Wireless industrial monitoring and control networks: the journey so far and the road ahead

While traditional wired communication technologies have played a crucial role in industrial monitoring and control networks over the past few decades, they are increasingly proving to be inadequate to meet the highly dynamic and stringent demands of today’s industrial applications, primarily due to the very rigid nature of wired infrastructures. Wireless technology, however, through its increased pervasiveness, has the potential to revolutionize the industry, not only by mitigating the problems faced by wired solutions, but also by introducing a completely new class of applications. While present day wireless technologies made some preliminary inroads in the monitoring domain, they still have severe limitations especially when real-time, reliable distributed control operations are concerned. This article provides the reader with an overview of existing wireless technologies commonly used in the monitoring and control industry. It highlights the pros and cons of each technology and assesses the degree to which each technology is able to meet the stringent demands of industrial monitoring and control networks. Additionally, it summarizes mechanisms proposed by academia, especially serving critical applications by addressing the real-time and reliability requirements of industrial process automation. The article also describes certain key research problems from the physical layer communication for sensor networks and the wireless networking perspective that have yet to be addressed to allow the successful use of wireless technologies in industrial monitoring and control networks

A Survey of Applying Ad Hoc Wireless Sensor Actuator Networks to Enhance Context-Awareness in Environmental Management Systems

Sensor mesh networking is set to be one of the key tools for the future of Ambient Intelligence (AmI) due to new emerging technologies in Ad hoc Wireless Sensor Networks (AWSNs). AWSNs symbolize the new generation of sensor networks with many promising advantages applicable to most networked environments. Unfortunately, however, these practical technologies have some technical problems and, as a consequence, this fascinating field has created novel and interesting challenges, which in turn, have inspired many ongoing research projects and more are likely to follow. Almost certainly, there will be notable improvements in the management of control/actuator networks as a consequence of enhancing the sensitivity capabilities of systems. With an emphasis on Ad hoc Wireless Sensor Actuator Networks (AWSANs) this study presents a systematic analysis of the different existing techniques to improve such systems. It also discusses, analyzes and summarizes the advantages these technologies offer in certain applications and presents a generic solution, in the form of a case study, for an AmI system to enhance the overall environmental management of a campus based on a hierarchical network using an AWSAN

Fuzzy Logic Control Based QoS Management in Wireless Sensor/Actuator Networks

Wireless sensor/actuator networks (WSANs) are emerging rapidly as a new generation of sensor networks. Despite intensive research in wireless sensor networks (WSNs), limited work has been found in the open literature in the field of WSANs. In particular, quality-of-service (QoS) management in WSANs remains an important issue yet to be investigated. As an attempt in this direction, this paper develops a fuzzy logic control based QoS management (FLC-QM) scheme for WSANs with constrained resources and in dynamic and unpredictable environments. Taking advantage of the feedback control technology, this scheme deals with the impact of unpredictable changes in traffic load on the QoS of WSANs. It utilizes a fuzzy logic controller inside each source sensor node to adapt sampling period to the deadline miss ratio associated with data transmission from the sensor to the actuator. The deadline miss ratio is maintained at a pre-determined desired level so that the required QoS can be achieved. The FLC-QM has the advantages of generality, scalability, and simplicity. Simulation results show that the FLC-QM can provide WSANs with QoS support.Comment: 13 pages, 8 figures; Open Access at http://www.mdpi.org/sensor

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

Robotic ubiquitous cognitive ecology for smart homes

Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent- based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feed- back received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work

The Bus Goes Wireless: Routing-Free Data Collection with QoS Guarantees in Sensor Networks

Abstract—We present the low-power wireless bus (LWB), a new communication paradigm for QoS-aware data collection in lowpower sensor networks. The LWB maps all communication onto network floods by using Glossy, an efficient flooding architecture for wireless sensor networks. Therefore, unlike current solutions, the LWB requires no information of the network topology, and inherently supports networks with mobile nodes and multiple data sinks. A LWB prototype implemented in Contiki guarantees bounded end-to-end communication delay and duplicate-free, inorder packet delivery—key QoS requirements in many control and mission-critical applications. Experiments on two testbeds demonstrate that the LWB prototype outperforms state-of-theart data collection and link layer protocols, in terms of reliability and energy efficiency. For instance, we measure an average radio duty cycle of 1.69 % and an overall data yield of 99.97 % in a typical data collection scenario with 85 sensor nodes on Twist. I

A survey on data storage and information discovery in the WSANs-based edge computing systems

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. In the post-Cloud era, the proliferation of Internet of Things (IoT) has pushed the horizon of Edge computing, which is a new computing paradigm with data are processed at the edge of the network. As the important systems of Edge computing, wireless sensor and actuator networks (WSANs) play an important role in collecting and processing the sensing data from the surrounding environment as well as taking actions on the events happening in the environment. In WSANs, in-network data storage and information discovery schemes with high energy efficiency, high load balance and low latency are needed because of the limited resources of the sensor nodes and the real-time requirement of some specific applications, such as putting out a big fire in a forest. In this article, the existing schemes of WSANs on data storage and information discovery are surveyed with detailed analysis on their advancements and shortcomings, and possible solutions are proposed on how to achieve high efficiency, good load balance, and perfect real-time performances at the same time, hoping that it can provide a good reference for the future research of the WSANs-based Edge computing systems

Simulating sensor networks

Tese de mestrado em Informática, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2010Nos últimos anos, as redes de sensores sem fios conheceram um grande impulso em variadas ´áreas, nomeadamente na monitorização industrial e ambiental e, mais recentemente, na logística e noutras aplicações que envolvem processos de negócio e a chamada Internet das Coisas e dos Serviços. Contudo, e apesar dos avanços que se têm verificado tanto em termos de hardware como de software, estas redes são difíceis de programar, testar e instalar. A simulação de redes de sensores é frequentemente utilizada para testar e depurar aplicações para redes de sensores, pois permite testar a execução de das aplicações em ambientes virtuais. Esta tese aborda um problema que diz respeito a testar estas redes através de simulação: a definição (manual) de modelos. A nossa abordagem aponta para a geração de modelos de simulação directamente a partir de aplicações redes de sensores, em particular, modelos para o simulador VisualSense criados a partir de aplicações escritas em Callas, uma linguagem de programação para as redes de sensores. Para tal, criamos uma ferramenta capaz de gerar modelos que ´e paramétrica pelos modelos de rede e modelos sensores da rede que se pretende modelar, e ainda por um conjunto extensível de parâmetros de simulação. As nossas experiências mostraram resultados encorajadores na simulação de redes de grande escala, uma vez que conseguimos executar simulações com até 5000 nós. À medida que as redes de sensores sem fios começam a ser utilizadas em processos de negócio, a informação que recolhem do ambiente tem cada vez mais influência no decurso dos fluxos de trabalho associados aos processos de negócio. De um modo geral, os testes levados a cabo em fluxos de trabalho fazem uso de informação gravada em fluxos de trabalho executados previamente, tornando difícil testar o sistema como um todo. Em alternativa, e como uma segunda proposta desta tese, propomos testar fluxos de trabalho através da incorporação de resultados obtidos nas simulações das aplicações das redes de sensores. Além de cobrir os casos cobertos pela primeira abordagem, esta técnica permite testar novos fluxos de trabalho, bem como as mudanças ocorridas num determinado fluxo de trabalho por acontecimentos no ambiente.In recent years, Wireless Sensor Networks have gaining momentum in several fields, notably in industrial and environmental monitoring and, more recently, in logistics. However, and in spite of the advances in hardware and software, Wireless Sensor Networks are still hard to program, test, and deploy. Simulation is often used for testing and debugging sensor networks because they allow us to perform deployments in virtual environments. This paper addresses a key problem of testing such networks using simulation: (manual) model definition. Our approach is to generate simulation models directly from WSN applications, in particular, VisualSense simulator models from applications written in Callas, a programming language for WSN. For that purpose, we create a model generator tool that is parameter sable by network and sensor templates, and by an extensible set of simulation parameters. Our experiments show encouraging results on simulating large scale networks, as we are able to handle WSN with as many as 5000 nodes. As Wireless Sensor Networks begin to play some role in business processes, the information they gather from the environment influences the execution of workflows. Generally, the tests carried out on these systems make use of recorded information in earlier workflow executions, making it difficult to test the system as a whole. Alternatively, and as a second proposal of this thesis, we propose testing such workflows by incorporating results obtained from the simulation of sensor network applications. Besides covering the situations described in the first approach, this technique allows the testing of new workflows, as well as the changes made to a given workflow by events in the environment

Real-Time and Energy-Efficient Routing for Industrial Wireless Sensor-Actuator Networks

With the emergence of industrial standards such as WirelessHART, process industries are adopting Wireless Sensor-Actuator Networks (WSANs) that enable sensors and actuators to communicate through low-power wireless mesh networks. Industrial monitoring and control applications require real-time communication among sensors, controllers and actuators within end-to-end deadlines. Deadline misses may lead to production inefficiency, equipment destruction to irreparable financial and environmental impacts. Moreover, due to the large geographic area and harsh conditions of many industrial plants, it is labor-intensive or dan- gerous to change batteries of field devices. It is therefore important to achieve long network lifetime with battery-powered devices. This dissertation tackles these challenges and make a series of contributions. (1) We present a new end-to-end delay analysis for feedback control loops whose transmissions are scheduled based on the Earliest Deadline First policy. (2) We propose a new real-time routing algorithm that increases the real-time capacity of WSANs by exploiting the insights of the delay analysis. (3) We develop an energy-efficient routing algorithm to improve the network lifetime while maintaining path diversity for reliable communication. (4) Finally, we design a distributed game-theoretic algorithm to allocate sensing applications with near-optimal quality of sensing

Clustering objectives in wireless sensor networks: A survey and research direction analysis

Wireless Sensor Networks (WSNs) typically include thousands of resource-constrained sensors to monitor their surroundings, collect data, and transfer it to remote servers for further processing. Although WSNs are considered highly flexible ad-hoc networks, network management has been a fundamental challenge in these types of net- works given the deployment size and the associated quality concerns such as resource management, scalability, and reliability. Topology management is considered a viable technique to address these concerns. Clustering is the most well-known topology management method in WSNs, grouping nodes to manage them and/or executing various tasks in a distributed manner, such as resource management. Although clustering techniques are mainly known to improve energy consumption, there are various quality-driven objectives that can be realized through clustering. In this paper, we review comprehensively existing WSN clustering techniques, their objectives and the network properties supported by those techniques. After refining more than 500 clustering techniques, we extract about 215 of them as the most important ones, which we further review, catergorize and classify based on clustering objectives and also the network properties such as mobility and heterogeneity. In addition, statistics are provided based on the chosen metrics, providing highly useful insights into the design of clustering techniques in WSNs.publishedVersio