Comunicações cooperativas em redes IEEE 802.11 multi-débito

Doutoramento em TelecomunicaçõesEsta tese apresenta um estudo sobre alguns dos protocolos de cooperação MAC para redes sem fios utilizando o sistema IEEE 802.11 multi-débito. É proposto um novo modelo de arquitetura para a categorização e análise da cooperação em redes sem fios, tendo este modelo sido aplicado a protocolos cooperativos existentes para camada MAC. É investigado como as características do meio físico, assim como os requisitos de níveis superiores podem ser aplicados ao processo de cooperação, com vista a melhorar as características de funcionamento da rede de comunicações. Para este propósito são exploradas as métricas mais relevantes para o processo de cooperação. São igualmente estudados os limites impostos pelos protocolos da camada MAC e as limitações práticas impostas por protocolos da família de normas que compõem o IEEE 802.11. Neste trabalho foi criada uma métrica multicamada, que permite considerar os requisitos aplicacionais de performance e o tipo de tráfego, assim como a mobilidade dos dispositivos, no funcionamento dos mecanismos de cooperação. Como forma de validação, e para corretamente avaliar o impacto da métrica, um novo protocolo de cooperação foi desenvolvido e implementado. O seu funcionamento é descrito de forma analítica assim como validado através de a um ambiente de simulação. Os resultados obtidos mostram que a utilização de uma métrica multicamada é uma técnica robusta, fornecendo melhorias consistentes no contexto de redes IEEE 802.11. São igualmente demonstradas várias outras características de funcionamento com impacto para as comunicações. Estes dados fornecem uma visão real e encorajadora para a realização de mais pesquisas para a melhoria da performance dos protocolos cooperativos, assim como a sua utilização num variado número de aplicações futuras. No final do documento são apresentados alguns desafios para a continuação da investigação deste tópico.This thesis presents a study on cooperative MAC protocols in Multi-rate IEEE 802.11 wireless networks. We proposed a novel architectural framework for cooperation algorithms in wireless network. This behavior model was considered for existing cooperative MAC protocols. A classification of these protocols was presented based on their cooperation objectives. We investigate how physical layer specifications and higher layer requirements can be applied in cooperation MAC protocols to enhance the overall network performance. For this purpose, we exploit the appropriate metrics which are consistent to the cooperation objectives. Performance bounds provided by MAC protocols and practical limitations posed by IEEE 802.11 standards have been also studied. A cross layer metric was achieved in cooperative MAC protocols to adapt cooperation performance to traffic service requirements and mobility scenario. In order to realize the impact of this metric, a new cooperative MAC protocol is designed and implemented. Analytical and simulation of this protocol was performed in different scenarios and environments. The obtained results have shown a robust technique in providing consistent cross layer optimization in context of IEEE 802.11 networks. A number of findings was experienced which are illustrated at the end. These observations would enhance and encourage potential research in the area and optimize the performance of cooperative protocols for a number of interesting applications in future. A summary of future research challenges is presented at the end

Constructing living buildings: a review of relevant technologies for a novel application of biohybrid robotics

Biohybrid robotics takes an engineering approach to the expansion and exploitation of biological behaviours for application to automated tasks. Here, we identify the construction of living buildings and infrastructure as a high-potential application domain for biohybrid robotics, and review technological advances relevant to its future development. Construction, civil infrastructure maintenance and building occupancy in the last decades have comprised a major portion of economic production, energy consumption and carbon emissions. Integrating biological organisms into automated construction tasks and permanent building components therefore has high potential for impact. Live materials can provide several advantages over standard synthetic construction materials, including self-repair of damage, increase rather than degradation of structural performance over time, resilience to corrosive environments, support of biodiversity, and mitigation of urban heat islands. Here, we review relevant technologies, which are currently disparate. They span robotics, self-organizing systems, artificial life, construction automation, structural engineering, architecture, bioengineering, biomaterials, and molecular and cellular biology. In these disciplines, developments relevant to biohybrid construction and living buildings are in the early stages, and typically are not exchanged between disciplines. We, therefore, consider this review useful to the future development of biohybrid engineering for this highly interdisciplinary application.publishe

Self-management Framework for Mobile Autonomous Systems

The advent of mobile and ubiquitous systems has enabled the development of autonomous systems such as wireless-sensors for environmental data collection and teams of collaborating Unmanned Autonomous Vehicles (UAVs) used in missions unsuitable for humans. However, with these range of new application domains comes a new challenge – enabling self-management in mobile autonomous systems. The primary challenge in using autonomous systems for real-life missions is shifting the burden of management from humans to these systems themselves without loss of the ability to adapt to failures, changes in context, and changing user requirements. Autonomous systems have to be able to manage themselves individually as well as to form self-managing teams that are able to recover or adapt to failures, protect themselves from attacks and optimise performance. This thesis proposes a novel distributed policy-based framework that enables autonomous systems to perform self management individually and as a team. The framework allows missions to be specified in terms of roles in an adaptable and reusable way, enables dynamic and secure team formation with a utility-based approach for optimal role assignment, caters for communication link maintenance among team members and recovery from failure. Adaptive management is achieved by employing an architecture that uses policy-based techniques to allow dynamic modification of the management strategy relating to resources, role behaviour, team and communications management, without reloading the basic software within the system. Evaluation of the framework shows that it is scalable with respect to the number of roles, and consequently the number of autonomous systems participating in the mission. It is also shown to be optimal with respect to role assignments, and robust to intermittent communication link disconnections and permanent team-member failures. The prototype implementation was tested on mobile robots as a proof-ofconcept demonstration

Machine Learning for Unmanned Aerial System (UAS) Networking

Fueled by the advancement of 5G new radio (5G NR), rapid development has occurred in many fields. Compared with the conventional approaches, beamforming and network slicing enable 5G NR to have ten times decrease in latency, connection density, and experienced throughput than 4G long term evolution (4G LTE). These advantages pave the way for the evolution of Cyber-physical Systems (CPS) on a large scale. The reduction of consumption, the advancement of control engineering, and the simplification of Unmanned Aircraft System (UAS) enable the UAS networking deployment on a large scale to become feasible. The UAS networking can finish multiple complex missions simultaneously. However, the limitations of the conventional approaches are still a big challenge to make a trade-off between the massive management and efficient networking on a large scale. With 5G NR and machine learning, in this dissertation, my contributions can be summarized as the following: I proposed a novel Optimized Ad-hoc On-demand Distance Vector (OAODV) routing protocol to improve the throughput of Intra UAS networking. The novel routing protocol can reduce the system overhead and be efficient. To improve the security, I proposed a blockchain scheme to mitigate the malicious basestations for cellular connected UAS networking and a proof-of-traffic (PoT) to improve the efficiency of blockchain for UAS networking on a large scale. Inspired by the biological cell paradigm, I proposed the cell wall routing protocols for heterogeneous UAS networking. With 5G NR, the inter connections between UAS networking can strengthen the throughput and elasticity of UAS networking. With machine learning, the routing schedulings for intra- and inter- UAS networking can enhance the throughput of UAS networking on a large scale. The inter UAS networking can achieve the max-min throughput globally edge coloring. I leveraged the upper and lower bound to accelerate the optimization of edge coloring. This dissertation paves a way regarding UAS networking in the integration of CPS and machine learning. The UAS networking can achieve outstanding performance in a decentralized architecture. Concurrently, this dissertation gives insights into UAS networking on a large scale. These are fundamental to integrating UAS and National Aerial System (NAS), critical to aviation in the operated and unmanned fields. The dissertation provides novel approaches for the promotion of UAS networking on a large scale. The proposed approaches extend the state-of-the-art of UAS networking in a decentralized architecture. All the alterations can contribute to the establishment of UAS networking with CPS