Energy-aware medium access control protocols for wireless sensors network applications

The main purpose of this thesis was to investigate energy efficient Medium Access Control (MAC) protocols designed to extend the lifetime of a wireless sensor network application, such as tracking, environment monitoring, home security, patient monitoring, e.g., foetal monitoring in the last weeks of pregnancy. From the perspective of communication protocols, energy efficiency is one of the most important issues, and can be addressed at each layer of the protocol stack; however, our research only focuses on the medium access control (MAC) layer. An energy efficient MAC protocol was designed based on modifications and optimisations for a synchronized power saving Sensor MAC (SMAC) protocol, which has three important components: periodic listen and sleep, collision and overhearing avoidance and message passing. The Sensor Block Acknowledgement (SBACK) MAC protocol is proposed, which combines contention-based, scheduling-based and block acknowledgement-based schemes to achieve energy efficiency. In SBACK, the use of ACK control packets is reduced since it will not have an ACK packet for every DATA packet sent; instead, one special packet called Block ACK Response will be used at the end of the transmission of all data packets. This packet informs the sender of how many packets were received by the receiver, reducing the number of ACK control packets we intended to reduce the power consumption for the nodes. Hence more useful data packets can be transmitted. A comparison study between SBACK and SMAC protocol is also performed. Considering 0% of packet losses, SBACK decreases the energy consumption when directly compared with S-MAC, we will have always a decrease of energy consumption. Three different transceivers will be used and considering a packet loss of 10% we will have a decrease of energy consumption between 10% and 0.1% depending on the transceiver. When there are no retransmissions of packets, SBACK only achieve worst performance when the number of fragments is less than 12, after that the decrease of average delay increases with the increase of the fragments sent. When 10% of the packets need retransmission only for the TR1000 transceiver worst results occurs in terms of energy waste, all other transceivers (CC2420 and AT86RF230) achieve better results. In terms of delay if we need to retransmit more than 10 packets the SBACK protocol always achieves better performance when comparing with the other MAC protocols that uses ACK

Technologies to improve the performance of wireless sensor networks in high-traffic applications

The expansion of wireless sensor networks to advanced areas, including structure health monitoring, multimedia surveillance, and health care monitoring applications, has resulted in new and complex problems. Traditional sensor systems are designed and optimised for extremely low traffic loads. However, it has been witnessed that network performance drops rapidly with the higher traffic loads common in advanced applications. In this thesis, we examine the system characteristics and new system requirements of these advanced sensor network applications. Based on this analysis, we propose an improved architecture for wireless sensor systems to increase the network performance while maintaining compatibility with the essential WSN requirements: low power, low cost, and distributed scalability. We propose a modified architecture deriving from the IEEE 802.15.4 standard, which is shown to significantly increase the network performance in applications generating increased data loads. This is achieved by introducing the possibility of independently allocating the sub-carriers in a distributed manner. As a result, the overall efficiency of the channel contention mechanism will be increased to deliver higher throughput with lower energy consumption. Additionally, we develop the concept of increasing the data transmission efficiency by adapting the spreading code length to the wireless environment. Such a modification will not only be able to deliver higher throughput but also maintain a reliable wireless link in the harsh RF environment. Finally, we propose the use of the battery recovery effect to increase the power efficiency of the system under heavy traffic load conditions. These three innovations minimise the contention window period while maximising the capacity of the available channel, which is shown to increase network performance in terms of energy efficiency, throughput and latency. The proposed system is shown to be backwards compatible and able to satisfy both traditional and advanced applications and is particularly suitable for deployment in harsh RF environments. Experiments and analytic techniques have been described and developed to produce performance metrics for all the proposed techniques

Design for energy-efficient and reliable fog-assisted healthcare IoT systems

Cardiovascular disease and diabetes are two of the most dangerous diseases as they are the leading causes of death in all ages. Unfortunately, they cannot be completely cured with the current knowledge and existing technologies. However, they can be effectively managed by applying methods of continuous health monitoring. Nonetheless, it is difficult to achieve a high quality of healthcare with the current health monitoring systems which often have several limitations such as non-mobility support, energy inefficiency, and an insufficiency of advanced services. Therefore, this thesis presents a Fog computing approach focusing on four main tracks, and proposes it as a solution to the existing limitations. In the first track, the main goal is to introduce Fog computing and Fog services into remote health monitoring systems in order to enhance the quality of healthcare. In the second track, a Fog approach providing mobility support in a real-time health monitoring IoT system is proposed. The handover mechanism run by Fog-assisted smart gateways helps to maintain the connection between sensor nodes and the gateways with a minimized latency. Results show that the handover latency of the proposed Fog approach is 10%-50% less than other state-of-the-art mobility support approaches. In the third track, the designs of four energy-efficient health monitoring IoT systems are discussed and developed. Each energy-efficient system and its sensor nodes are designed to serve a specific purpose such as glucose monitoring, ECG monitoring, or fall detection; with the exception of the fourth system which is an advanced and combined system for simultaneously monitoring many diseases such as diabetes and cardiovascular disease. Results show that these sensor nodes can continuously work, depending on the application, up to 70-155 hours when using a 1000 mAh lithium battery. The fourth track mentioned above, provides a Fog-assisted remote health monitoring IoT system for diabetic patients with cardiovascular disease. Via several proposed algorithms such as QT interval extraction, activity status categorization, and fall detection algorithms, the system can process data and detect abnormalities in real-time. Results show that the proposed system using Fog services is a promising approach for improving the treatment of diabetic patients with cardiovascular disease

Ultra-low power IoT applications: from transducers to wireless protocols

This dissertation aims to explore Internet of Things (IoT) sensor nodes in various application scenarios with different design requirements. The research provides a comprehensive exploration of all the IoT layers composing an advanced device, from transducers to on-board processing, through low power hardware schemes and wireless protocols for wide area networks. Nowadays, spreading and massive utilization of wireless sensor nodes pushes research and industries to overcome the main limitations of such constrained devices, aiming to make them easily deployable at a lower cost. Significant challenges involve the battery lifetime that directly affects the device operativity and the wireless communication bandwidth. Factors that commonly contrast the system scalability and the energy per bit, as well as the maximum coverage. This thesis aims to serve as a reference and guideline document for future IoT projects, where results are structured following a conventional development pipeline. They usually consider communication standards and sensing as project requirements and low power operation as a necessity. A detailed overview of five leading IoT wireless protocols, together with custom solutions to overcome the throughput limitations and decrease the power consumption, are some of the topic discussed. Low power hardware engineering in multiple applications is also introduced, especially focusing on improving the trade-off between energy, functionality, and on-board processing capabilities. To enhance these features and to provide a bottom-top overview of an IoT sensor node, an innovative and low-cost transducer for structural health monitoring is presented. Lastly, the high-performance computing at the extreme edge of the IoT framework is addressed, with special attention to image processing algorithms running on state of the art RISC-V architecture. As a specific deployment scenario, an OpenCV-based stack, together with a convolutional neural network, is assessed on the octa-core PULP SoC

Intelligent Security Provisioning and Trust Management for Future Wireless Communications

The fifth-generation (5G)-and-beyond networks will provide broadband access to a massive number of heterogeneous devices with complex interconnections to support a wide variety of vertical Internet-of-Things (IoT) applications. Any potential security risk in such complex systems could lead to catastrophic consequences and even system failure of critical infrastructures, particularly for applications relying on tight collaborations among distributed devices and facilities. While security is the cornerstone for such applications, trust among entities and information privacy are becoming increasingly important. To effectively support future IoT systems in vertical industry applications, security, trust and privacy should be dealt with integratively due to their close interactions. However, conventional technologies always treat these aspects separately, leading to tremendous security loopholes and low efficiency. Existing solutions often feature various distinctive weaknesses, including drastically increased latencies, communication and computation overheads, as well as privacy leakage, which are extremely undesirable for delay-sensitive, resource-constrained, and privacy-aware communications. To overcome these issues, this thesis aims at creating new multi-dimensional intelligent security provisioning and trust management approaches by leveraging the most recent advancements in artificial intelligence (AI). The performance of the existing physical-layer authentication could be severely affected by the imperfect estimate and the variation of physical link attributes, especially when only a single attribute is employed. To overcome this challenge, two multi-dimensional adaptive schemes are proposed as intelligent processes to learn and track the all available physical attributes, hence to improve the reliability and robustness of authentication by fusing multiple attributes. To mitigate the effects of false authentication, an adaptive trust management-based soft authentication and progressive authorization scheme is proposed by establishing trust between transceivers. The devices are authorized by their trust values, which are dynamically evaluated in real-time based on the varying attributes, resulting in soft security and progressive authorization. By jointly considering security and privacy-preservation, a distributed accountable recommendation-based access scheme is proposed for blockchain-enabled IoT systems. Authorized devices are introduced as referrers for collaborative authentication, and the anonymous credential algorithm helps to protect privacy. Wrong recommendations will decrease the referrers’ reputations, named as accountability. Finally, to secure resource-constrained communications, a lightweight continuous authentication scheme is developed to identify devices via their pre-arranged pseudo-random access sequences. A device will be authenticated as legitimate if its access sequences are identical to the pre-agreed unique order between the transceiver pair, without incurring long latency and high overhead. Applications enabled by 5G-and-beyond networks are expected to play critical roles in the coming connected society. By exploring new AI techniques, this thesis jointly considers the requirements and challenges of security, trust, and privacy provisioning, and develops multi-dimensional intelligent continuous processes for ever-growing demands of the quality of service in diverse applications. These novel approaches provide highly efficient, reliable, model-independent, situation-aware, and continuous protection for legitimate communications, especially in the complex time-varying environment under unpredictable network dynamics. Furthermore, the proposed soft security enables flexible designs for heterogeneous IoT devices, and the collaborative schemes provide efficient solutions for massively distributed entities, which are of paramount importance to diverse industrial applications due to their ongoing convergence with 5G-and-beyond networks

On a Joint Physical Layer and Medium Access Control Sublayer Design for Efficient Wireless Sensor Networks and Applications

Wireless sensor networks (WSNs) are distributed networks comprising small sensing devices equipped with a processor, memory, power source, and often with the capability for short range wireless communication. These networks are used in various applications, and have created interest in WSN research and commercial uses, including industrial, scientific, household, military, medical and environmental domains. These initiatives have also been stimulated by the finalisation of the IEEE 802.15.4 standard, which defines the medium access control (MAC) and physical layer (PHY) for low-rate wireless personal area networks (LR-WPAN). Future applications may require large WSNs consisting of huge numbers of inexpensive wireless sensor nodes with limited resources (energy, bandwidth), operating in harsh environmental conditions. WSNs must perform reliably despite novel resource constraints including limited bandwidth, channel errors, and nodes that have limited operating energy. Improving resource utilisation and quality-of-service (QoS), in terms of reliable connectivity and energy efficiency, are major challenges in WSNs. Hence, the development of new WSN applications with severe resource constraints will require innovative solutions to overcome the above issues as well as improving the robustness of network components, and developing sustainable and cost effective implementation models. The main purpose of this research is to investigate methods for improving the performance of WSNs to maintain reliable network connectivity, scalability and energy efficiency. The study focuses on the IEEE 802.15.4 MAC/PHY layers and the carrier sense multiple access with collision avoidance (CSMA/CA) based networks. First, transmission power control (TPC) is investigated in multi and single-hop WSNs using typical hardware platform parameters via simulation and numerical analysis. A novel approach to testing TPC at the physical layer is developed, and results show that contrary to what has been reported from previous studies, in multi-hop networks TPC does not save energy. Next, the network initialization/self-configuration phase is addressed through investigation of the 802.15.4 MAC beacon interval setting and the number of associating nodes, in terms of association delay with the coordinator. The results raise doubt whether that the association energy consumption will outweigh the benefit of duty cycle power management for larger beacon intervals as the number of associating nodes increases. The third main contribution of this thesis is a new cross layer (PHY-MAC) design to improve network energy efficiency, reliability and scalability by minimising packet collisions due to hidden nodes. This is undertaken in response to findings in this thesis on the IEEE 802.15.4 MAC performance in the presence of hidden nodes. Specifically, simulation results show that it is the random backoff exponent that is of paramount importance for resolving collisions and not the number of times the channel is sensed before transmitting. However, the random backoff is ineffective in the presence of hidden nodes. The proposed design uses a new algorithm to increase the sensing coverage area, and therefore greatly reduces the chance of packet collisions due to hidden nodes. Moreover, the design uses a new dynamic transmission power control (TPC) to further reduce energy consumption and interference. The above proposed changes can smoothly coexist with the legacy 802.15.4 CSMA/CA. Finally, an improved two dimensional discrete time Markov chain model is proposed to capture the performance of the slotted 802.15.4 CSMA/CA. This model rectifies minor issues apparent in previous studies. The relationship derived for the successful transmission probability, throughput and average energy consumption, will provide better performance predictions. It will also offer greater insight into the strengths and weaknesses of the MAC operation, and possible enhancement opportunities. Overall, the work presented in this thesis provides several significant insights into WSN performance improvements with both existing protocols and newly designed protocols. Finally, some of the numerous challenges for future research are described

Advanced Trends in Wireless Communications

Physical limitations on wireless communication channels impose huge challenges to reliable communication. Bandwidth limitations, propagation loss, noise and interference make the wireless channel a narrow pipe that does not readily accommodate rapid flow of data. Thus, researches aim to design systems that are suitable to operate in such channels, in order to have high performance quality of service. Also, the mobility of the communication systems requires further investigations to reduce the complexity and the power consumption of the receiver. This book aims to provide highlights of the current research in the field of wireless communications. The subjects discussed are very valuable to communication researchers rather than researchers in the wireless related areas. The book chapters cover a wide range of wireless communication topics

Diseño y desarrollo del sistema de comunicaciones inalámbrico de un enjambre de UAV`S colaborativos

[Resumen] La Inteligencia Colectiva, dentro del campo de la Inteligencia Computacional, aborda temas de estudio como el comportamiento de los agentes individuales dentro de un sistema global y la asociación de la información para la resolución conjunta de problemas complejos. Dentro de la línea de investigación de Inteligencia Computacional e Inteligencia Colectiva, el Grupo Integrado de Ingeniería (GII) ha propuesto como proyecto de estudio el abordar un análisis exhaustivo de las tecnologías IoT de comunicación existentes, con el fin de adoptar la más adecuada a los requerimientos e incorporarla a un modelo de enjambre de UAV’s colaborativos. Las características más valoradas a la hora de la adopción del sistema serán las inherentes a los UAV’s, como son el alcance o la eficiencia energética, además de obtener las mejores prestaciones a la hora de establecer el radioenlace, como obtener el máximo ancho de banda, optimización de latencias y ciclos de CPU y la mayor inmunidad posible frente a interferencias. Una vez elegido el sistema, se tratará de optimizar para su uso en UAV’s y se realizarán pruebas de vuelo en escenarios reales para obtener datos específicos sobre consumo energético, rendimiento y alcance máximo.Traballo fin de mestrado (UDC.EPS). Enxeñaría industrial. Curso 2016/201