Enabling Hardware Green Internet of Things: A review of Substantial Issues

Between now and the near future, the Internet of Things (IoT) will redesign the socio-ecological morphology of the human terrain. The IoT ecosystem deploys diverse sensor platforms connecting millions of heterogeneous objects through the Internet. Irrespective of sensor functionality, most sensors are low energy consumption devices and are designed to transmit sporadically or continuously. However, when we consider the millions of connected sensors powering various user applications, their energy efficiency (EE) becomes a critical issue. Therefore, the importance of EE in IoT technology, as well as the development of EE solutions for sustainable IoT technology, cannot be overemphasised. Propelled by this need, EE proposals are expected to address the EE issues in the IoT context. Consequently, many developments continue to emerge, and the need to highlight them to provide clear insights to researchers on eco-sustainable and green IoT technologies becomes a crucial task. To pursue a clear vision of green IoT, this study aims to present the current state-of-the art insights into energy saving practices and strategies on green IoT. The major contribution of this study includes reviews and discussions of substantial issues in the enabling of hardware green IoT, such as green machine to machine, green wireless sensor networks, green radio frequency identification, green microcontroller units, integrated circuits and processors. This review will contribute significantly towards the future implementation of green and eco-sustainable IoT

Energy aware optimization for low power radio technologies

The explosive growth of IoT is pushing the market towards cheap, very low power devices with a strong focus on miniaturization, for applications such as in-body sensors, personal health monitoring and microrobots. Proposing procedures for energy efficiency in IoT is a difficult task, as it is a rapidly growing market comprised of many and very diverse product categories using technologies that are not stable, evolving at a high pace. The research in this field proposes solutions that go from physical layer optimization up to the network layer, and the sensor network designer has to select the techniques that are best for its application specific architecture and radio technology used. This work is focused on exploring new techniques for enhancing the energy efficiency and user experience of IoT networks. We divide the proposed techniques in frame and chip level optimization techniques, respectively. While the frame level techniques are meant to improve the performance of existing radio technologies, the chip level techniques aim at replacing them with crystal-free architectures. The identified frame level techniques are the use of preamble authentication and packet fragmentation, advisable for Low Power Wide Area Networks (LPWANs), a technology that offers the lowest energy consumption per provided service, but is vulnerable in front of energy exhaustion attacks and does not perform well in dense networks. The use of authenticated preambles between the sensors and gateways becomes a defence mechanism against the battery draining intended by attackers. We show experimentally that this approach is able to reduce with 91% the effect of an exhaustion attack, increasing the device's lifetime from less than 0.24 years to 2.6 years. The experiments were conducted using Loadsensing sensor nodes, commercially used for critical infrastructure control and monitoring. Even if exemplified on LoRaWAN, the use of preamble authentication is extensible to any wireless protocol. The use of packet fragmentation despite the packet fits the frame, is shown to reduce the probability of collisions while the number of users in the duty-cycle restricted network increases. Using custom-made Matlab simulations, important goodput improvement was obtained with fragmentation, with higher impact in slower and denser networks. Using NS3 simulations, we showed that combining packet fragmentation with group NACK can increase the network reliability, while reducing the energy consumed for retransmissions, at the cost of adding small headers to each fragment. It is a strategy that proves to be effective in dense duty-cycle restricted networks only, where the headers overhead is negligible compared to the network traffic. As a chip level technique, we consider using radios for communication that do not use external frequency references such as crystal oscillators. This would enable having all sensor's elements on a single piece of silicon, rendering it even ten times more energy efficient due to the compactness of the chip. The immediate consequence is the loss of communication accuracy and ability to easily switch communication channels. In this sense, we propose a sequence of frequency synchronization algorithms and phases that have to be respected by a crystal-free device so that it can be able to join a network by finding the beacon channel, synthesize all communication channels and then maintain their accuracy against temperature change. The proposed algorithms need no additional network overhead, as they are using the existing network signaling. The evaluation is made in simulations and experimentally on a prototype implementation of an IEEE802.15.4 crystal-free radio. While in simulations we are able to change to another communication channel with very good frequency accuracy, the results obtained experimentally show an initial accuracy slightly above 40ppm, which will be later corrected by the chip to be below 40 ppm.El crecimiento significativo de la IoT está empujando al mercado hacia el desarrollo de dispositivos de bajo coste, de muy bajo consumo energético y con un fuerte enfoque en la miniaturización, para aplicaciones que requieran sensores corporales, monitoreo de salud personal y micro-robots. La investigación en el campo de la eficiencia energética en la IoT propone soluciones que van desde la optimización de la capa física hasta la capa de red. Este trabajo se centra en explorar nuevas técnicas para mejorar la eficiencia energética y la experiencia del usuario de las redes IoT. Dividimos las técnicas propuestas en técnicas de optimización de nivel de trama de red y chip, respectivamente. Si bien las técnicas de nivel de trama están destinadas a mejorar el rendimiento de las tecnologías de radio existentes, las técnicas de nivel de chip tienen como objetivo reemplazarlas por arquitecturas que no requieren de cristales. Las técnicas de nivel de trama desarrolladas en este trabajo son el uso de autenticación de preámbulos y fragmentación de paquetes, aconsejables para redes LPWAN, una tecnología que ofrece un menor consumo de energía por servicio prestado, pero es vulnerable frente a los ataques de agotamiento de energía y no escalan frente la densificación. El uso de preámbulos autenticados entre los sensores y las pasarelas de enlace se convierte en un mecanismo de defensa contra el agotamiento del batería previsto por los atacantes. Demostramos experimentalmente que este enfoque puede reducir con un 91% el efecto de un ataque de agotamiento, aumentando la vida útil del dispositivo de menos de 0.24 años a 2.6 años. Los experimentos se llevaron a cabo utilizando nodos sensores de detección de carga, utilizados comercialmente para el control y monitoreo de infrastructura crítica. Aunque la técnica se ejemplifica en el estándar LoRaWAN, el uso de autenticación de preámbulo es extensible a cualquier protocolo inalámbrico. En esta tesis se muestra también que el uso de la fragmentación de paquetes a pesar de que el paquete se ajuste a la trama, reduce la probabilidad de colisiones mientras aumenta el número de usuarios en una red con restricciones de ciclos de transmisión. Mediante el uso de simulaciones en Matlab, se obtiene una mejora importante en el rendimiento de la red con la fragmentación, con un mayor impacto en redes más lentas y densas. Usando simulaciones NS3, demostramos que combinar la fragmentación de paquetes con el NACK en grupo se puede aumentar la confiabilidad de la red, al tiempo que se reduce la energía consumida para las retransmisiones, a costa de agregar pequeños encabezados a cada fragmento. Como técnica de nivel de chip, consideramos el uso de radios para la comunicación que no usan referencias de frecuencia externas como los osciladores basados en un cristal. Esto permitiría tener todos los elementos del sensor en una sola pieza de silicio, lo que lo hace incluso diez veces más eficiente energéticamente debido a la integración del chip. La consecuencia inmediata, en el uso de osciladores digitales en vez de cristales, es la pérdida de precisión de la comunicación y la capacidad de cambiar fácilmente los canales de comunicación. En este sentido, proponemos una secuencia de algoritmos y fases de sincronización de frecuencia que deben ser respetados por un dispositivo sin cristales para que pueda unirse a una red al encontrar el canal de baliza, sintetizar todos los canales de comunicación y luego mantener su precisión contra el cambio de temperatura. Los algoritmos propuestos no necesitan una sobrecarga de red adicional, ya que están utilizando la señalización de red existente. La evaluación se realiza en simulaciones y experimentalmente en una implementación prototipo de una radio sin cristal IEEE802.15.4. Los resultados obtenidos experimentalmente muestran una precisión inicial ligeramente superior a 40 ppm, que luego será corregida por el chip para que sea inferior a 40 ppm.Postprint (published version

Energy-Sustainable IoT Connectivity: Vision, Technological Enablers, Challenges, and Future Directions

Technology solutions must effectively balance economic growth, social equity, and environmental integrity to achieve a sustainable society. Notably, although the Internet of Things (IoT) paradigm constitutes a key sustainability enabler, critical issues such as the increasing maintenance operations, energy consumption, and manufacturing/disposal of IoT devices have long-term negative economic, societal, and environmental impacts and must be efficiently addressed. This calls for self-sustainable IoT ecosystems requiring minimal external resources and intervention, effectively utilizing renewable energy sources, and recycling materials whenever possible, thus encompassing energy sustainability. In this work, we focus on energy-sustainable IoT during the operation phase, although our discussions sometimes extend to other sustainability aspects and IoT lifecycle phases. Specifically, we provide a fresh look at energy-sustainable IoT and identify energy provision, transfer, and energy efficiency as the three main energy-related processes whose harmonious coexistence pushes toward realizing self-sustainable IoT systems. Their main related technologies, recent advances, challenges, and research directions are also discussed. Moreover, we overview relevant performance metrics to assess the energy-sustainability potential of a certain technique, technology, device, or network and list some target values for the next generation of wireless systems. Overall, this paper offers insights that are valuable for advancing sustainability goals for present and future generations.Comment: 25 figures, 12 tables, submitted to IEEE Open Journal of the Communications Societ

Energy harvesting methods for transmission lines: a comprehensive review

Humanity faces important challenges concerning the optimal use, security, and availability of energy systems, particularly electrical power systems and transmission lines. In this context, data-driven predictive maintenance plans make it possible to increase the safety, stability, reliability, and availability of electrical power systems. In contrast, strategies such as dynamic line rating (DLR) make it possible to optimize the use of power lines. However, these approaches require developing monitoring plans based on acquiring electrical data in real-time using different types of wireless sensors placed in strategic locations. Due to the specific conditions of the transmission lines, e.g., high electric and magnetic fields, this a challenging problem, aggravated by the harsh outdoor environments where power lines are built. Such sensors must also incorporate an energy harvesting (EH) unit that supplies the necessary electronics. Therefore, the EH unit plays a key role, so when designing such electronic systems, care must be taken to select the most suitable EH technology, which is currently evolving rapidly. This work reviews and analyzes the state-of-the-art technology for EH focused on transmission lines, as it is an area with enormous potential for expansion. In addition to recent advances, it also discusses the research needs and challenges that need to be addressed. Despite the importance of this topic, there is still much to investigate, as this area is still in its infancy. Although EH systems for transmission lines are reviewed, many other applications could potentially benefit from introducing wireless sensors with EH capabilities, such as power transformers, distribution switches, or low- and medium-voltage power lines, among others.This research was funded by Ministerio de Ciencia e Innovación de España, grant number PID2020-114240RB-I00 and by the Generalitat de Catalunya, grant number 2017 SGR 967.Peer ReviewedPostprint (author's final draft

Toward End-to-End, Full-Stack 6G Terahertz Networks

Recent evolutions in semiconductors have brought the terahertz band in the spotlight as an enabler for terabit-per-second communications in 6G networks. Most of the research so far, however, has focused on understanding the physics of terahertz devices, circuitry and propagation, and on studying physical layer solutions. However, integrating this technology in complex mobile networks requires a proper design of the full communication stack, to address link- and system-level challenges related to network setup, management, coordination, energy efficiency, and end-to-end connectivity. This paper provides an overview of the issues that need to be overcome to introduce the terahertz spectrum in mobile networks, from a MAC, network and transport layer perspective, with considerations on the performance of end-to-end data flows on terahertz connections.Comment: Published on IEEE Communications Magazine, THz Communications: A Catalyst for the Wireless Future, 7 pages, 6 figure

Reliability performance analysis of half-duplex and full-duplex schemes with self-energy recycling

Abstract. Radio frequency energy harvesting (EH) has emerged as a promising option for improving the energy efficiency of current and future networks. Self-energy recycling (sER), as a variant of EH, has also appeared as a suitable alternative that allows to reuse part of the transmitted energy via an energy loop. In this work we study the benefits of using sER in terms of reliability improvements and compare the performance of full-duplex (FD) and half-duplex (HD) schemes when using multi-antenna techniques at the base station side. We also assume a model for the hardware energy consumption, making the analysis more realistic since most works only consider the energy spent on transmission. In addition to spectral efficiency enhancements, results show that FD performs better than HD in terms of reliability. We maximize the outage probability of the worst link in the network using a dynamic FD scheme where a small base station (SBS) determines the optimal number of antennas for transmission and reception. This scheme proves to be more efficient than classical HD and FD modes. Results show that the use of sER at the SBS introduces changes on the distribution of antennas for maximum fairness when compared to the setup without sER. Moreover, we determine the minimum number of active radio frequency chains required at the SBS in order to achieve a given reliability target

Building a green connected future: smart (Internet of) Things for smart networks

The vision of Internet of Things (IoT) promises to reshape society by creating a future where we will be surrounded by a smart environment that is constantly aware of the users and has the ability to adapt to any changes. In the IoT, a huge variety of smart devices is interconnected to form a network of distributed agents that continuously share and process information. This communication paradigm has been recognized as one of the key enablers of the rapidly emerging applications that make up the fabric of the IoT. These networks, often called wireless sensor networks (WSNs), are characterized by the low cost of their components, their pervasive connectivity, and their self-organization features, which allow them to cooperate with other IoT elements to create large-scale heterogeneous information systems. However, a number of considerable challenges is arising when considering the design of large-scale WSNs. In particular, these networks are made up by embedded devices that suffer from severe power constraints and limited resources. The advent of low-power sensor nodes coupled with intelligent software and hardware technologies has led to the era of green wireless networks. From the hardware perspective, green sensor nodes are endowed with energy scavenging capabilities to overcome energy-related limitations. They are also endowed with low-power triggering techniques, i.e., wake-up radios, to eliminate idle listening-induced communication costs. Green wireless networks are considered a fundamental vehicle for enabling all those critical IoT applications where devices, for different reasons, do not carry batteries, and that therefore only harvest energy and store it for future use. These networks are considered to have the potential of infinite lifetime since they do not depend on batteries, or on any other limited power sources. Wake-up radios, coupled with energy provisioning techniques, further assist on overcoming the physical constraints of traditional WSNs. In addition, they are particularly important in green WSNs scenarios in which it is difficult to achieve energy neutrality due to limited harvesting rates. In this PhD thesis we set to investigate how different data forwarding mechanisms can make the most of these green wireless networks-enabling technologies, namely, energy harvesting and wake-up radios. Specifically, we present a number of cross-layer routing approaches with different forwarding design choices and study their consequences on network performance. Among the most promising protocol design techniques, the past decade has shown the increasingly intensive adoption of techniques based on various forms of machine learning to increase and optimize the performance of WSNs. However, learning techniques can suffer from high computational costs as nodes drain a considerable percentage of their energy budget to run sophisticated software procedures, predict accurate information and determine optimal decision. This thesis addresses also the problem of local computational requirements of learning-based data forwarding strategies by investigating their impact on the performance of the network. Results indicate that local computation can be a major source of energy consumption; it’s impact on network performance should not be neglected