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 new intra-cluster scheduling scheme for real-time flows in wireless sensor networks

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Real-time flows using time division multiple access (TDMA) scheduling in cluster-based wireless sensor networks try to schedule more flows per time frame to minimize the schedule length to meet the deadline. The problem with the previously used cluster-based scheduling algorithm is that intra-cluster scheduling does not consider that the clusters may have internal or outgoing flows. Thus, intra-cluster scheduling algorithms do not utilize their empty time-slots and thus increase schedule length. In this paper, we propose a new intra-cluster scheduling algorithm by considering that clusters may have having internal or outgoing flows. Thus, intra-cluster scheduling algorithms do not differentiate the intra-cluster time slots and utilize their empty time slots. The objective is to schedule more flows per time frame, to reduce schedule length and improve the acceptance rate of flows. Simulation results show that the acceptance rate of the proposed scheme has a higher performance than the previous scheme

Resource management algorithms for real-time wireless sensor networks with applications in cyber-physical systems

Wireless Sensor Networks (WSN) are playing a key role in the efficient operation of Cyber Physical Systems (CPS). They provide cost efficient solutions to current and future CPS re- quirements such as real-time structural awareness, faster event localization, cost reduction due to condition based maintenance rather than periodic maintenance, increased opportunities for real-time preventive or corrective control action and fine grained diagnostic analysis. However, there are several critical challenges in the real world applicability of WSN. The low power, low data rate characteristics of WSNs coupled with constraints such as application specified latency and wireless interference present challenges to their efficient integration in CPSs. The existing state of the art solutions lack methods to address these challenges that impediment the easy integration of WSN in CPS. This dissertation develops efficient resource management algorithms enabling WSNs to perform reliable, real-time, cost efficient monitoring. This research addresses three important problems in resource management in the presence of different constraints such as latency, precedence and wireless interference constraints. Additionally, the dissertation proposes a solution to deploy WSNs based real-time monitoring of critical infrastructure such as electrical overhead transmission lines. Firstly, design and analysis of an energy-aware scheduling algorithm encompassing both computation and communication subsystems in the presence of deadline, precedence and in- terference constraints is presented. The energy-delay tradeoff presented by the energy saving technologies such as Dynamic Voltage Scaling (DVS) and Dynamic modulation Scaling (DMS) is studied and methods to leverage it by way of efficient schedule construction is proposed. Performance results show that the proposed polynomial-time heuristic scheduling algorithm offers comparable energy savings to that of the analytically derived optimal solution. Secondly, design, analysis and evaluation of adaptive online algorithms leveraging run- time variations is presented. Specifically, two widely used medium access control schemes are considered and online algorithms are proposed for each. For one, temporal correlation in sensor measurements is exploited and three heuristics with varying complexities are proposed to perform energy minimization using DMS. For another, an adaptive algorithm is proposed addressing channel and load conditions at a node by influencing the selection of either low energy or low delay transmission option. In both cases, the simulation results show that the proposed schemes provide much better energy savings as compared to the existing algorithms. The third component presents design and evaluation of a WSN based framework to mon- itor a CPS namely, electrical overhead transmission line infrastructure. The cost optimized hybrid hierarchical network architecture is composed of a combination of wired, wireless and cellular technologies. The proposed formulation is generic and addresses constraints such as bandwidth and latency; and real world scenarios such as asymmetric sensor data generation, unreliable wireless link behavior, non-uniform cellular coverage and is suitable for cost minimized incremental future deployment. In conclusion, this dissertation addresses several challenging research questions in the area of resource management in WSNs and their applicability in future CPSs through associated algorithms and analyses. The proposed research opens up new avenues for future research such as energy management through network coding and fault diagnosis for reliable monitoring

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

EC-CENTRIC: An Energy- and Context-Centric Perspective on IoT Systems and Protocol Design

The radio transceiver of an IoT device is often where most of the energy is consumed. For this reason, most research so far has focused on low power circuit and energy efficient physical layer designs, with the goal of reducing the average energy per information bit required for communication. While these efforts are valuable per se, their actual effectiveness can be partially neutralized by ill-designed network, processing and resource management solutions, which can become a primary factor of performance degradation, in terms of throughput, responsiveness and energy efficiency. The objective of this paper is to describe an energy-centric and context-aware optimization framework that accounts for the energy impact of the fundamental functionalities of an IoT system and that proceeds along three main technical thrusts: 1) balancing signal-dependent processing techniques (compression and feature extraction) and communication tasks; 2) jointly designing channel access and routing protocols to maximize the network lifetime; 3) providing self-adaptability to different operating conditions through the adoption of suitable learning architectures and of flexible/reconfigurable algorithms and protocols. After discussing this framework, we present some preliminary results that validate the effectiveness of our proposed line of action, and show how the use of adaptive signal processing and channel access techniques allows an IoT network to dynamically tune lifetime for signal distortion, according to the requirements dictated by the application

Energy-efficient MAC protocols for wireless sensor networks: a survey

MAC Protocols enables sensor nodes of the same WSN to access a common shared communication channel. Many researchers have proposed different solutions explaining how to design and implement these protocols. The main goal of most MACs protocols is how to prolong lifetime of the WSN as long as possible by reducing energy consumption since it is often impossible to change or to recharge sensors’ batteries. The majority of these protocols designed for WSN are based on “duty-cycle” technique. Every node of the WSN operates on two periods: active period and sleep period to save energy. Until now (to our knowledge) there is no ideal protocol for this purpose. The main reason relies on the lack of standardization at lower layers (physical layer) and (physical) sensor hardware.  Therefore, the MAC protocol choice remains application-dependent. A useful MAC protocol should be able to adapt to network changes (topology, nodes density and network size). This paper surveys MAC protocols for WSNs and discusses the main characteristics, advantages and disadvantages of currently popular protocols

Industrial Wireless Sensor Networks

Wireless sensor networks are penetrating our daily lives, and they are starting to be deployed even in an industrial environment. The research on such industrial wireless sensor networks (IWSNs) considers more stringent requirements of robustness, reliability, and timeliness in each network layer. This Special Issue presents the recent research result on industrial wireless sensor networks. Each paper in this Special Issue has unique contributions in the advancements of industrial wireless sensor network research and we expect each paper to promote the relevant research and the deployment of IWSNs