesh and other common Mesh technologies. The results show that both Bluetooth Mesh and Long-range have strengths and weaknesses when it comes to different use cases. Transferring data with a bit higher throughput and a moderate distance would be suitable for a Long-range purpose, while Bluetooth Mesh is more suitable for a larger coverage and lighter data transfer.

[pt] Este trabalho avalia a coleta esporádica de dados em uma rede sem fio Bluetooth Mesh, usando o simulador OMNET (mais mais) INET. O coletor de dados é um nó sink em movimento, que poderia ser um smartphone ou outro dispositivo portátil, carregado por um pedestre, ciclista, animal, ou um drone. O nó sink poderia se conectar a uma rede mesh em áreas de difícil acesso onde não há acesso a internet, e coletar dados de sensores. Após implementar extensões ao Bluetooth Mesh, funcionalidades de nós Low Power e Friends no OMNET (mais mais), conseguimos propor e avaliar algoritmos para roteamento adaptativo, e com foco em mobilidade, de dados de sensores em direção ao nó sink. Uma variação de um dos algoritmos de roteamento propostos alcançou um aumento de 173,54 por cento na quantidade de dados únicos entregues ao nó sink em comparação ao algoritmo de roteamento padrão do Bluetooth Mesh. Neste caso, houve um aumento de apenas 4,63 por cento no consumo de energia para o mesmo cenário. Além disso, a taxa de entrega aumentou em 111.82 por cento. / [en] This work evaluates sporadic data collection on a Bluetooth Mesh network, using the OMNET (plus plus) INET simulator. The data collector is a roaming sink node, which could be a smartphone or other portable device, carried by a pedestrian, a biker, an animal, or a drone. The sink node could connect to a mesh network in hard-to-reach areas that do not have internet access and collect sensor data. After implementing Bluetooth Mesh relay extensions, Low Power, and Friend features in OMNET (plus plus), we were able to propose and evaluate algorithms for mobility-aware, adaptive, routing of sensor data towards the sink node. One variation of a proposed routing algorithm achieved a 173.54 percent increase in unique data delivered to the sink node compared to Bluetooth Mesh s default routing algorithm. In that case, there was only a 4.63 percent increase in energy consumption for the same scenario. Also, the delivery rate increased by 111.82 percent.

When choosing what IoT protocol to use today, there are lots of choices. If a mesh type network is chosen, Bluetooth mesh might be a possible candidate. Bluetooth mesh without correctly configured parameters can however suffer from congestion and packet loss if the network is very dense or consists of many nodes. This can be counteracted by choosing which nodes should be relays more carefully, as well as setting the re-transmission count and Time To Live (TTL) based on the current topology of the network. If the nodes in the network change position or are added/removed regularly, it is impossible to set the parameters optimal for all the possible network layouts. This is where a dynamic configuration comes in handy. In this master thesis a custom control model was created which implemented the K2 Pruning algorithm for relay selection, custom heartbeats for a dynamic TTL on each node, and a static re-transmission count for message originators and relays. A possible way to implement a dynamic re-transmission count is also discussed, as well as how the dynamic configuration could be autonomous without the need of physical interaction when reconfiguring the network. The implemented dynamic configuration tested on a physical system of 33 nodes was partly unsuccessful, but still provided improved Packet Delivery Ratio (PDR), reduced message delay, and useful knowledge for future implementations of a dynamic configuration. The K2 Pruning algorithm failed in choosing relays correct and quickly due to congestion during the neighbor information exchange needed to run the algorithm. Therefore, a different relay selection algorithm is suggested for future models or the refrain of acknowledged messages during the neighbor information exchange phase.

<p>Bluetooth is the de facto standard for short-range wireless communications. Besides Bluetooth Classic (BC), Bluetooth also consists of Bluetooth Low Energy (BLE) and Bluetooth Mesh (Mesh), two relatively new protocols, paving the way for its domination in the era of IoT and 5G. Meanwhile, attacks against Bluetooth, such as BlueBorne, BleedingBit, KNOB, BIAS, and BThack, have been booming in the past few years, impacting the security and privacy of billions of devices. These attacks exploit both design issues in the Bluetooth specification and vulnerabilities of its implementations, allowing for privilege escalation, remote code execution, breaking cryptography, spoofing, device tracking, etc.</p> <p><br></p> <p>To secure Bluetooth, researchers have proposed different approaches for both Bluetooth specification (e.g., formal analysis) and implementation (e.g., fuzzing). However, existing analyses of the Bluetooth specification and implementations are either done manually, or the automatic approaches only cover a small part of the targets. As a consequence, current research is far from complete in securing Bluetooth.</p> <p><br></p> <p>Therefore, in this dissertation, we propose the following research to provide missing pieces in prior research toward completing Bluetooth security research in terms of both Bluetooth specification and implementations. (i) For Bluetooth security at the specification level, we start from one protocol in Bluetooth, BLE, and focus on the previously unexplored reconnection procedure of two paired BLE devices. We conduct a formal analysis of this procedure defined in the BLE specification to provide security guarantees and identify new vulnerabilities that allow spoofing attacks. (ii) Besides BLE, we then formally verify other security-critical protocols in all Bluetooth protocols (BC, BLE, and Mesh). We provide a comprehensive formal analysis by covering the aspects that prior research fails to include (i.e., all possible combinations of protocols and protocol configurations) and considering a more realistic attacker model (i.e., semi-compromised device). With this model, we are able to rediscover five known vulnerabilities and reveal two new issues that affect BC/BLE dual-stack devices and Mesh devices, respectively. (iii) In addition to the formal analysis of specification security, we propose and build a comprehensive formal model to analyze Bluetooth privacy (i.e., device untraceability) at the specification level. In this model, we convert device untraceability into a reachability problem so that it can be verified using existing tools without introducing false results. We discover four new issues allowed in the specification that can lead to eight device tracking attacks. We also evaluate these attacks on 13 Bluetooth implementations and find that all of them are affected by at least two issues. (iv) At the implementation level, we improve Bluetooth security by debloating (i.e., removing code) Bluetooth stack implementations, which differs from prior automatic approaches, such as fuzzing. We keep only the code of needed functionality by a user and minimize their Bluetooth attack surface by removing unneeded Bluetooth features in both the host stack code and the firmware. Through debloating, we can remove 20 known CVEs and prevent a wide range of attacks again Bluetooth. With the research presented in this thesis, we improve Bluetooth security and privacy at both the specification and implementation levels.</p>