On the use of IEEE 802.15.4/Zigbee for time-sensitive wireless sensor network applications

Mestrado em Engenharia Electrotécnica e de ComputadoresRecent advancements in information and communication technologies are paving the way for new paradigms in embedded computing systems. This, allied with an increasing eagerness for monitoring and controlling everything, everywhere, is pushing forward the design of new Wireless Sensor Network (WSN) infrastructures that will tightly interact with the physical environment, in a ubiquitous and pervasive fashion. Such cyber-physical systems require a rethinking of the usual computing and networking concepts, and given that the computing entities closely interact with their environment, timeliness is of increasing importance. This Thesis addresses the use of standard protocols, particularly IEEE 802.15.4 and ZigBee, combined with commercial technologies as a baseline to enable WSN infrastructures capable of supporting the Quality of Service (QoS) requirements (specially timeliness and system lifetime) that future large-scale networked embedded systems will impose. With this purpose, in this Thesis we start by evaluating the network performance of the IEEE 802.15.4 Slotted CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance) mechanism for different parameter settings, both through simulation and through an experimental testbed. In order to improve the performance of these networks (e.g. throughput, energyefficiency, message delay) against the hidden-terminal problem, a mechanism to mitigate it was implemented and experimentally validated. The effectiveness of this mechanism was also demonstrated in a real application scenario, featuring a target tracking application. A methodology for modelling cluster-tree WSNs and computing the worst-case endto-end delays, buffering and bandwidth requirements was tested and validated experimentally. This work is of paramount importance to understand the behaviour of WSNs under worst-case conditions and also to make the appropriate network settings. Our experimental work enabled us to identify a number of technological constrains, namely related to hardware/software and to the Open-ZB implementation in TinyOS. In this line, a new implementation effort was triggered to port the Open-ZB IEEE 802.15.4/ZigBee protocol stack to the ERIKA real-time operating system. This implementation was validated experimentally and its behaviour compared with the TinyOS–based implementation.Os últimos avanços nas tecnologias de informação e comunicação (ICTs) estão a abrir caminho para novos paradigmas de sistemas computacionais embebidos. Este facto, aliado à tendência crescente em monitorizar e controlar tudo, em qualquer lugar, está a alimentar o desenvolvimento de novas infra-estruturas de Redes de Sensores Sem Fios (WSNs), que irão interagir intimamente com o mundo físico de uma forma ubíqua. Este género de sistemas ciber-físicos de grande escala, requer uma reflexão sobre os conceitos de redes e de computação tradicionais, e tendo em conta a proximidade que estas entidades partilham com ambiente envolvente, o seu comportamento temporal é de acrescida importância. Esta Tese endereça a utilização de protocolos normalizados, em particular do IEEE 802.15.4 e ZigBee em conjunto com tecnologias comerciais, para desenvolver infraestruturas WSN capazes de responder aos requisitos de Qualidade de Serviço (QoS) (especialmente em termos de comportamento temporal e tempo de vida do sistema), que os futuros sistemas embebidos de grande escala deverão exigir. Com este propósito, nesta Tese começamos por analisar a performance do mecanismo de Slotted CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance) do IEEE 802.15.4 para diferentes parâmetros, através de simulação e experimentalmente. De modo a melhorar a performance destas redes (ex. throughput, eficiência energética, atrasos) em cenários que contenham nós escondidos (hidden-nodes), foi implementado e validado experimentalmente um mecanismo para eliminar este problema. A eficácia deste mecanismo foi também demonstrada num cenário aplicacional real. Foi testada e validada uma metodologia para modelizar uma WSN em cluster-tree e calcular os piores atrasos das mensagens, necessidades de buffering e de largura de banda. Este trabalho foi de grande importância para compreender o comportamento deste tipo de redes para condições de utilização limite e para as configurar a priori. O nosso trabalho experimental permitiu identificar uma série de limitações tecnológicas, nomeadamente relacionadas com hardware/software e outras relacionadas com a implementação do Open-ZB em TinyOS. Isto desencadeou a migração da pilha protocolar IEEE 802.15.4/ZigBee Open-ZB para o ERIKA, um sistema operativo de tempo-real. Esta implementação foi validada experimentalmente e o seu comportamento comparado com o da implementação baseada em TinyOS

Energy Harvesting Techniques for Internet of Things (IoT)

The rapid growth of the Internet of Things (IoT) has accelerated strong interests in the development of low-power wireless sensors. Today, wireless sensors are integrated within IoT systems to gather information in a reliable and practical manner to monitor processes and control activities in areas such as transportation, energy, civil infrastructure, smart buildings, environment monitoring, healthcare, defense, manufacturing, and production. The long-term and self-sustainable operation of these IoT devices must be considered early on when they are designed and implemented. Traditionally, wireless sensors have often been powered by batteries, which, despite allowing low overall system costs, can negatively impact the lifespan and the performance of the entire network they are used in. Energy Harvesting (EH) technology is a promising environment-friendly solution that extends the lifetime of these sensors, and, in some cases completely replaces the use of battery power. In addition, energy harvesting offers economic and practical advantages through the optimal use of energy, and the provisioning of lower network maintenance costs. We review recent advances in energy harvesting techniques for IoT. We demonstrate two energy harvesting techniques using case studies. Finally, we discuss some future research challenges that must be addressed to enable the large-scale deployment of energy harvesting solutions for IoT environments

On the use of IEEE 802.15.4/ZigBee as federating communication protocols for Wireless Sensor Networks

Tese de mestrado. Redes e Serviços de Comunicação. Faculdade de Engenharia. Universidade do Porto, Instituto Superior de Engenharia. 200

Design of a low-voltage CMOS RF receiver for energy harvesting sensor node

In this thesis a CMOS low-power and low-voltage RF receiver front-end is presented. The main objective is to design this RF receiver so that it can be powered by a piezoelectric energy harvesting power source, included in a Wireless Sensor Node application. For this type of applications the major requirements are: the low-power and low-voltage operation, the reduced area and cost and the simplicity of the architecture. The system key blocks are the LNA and the mixer, which are studied and optimized with greater detail, achieving a good linearity, a wideband operation and a reduced introduction of noise. A wideband balun LNA with noise and distortion cancelling is designed to work at a 0.6 V supply voltage, in conjunction with a double-balanced passive mixer and subsequent TIA block. The passive mixer operates in current mode, allowing a minimal introduction of voltage noise and a good linearity. The receiver analog front-end has a total voltage conversion gain of 31.5 dB, a 0.1 - 4.3 GHz bandwidth, an IIP3 value of -1.35 dBm, and a noise figure lower than 9 dB. The total power consumption is 1.9 mW and the die area is 305x134.5 m2, using a standard 130 nm CMOS technology

An Internet of Things (IoT) based wide-area Wireless Sensor Network (WSN) platform with mobility support.

Wide-area remote monitoring applications use cellular networks or satellite links to transfer sensor data to the central storage. Remote monitoring applications uses Wireless Sensor Networks (WSNs) to accommodate more Sensor Nodes (SNs) and for better management. Internet of Things (IoT) network connects the WSN with the data storage and other application specific services using the existing internet infrastructure. Both cellular networks, such as the Narrow-Band IoT (NB-IoT), and satellite links will not be suitable for point-to-point connections of the SNs due to their lack of coverage, high cost, and energy requirement. Low Power Wireless Area Network (LPWAN) is used to interconnect all the SNs and accumulate the data to a single point, called Gateway, before sending it to the IoT network. WSN implements clustering of the SNs to increase the network coverage and utilizes multiple wireless links between the repeater nodes (called hops) to reach the gateway at a longer distance. Clustered WSN can cover up to a few km using the LPWAN technologies such as Zigbee using multiple hops. Each Zigbee link can be from 200 m to 500 m long. Other LPWAN technologies, such as LoRa, can facilitate an extended range from 1km to 15km. However, the LoRa will not be suitable for the clustered WSN due to its long Time on Air (TOA) which will introduce data transmission delay and become severe with the increase of hop count. Besides, a sensor node will need to increase the antenna height to achieve the long-range benefit of Lora using a single link (hop) instead of using multiple hops to cover the same range. With the increased WSN coverage area, remote monitoring applications such as smart farming may require mobile sensor nodes. This research focuses on the challenges to overcome LoRa’s limitations (long TOA and antenna height) and accommodation of mobility in a high-density and wide-area WSN for future remote monitoring applications. Hence, this research proposes lightweight communication protocols and networking algorithms using LoRa to achieve mobility, energy efficiency and wider coverage of up to a few hundred km for the WSN. This thesis is divided into four parts. It presents two data transmission protocols for LoRa to achieve a higher data rate and wider network coverage, one networking algorithm for wide-area WSN and a channel synchronization algorithm to improve the data rate of LoRa links. Part one presents a lightweight data transmission protocol for LoRa using a mobile data accumulator (called data sink) to increase the monitoring coverage area and data transmission energy efficiency. The proposed Lightweight Dynamic Auto Reconfigurable Protocol (LDAP) utilizes direct or single hop to transmit data from the SNs using one of them as the repeater node. Wide-area remote monitoring applications such as Water Quality Monitoring (WQM) can acquire data from geographically distributed water resources using LDAP, and a mobile Data Sink (DS) mounted on an Unmanned Aerial Vehicle (UAV). The proposed LDAP can acquire data from a minimum of 147 SNs covering 128 km in one direction reducing the DS requirement down to 5% comparing other WSNs using Zigbee for the same coverage area with static DS. Applications like smart farming and environmental monitoring may require mobile sensor nodes (SN) and data sinks (DS). The WSNs for these applications will require real-time network management algorithms and routing protocols for the dynamic WSN with mobility that is not feasible using static WSN technologies. This part proposes a lightweight clustering algorithm for the dynamic WSN (with mobility) utilizing the proposed LDAP to form clusters in real-time during the data accumulation by the mobile DS. The proposed Lightweight Dynamic Clustering Algorithm (LDCA) can form real-time clusters consisting of mobile or stationary SNs using mobile DS or static GW. WSN using LoRa and LDCA increases network capacity and coverage area reducing the required number of DS. It also reduces clustering energy to 33% and shows clustering efficiency of up to 98% for single-hop clustering covering 100 SNs. LoRa is not suitable for a clustered WSN with multiple hops due to its long TOA, depending on the LoRa link configurations (bandwidth and spreading factor). This research proposes a channel synchronization algorithm to improve the data rate of the LoRa link by combining multiple LoRa radio channels in a single logical channel. This increased data rate will enhance the capacity of the clusters in the WSN supporting faster clustering with mobile sensor nodes and data sink. Along with the LDCA, the proposed Lightweight Synchronization Algorithm for Quasi-orthogonal LoRa channels (LSAQ) facilitating multi-hop data transfer increases WSN capacity and coverage area. This research investigates quasi-orthogonality features of LoRa in terms of radio channel frequency, spreading factor (SF) and bandwidth. It derived mathematical models to obtain the optimal LoRa parameters for parallel data transmission using multiple SFs and developed a synchronization algorithm for LSAQ. The proposed LSAQ achieves up to a 46% improvement in network capacity and 58% in data rate compared with the WSN using the traditional LoRa Medium Access Control (MAC) layer protocols. Besides the high-density clustered WSN, remote monitoring applications like plant phenotyping may require transferring image or high-volume data using LoRa links. Wireless data transmission protocols used for high-volume data transmission using the link with a low data rate (like LoRa) requiring multiple packets create a significant amount of packet overload. Besides, the reliability of these data transmission protocols is highly dependent on acknowledgement (ACK) messages creating extra load on overall data transmission and hence reducing the application-specific effective data rate (goodput). This research proposes an application layer protocol to improve the goodput while transferring an image or sequential data over the LoRa links in the WSN. It uses dynamic acknowledgement (DACK) protocol for the LoRa physical layer to reduce the ACK message overhead. DACK uses end-of-transmission ACK messaging and transmits multiple packets as a block. It retransmits missing packets after receiving the ACK message at the end of multiple blocks. The goodput depends on the block size and the number of lossy packets that need to be retransmitted. It shows that the DACK LoRa can reduce the total ACK time 10 to 30 times comparing stop-wait protocol and ten times comparing multi-packet ACK protocol. The focused wide-area WSN and mobility requires different matrices to be evaluated. The performance evaluation matrices used for the static WSN do not consider the mobility and the related parameters, such as clustering efficiency in the network and hence cannot evaluate the performance of the proposed wide-area WSN platform supporting mobility. Therefore, new, and modified performance matrices are proposed to measure dynamic performance. It can measure the real-time clustering performance using the mobile data sink and sensor nodes, the cluster size, the coverage area of the WSN and more. All required hardware and software design, dimensioning, and performance evaluation models are also presented