UWB localization with battery-powered wireless backbone for drone-based inventory management

Current inventory-taking methods (counting stocks and checking correct placements) in large vertical warehouses are mostly manual, resulting in (i) large personnel costs, (ii) human errors and (iii) incidents due to working at large heights. To remedy this, the use of autonomous indoor drones has been proposed. However, these drones require accurate localization solutions that are easy to (temporarily) install at low costs in large warehouses. To this end, we designed a Ultra-Wideband (UWB) solution that uses infrastructure anchor nodes that do not require any wired backbone and can be battery powered. The resulting system has a theoretical update rate of up to 2892 Hz (assuming no hardware dependent delays). Moreover, the anchor nodes have an average current consumption of only 27 mA (compared to 130 mA of traditional UWB infrastructure nodes). Finally, the system has been experimentally validated and is available as open-source software

Integrated Framework For Mobile Low Power IoT Devices

Ubiquitous object networking has sparked the concept of the Internet of Things (IoT) which defines a new era in the world of networking. The IoT principle can be addressed as one of the important strategic technologies that will positively influence the humans’ life. All the gadgets, appliances and sensors around the world will be connected together to form a smart environment, where all the entities that connected to the Internet can seamlessly share data and resources. The IoT vision allows the embedded devices, e.g. sensor nodes, to be IP-enabled nodes and interconnect with the Internet. The demand for such technique is to make these embedded nodes act as IP-based devices that communicate directly with other IP networks without unnecessary overhead and to feasibly utilize the existing infrastructure built for the Internet. In addition, controlling and monitoring these nodes is maintainable through exploiting the existed tools that already have been developed for the Internet. Exchanging the sensory measurements through the Internet with several end points in the world facilitates achieving the concept of smart environment. Realization of IoT concept needs to be addressed by standardization efforts that will shape the infrastructure of the networks. This has been achieved through the IEEE 802.15.4, 6LoWPAN and IPv6 standards. The bright side of this new technology is faced by several implications since the IoT introduces a new class of security issues, such as each node within the network is considered as a point of vulnerability where an attacker can utilize to add malicious code via accessing the nodes through the Internet or by compromising a node. On the other hand, several IoT applications comprise mobile nodes that is in turn brings new challenges to the research community due to the effect of the node mobility on the network management and performance. Another defect that degrades the network performance is the initialization stage after the node deployment step by which the nodes will be organized into the network. The recent IEEE 802.15.4 has several structural drawbacks that need to be optimized in order to efficiently fulfil the requirements of low power mobile IoT devices. This thesis addresses the aforementioned three issues, network initialization, node mobility and security management. In addition, the related literature is examined to define the set of current issues and to define the set of objectives based upon this. The first contribution is defining a new strategy to initialize the nodes into the network based on the IEEE 802.15.4 standard. A novel mesh-under cluster-based approach is proposed and implemented that efficiently initializes the nodes into clusters and achieves three objectives: low initialization cost, shortest path to the sink node, low operational cost (data forwarding). The second contribution is investigating the mobility issue within the IoT media access control (MAC) infrastructure and determining the related problems and requirements. Based on this, a novel mobility scheme is presented that facilitates node movement inside the network under the IEEE 802.15.4e time slotted channel hopping (TSCH) mode. The proposed model mitigates the problem of frequency channel hopping and slotframe issue in the TSCH mode. The next contribution in this thesis is determining the mobility impact on low latency deterministic (LLDN) network. One of the significant issues of mobility is increasing the latency and degrading packet delivery ratio (PDR). Accordingly, a novel mobility protocol is presented to tackle the mobility issue in LLDN mode and to improve network performance and lessen impact of node movement. The final contribution in this thesis is devising a new key bootstrapping scheme that fits both IEEE 802.15.4 and 6LoWPAN neighbour discovery architectures. The proposed scheme permits a group of nodes to establish the required link keys without excessive communication/computational overhead. Additionally, the scheme supports the mobile node association process by ensuring secure access control to the network and validates mobile node authenticity in order to eliminate any malicious node association. The purposed key management scheme facilitates the replacement of outdated master network keys and release the required master key in a secure manner. Finally, a modified IEEE 802.15.4 link-layer security structure is presented. The modified architecture minimizes both energy consumption and latency incurred through providing authentication/confidentiality services via the IEEE 802.15.4

Adaptive parameters adjustment in WBAN to mitigate Wi-Fi interferences

Wireless Body Area Network (WBAN), called also Wireless Body Sensor Network (WBSN), is composed of a set of tiny wireless devices (sensors) attached, implanted or ingested into the body. It offers real time and ubiquitous applications thanks to the small form, the lightness, and the wireless interface of sensors. WBAN performance is expected to be considerably degraded in the presence of Wi-Fi networks. Their operating channels overlap in the 2.4 GHz Industrial Scientific and Medical (ISM) band which produces interference when they transmit data, accompanied by data losses and quick battery exhaustion. Therefore, it is crucial to mitigate the interference between WBAN and Wi-Fi networks in order to maintain the efficiency and the reliability of the WBAN system. Proposals in the literature use an added complex hardware in WBAN system, or perform the exchange of additional information, or establish expensive communications, or affect the quality of service of the WBAN. Unlike previous researches, we proposed simple, low cost and dynamic method that adaptively adjusts specific parameters in the Medium Access Control (MAC) layer. We have proved the effectiveness of our approach based on theoretical analysis and simulation using MiXiM framework of OMNet++ simulato

Application of reinforcement learning with Q-learning for the routing in industrial wireless sensors networks

Industrial Wireless Sensor Networks (IWSN) usually have a centralized management approach, where a device known as Network Manager is responsible for the overall configuration, definition of routes, and allocation of communication resources. The routing algorithms need to ensure path redundancy while reducing latency, power consumption, and resource usage. Graph routing algorithms are used to address these requirements. The dynamicity of wireless networks has been a challenge for tuning and developing routing algorithms, and Machine Learning models such as Reinforcement Learning have been applied in a promising way in Wireless Sensor Networks to select, adapt and optimize routes. The basic concept of Reinforcement Learning is the existence of a learning agent that acts and changes the state of the environment, and receives rewards. However, the existing approaches do not meet some of the requirements of the IWSN standards. In this context, this thesis proposes the Q-Learning Reliable Routing approach, where the Q-Learning model is used to build graph routes. Two approaches are presented: QLRR-WA and QLRR-MA. QLRR-WA uses a learning agent that adjusts the weights of the cost equation of a state-of-the-art routing algorithm to reduce the latency and increase the network lifetime. QLRR-MA uses several learning agents so nodes can choose connections in the graph trying to reduce the latency. Other contributions of this thesis are the performance comparison of the state-of-the-art graph-routing algorithms and the evaluation methodology proposed. The QLRR algorithms were evaluated in a WirelessHART simulator, considering industrial monitoring applications with random topologies. The performance was analyzed considering the average network latency, network lifetime, packet delivery ratio and the reliability of the graphs. The results showed that, when compared to the state of the art, QLRR-WA reduced the average network latency and improved the lifetime while keeping high reliability, while QLRR-MA reduced latency and increased packet delivery ratio with a reduction in the network lifetime. These results indicate that Reinforcement Learning may be helpful to optimize and improve network performance.As Redes Industriais de Sensores Sem Fio (IWSN) geralmente têm uma abordagem de gerenciamento centralizado, onde um dispositivo conhecido como Gerenciador de Rede é responsável pela configuração geral, definição de rotas e alocação de recursos de comunicação. Os algoritmos de roteamento precisam garantir a redundância de caminhos para as mensagens, e também reduzir a latência, o consumo de energia e o uso de recursos. O roteamento por grafos é usado para alcançar estes requisitos. A dinamicidade das redes sem fio tem sido um desafio para o ajuste e o desenvolvimento de algoritmos de roteamento, e modelos de Aprendizado de Máquina como o Aprendizado por Reforço têm sido aplicados de maneira promissora nas Redes de Sensores Sem Fio para selecionar, adaptar e otimizar rotas. O conceito básico do Aprendizado por Reforço envolve a existência de um agente de aprendizado que atua em um ambiente, altera o estado do ambiente e recebe recompensas. No entanto, as abordagens existentes não atendem a alguns dos requisitos dos padrões das IWSN. Nesse contexto, esta tese propõe a abordagem Q-Learning Reliable Routing, onde o modelo Q-Learning é usado para construir os grafos de roteamento. Duas abordagens são propostas: QLRR-WA e QLRR-MA. A abordagem QLRR-WA utiliza um agente de aprendizado que ajusta os pesos da equação de custo de um algoritmo de roteamento de estado da arte, com o objetivo de reduzir a latência e aumentar a vida útil da rede. A abordagem QLRR-MA utiliza diversos agente de aprendizado de forma que cada dispositivo na rede pode escolher suas conexões tentando reduzir a latência. Outras contribuições desta tese são a comparação de desempenho das abordagens com os algoritmos de roteamento de estado da arte e a metodologia de avaliação proposta. As abordagens do QLRR foram avaliadas com um simulador WirelessHART, considerando aplicações de monitoramento industrial com diversas topologias. O desempenho foi analisado considerando a latência média da rede, o tempo de vida esperado da rede, a taxa de entrega de pacotes e a confiabilidade dos grafos. Os resultados mostraram que, quando comparado com o estado da arte, o QLRR-WA reduziu a latência média da rede e melhorou o tempo de vida esperado, mantendo alta confiabilidade, enquanto o QLRR-MA reduziu a latência e aumentou a taxa de entrega de pacotes, ao custo de uma redução no tempo de vida esperado da rede. Esses resultados indicam que o Aprendizado por Reforço pode ser útil para otimizar e melhorar o desempenho destas redes

Efficient aggregate computations in large-scale dense wireless sensor networks

Tese de doutoramento em InformáticaAssuming a world where we can be surrounded by hundreds or even thousands of inexpensive computing nodes densely deployed, each one with sensing and wireless communication capabilities, the problem of efficiently dealing with the enormous amount of information generated by those nodes emerges as a major challenge. The research in this dissertation addresses this challenge. This research work proves that it is possible to obtain aggregate quantities with a timecomplexity that is independent of the number of nodes, or grows very slowly as the number of nodes increases. This is achieved by co-designing the distributed algorithms for obtaining aggregate quantities and the underlying communication system. This work describes (i) the design and implementation of a prioritized medium access control (MAC) protocol which enforces strict priorities over wireless channels and (ii) the algorithms that allow exploiting this MAC protocol to obtain the minimum (MIN), maximum (MAX) and interpolation of sensor values with a time-complexity that is independent of the number of nodes deployed, whereas other state-of-the-art approaches have a time-complexity that is dependent on the number of nodes. These techniques also enable to efficiently obtain estimates of the number of nodes (COUNT) and the median of the sensor values (MEDIAN). The novel approach proposed to efficiently obtain aggregate quantities in large-scale, dense wireless sensor networks (WSN) is based on the adaptation to wireless media of a MAC protocol, known as dominance/binary countdown, which existed previously only for wired media, and design algorithms that exploit this MAC protocol for efficient data aggregation. Designing and implementing such MAC protocol for wireless media is not trivial. For this reason, a substantial part of this work is focused on the development and implementation of WiDom (short for Wireless Dominance) - a wireless MAC protocol that enables efficient data aggregation in large-scale, dense WSN. An implementation of WiDom is first proposed under the assumption of a fully connected network (a network with a single broadcast domain). This implementation can be exploited to efficiently obtain aggregated quantities. WiDom can also implement static priority scheduling over wireless media. Therefore, a schedulability analysis for WiDom is also proposed. WiDom is then extended to operate in sensor networks where a single transmission cannot reach all nodes, in a network with multiple broadcast domains. These results are significant because often networks of nodes that take sensor readings are designed to be large scale, dense networks and it is exactly for such scenarios that the proposed distributed algorithms for obtaining aggregate quantities excel. The implementation and test of these distributed algorithms in a hardware platform developed shows that aggregate quantities in large-scale, dense wireless sensor systems can be obtained efficientlly.É possível prever um mundo onde estaremos rodeados por centenas ou até mesmo milhares de pequenos nós computacionais densamente instalados. Cada um destes nós será de dimensões muito reduzidas e possui capacidades para obter dados directamente do ambiente através de sensores e transmitir informação via rádio. Frequentemente, este tipo de redes são denominadas de redes de sensores sem fio. Perante tal cenário, o problema de lidar com a considerável quantidade de informação gerada por todos estes nós emerge como um desafio de grande relevância. A investigação apresentada nesta dissertação atenta neste desafio. Este trabalho de investigação prova que é possível obter quantidades agregadas com uma complexidade temporal que é independente do número de nós computacionais envolvidos, ou cresce muito lentamente quando o número de nós aumenta. Isto é conseguido através uma co-concepção dos algoritmos para obter quantidades agregadas e do sistema de comunicação subjacente. Este trabalho descreve (i) a concepção e implementação de um protocolo de acesso ao meio que garante prioridades estáticas em canais de comunicação sem fio e (ii) os algoritmos que permitem tirar partido deste protocolo de acesso ao meio para obter quantidades agregadas como o mínimo (MIN), máximo (MAX) e interpolação de valores obtidos a partir de sensores ambientais com uma complexidade que é independente do número de nós computacionais envolvidos. Estas técnicas também permitem obter, de forma eficiente, estimativas do número de nós (COUNT) e a mediana dos valores dos sensores (MEDIAN). A abordagem inovadora, proposta para obter de forma eficiente quantidades agregadas em redes de sensores sem fio de larga escala, é baseada na adaptação para meios de comunicação sem fio de um protocolo de acesso ao meio anteriormente apenas existente em sistemas cablados, e na concepção de algoritmos que tiram partido deste protocolo para agregação de dados eficiente. A concepção e implementação de tal protocolo de acesso ao meio não é trivial. Por esta razão, uma parte substancial deste trabalho é focada no desenvolvimento e implementação de um protocolo de acesso ao meio que permite agregação de dados eficiente em redes de sensores sem fio densas e de larga escala. Esta implementação é denominada de WiDom. A implementação do WiDom apresentada foi inicialmente desenvolvida assumindo que a rede é totalmente ligada (uma transmisão de um nó alcança todos os outros nós). Esta implementação pode ser explorada para obter quantidades agregadas de forma eficiente. Adicionalmente, o protocolo WiDom pode implementar escalonamento utilizando prioridades fixas, permitindo a proposta de uma análise de resposta temporal. Neste trabalho, o WiDom é também estendido para funcionar em redes onde a transmissão de um nó não pode alcançar todos os outros nós. Os resultados apresentados neste trabalho são relevantes porque as redes de sensores sem fio são frequentemente concebidas para serem densas e de larga escala. É exactamente nestes casos que os algoritmos propostos para obter quantidades agregadas de forma eficiente apresentam maiores vantagens. A implementação e teste destes algoritmos distribuídos numa plataforma especialmente desenvolvida para o efeito demonstra que de facto podem ser obtidas quandidades agregadas de forma eficiente, mesmo em redes de sensores sem fio densas e de larga escala.This research was partially developed at the Real-Time Computing System Research Centre (CISTER), from the School of Engineering of the Polytechnic of Porto (ISEP/IPP

Channel Access Management in Data Intensive Sensor Networks

There are considerable challenges for channel access in Data Intensive Sensor Networks - DISN, supporting Data Intensive Applications like Structural Health Monitoring. As the data load increases, considerable degradation of the key performance parameters of such sensor networks is observed. Successful packet delivery ratio drops due to frequent collisions and retransmissions. The data glut results in increased latency and energy consumption overall. With the considerable limitations on sensor node resources like battery power, this implies that excessive transmissions in response to sensor queries can lead to premature network death. After a certain load threshold the performance characteristics of traditional WSNs become unacceptable. Research work indicates that successful packet delivery ratio in 802.15.4 networks can drop from 95% to 55% as the offered network load increases from 1 packet/sec to 10 packets/sec. This result in conjunction with the fact that it is common for sensors in an SHM system to generate 6-8 packets/sec of vibration data makes it important to design appropriate channel access schemes for such data intensive applications.In this work, we address the problem of significant performance degradation in a special-purpose DISN. Our specific focus is on the medium access control layer since it gives a fine-grained control on managing channel access and reducing energy waste. The goal of this dissertation is to design and evaluate a suite of channel access schemes that ensure graceful performance degradation in special-purpose DISNs as the network traffic load increases.First, we present a case study that investigates two distinct MAC proposals based on random access and scheduling access. The results of the case study provide the motivation to develop hybrid access schemes. Next, we introduce novel hybrid channel access protocols for DISNs ranging from a simple randomized transmission scheme that is robust under channel and topology dynamics to one that utilizes limited topological information about neighboring sensors to minimize collisions and energy waste. The protocols combine randomized transmission with heuristic scheduling to alleviate network performance degradation due to excessive collisions and retransmissions. We then propose a grid-based access scheduling protocol for a mobile DISN that is scalable and decentralized. The grid-based protocol efficiently handles sensor mobility with acceptable data loss and limited overhead. Finally, we extend the randomized transmission protocol from the hybrid approaches to develop an adaptable probability-based data transmission method. This work combines probabilistic transmission with heuristics, i.e., Latin Squares and a grid network, to tune transmission probabilities of sensors, thus meeting specific performance objectives in DISNs. We perform analytical evaluations and run simulation-based examinations to test all of the proposed protocols