Wireless Sensor And Actuator Networks Research Articles

Working, design issues and applications of wireless sensor network

Wireless sensor networks (WSN) also known as wireless sensor and actuator networks (WSAN). These are distributed autonomous sensors for monitoring environmental or physical conditions, like sound, temperature pressure, etc. and used for passing their data via the network to a main location. These are measurement tools which are equipped with transmitters for converting the signals into a radio transmission from process control instruments. Receiver interprets the radio signal after that converts the wireless signal to a desired or specific output, like a data or Analog current analysis via computer software.

Multi-Access Edge Computing assisted ultra-low energy scheduling and harvesting in multi-hop Wireless Sensor and Actuator Network for energy neutral self-sustainable Next-gen Cyber-Physical System

Energy Neutrality is the need of the hour for future Cyber-physical infrastructure. Many past research works suggest low duty cycle networking for energy-efficient wireless sensor network; however, research problem still persist as these proposals have some practical deployment bottlenecks like sleep-latency and may trade-off with data-fidelity and Quality-of-Service (QoS) parameters. The research objective of this work is to propose a novel design for wireless sensor–actuator mote system to minimize energy consumption and compensate with harvesting to achieve energy neutral operation in multi-hop Wireless Sensor and Actuator Network (WSAN); A network scenario that is much needed for Internet of Thing (IoT) applications in future ready Next-gen Cyber Physical System (NG-CPS). In this paper, we have proposed a novel state-of-the-art Multi-Access/Mobile Edge Computing (MEC) assisted Low-Duty-Cycle Scheduling of Trans-Receiver for Store-Process-Then-Forward (LDCS-TR-SPTF) scheme in multi-hop WSAN for reducing the overall energy consumption. In addition to energy conservation, we have also proposed a hybrid harvesting to compensate energy to achieve energy neutral self-sustainable NG-CPS. The proposed novel LDCS-TR-SPTF has been implemented on multiple custom-made sensor–actuator motes equipped with ARM-based System-on-Chip (SoC) and IEEE 802.11 network interface. These motes are working both as end-nodes and relay nodes in a multi-hop WSAN testbed scenario for testing and validation of our proposed scheme. The results are promising with an overall energy conservation of 49.1% using our novel LDCS-TR-SPTF in comparison to stock IEEE 802.11. We have implemented solar energy harvester on wireless sensor–actuator motes to compensate the reduced energy consumption and achieved complete energy-neutrality. Motes are completely energy-autonomous in multi-hop WSAN scenario by eliminating the need of access to external power-grid for future cyber–physical system.

Joint Optimization of Control Strategy and Energy Consumption for Energy Harvesting WSAN.

With the rapid development of wireless sensor technology, recent progress in wireless sensor and actuator networks (WSANs) with energy harvesting provide the possibility for various real-time applications. Meanwhile, extensive research activities are carried out in the fields of efficient energy allocation and control strategy design. However, the joint design considering physical plant control, energy harvesting, and consumption is rarely concerned in existing works. In this paper, in order to enhance system control stability and promote quality of service for the WSAN energy efficiency, a novel three-step joint optimization algorithm is proposed through control strategy and energy management analysis. First, the optimal sampling interval can be obtained based on energy harvesting, consumption, and remaining conditions. Then, the control gain for each sampling interval is derived by using a backward iteration. Finally, the optimal control strategy is determined as a linear function of the current plant states and previous control strategies. The application of UAV formation flight system demonstrates that better system performance and control stability can be achieved by the proposed joint optimization design for all poor, sufficient, and general energy harvesting scenarios.

Analysis of ADC Quantization and Clipping Effects on CDMA-OQAM-OFDM-Based WSAN

In this paper, the joint effect of quantization and clipping done by the Analog-to-Digital Converter (ADC) in the receiver of a Wireless Sensor and Actuator Network (WSAN) is investigated. As an Ultra Reliable Low-Latency Communication (URLLC) system, a combination of Code Division Multiple Access (CDMA) and Orthogonal Frequency Division Multiplexing (OFDM) that uses Offset Quadrature Amplitude Modulation (OQAM) is applied. It is shown that under an industrial Non-Line-Of-Sight (NLOS) channel, CDMA-OQAM-OFDM outperforms CDMA-OFDM when both transmissions are attacked by Random Frequency Hopping Jamming (RFHJ).

Splitting–merging-based automatic scheduling scheme for balancing energy consumption and task allocation in WSANs

In wireless sensor and actuator networks (WSANs), sensing region partition, task allocation, and collector schedule greatly affect the performance of WSANs. Specifically, nonuniform data aggregation causes unbalanced energy consumption, thereby reducing the network lifetime. Additionally, unbalanced allocation of data collection tasks of collectors increases the gathering delay. Thus, it is critical to balance the energy consumption of sensor nodes, as well as task allocation and scheduling with the limited number of collectors. This study proposes a novel splitting–merging-based automatic scheduling scheme to balance energy consumption and task allocation for WSANs. First, a sensing region splitting–merging scheme is proposed to make the data load uniform, in which the sensing region is self-organized into many subregions taking into account the maximum number of sensor nodes and the maximum distance between sensor nodes in each subregion. Second, a task allocation strategy based on genetic algorithm is proposed to optimize the number of collectors and uniformly assign tasks to collectors. Finally, the trajectory of each collector is optimized by applying ant colony optimization algorithm. Numerical experiments show that the proposed method outperforms well in terms of prolonging the network lifetime and reducing the gathering delay when compared with several related methods.

Learning‐based adaptive feedback control for tracking optimisation in wireless sensor actuator networking systems

In wireless sensor and actuator networks (WSAN), sensors can have much longer lifetime as mobile sink nodes move through the network and collect data from static sensor nodes. Applying mobile sinks in WSAN systems has faced challenges in sink path planning and data gathering scheduling. Many studies have focused on priori-trail planning for mobile sinks; however, they have not considered tracking performance degradation during operation due to system nonlinearities and uncertain WSAN environments. Thus, two learning-based adaptive feedback control methods, adaptive neural-network-based feedback control (ANNFC) and adaptive neural-network-based feedback control with integrator model (ANNFC-IM), are proposed to improve and optimise tracking performance in unknown and uncertain WSAN environments. The proposed algorithms enable a mobile sink to adjust its flying trajectory with online learning by applying a neural-network-based control method. The performance of the proposed algorithm is validated by theoretical analysis and simulation results. The results demonstrate that the proposed methods significantly outperform existing methods in terms of tracking error, system stability, and convergence.

Improved Joint Optimization Design for Wireless Sensor and Actuator Networks with Time Delay

With the rapid development of wireless communication technology, the newest development of wireless sensor and actuator networks (WSANs) provides significant potential applications for various real-time scenarios. Currently, extensive research activities have been carried out in the field of efficient resource management and control design. However, the stability of the controlled plant and the efficiency of network resources are rarely considered collaboratively in existing works. In this paper, in order to enhance the control stability and improve the power consumption efficiency for the WSAN, a novel three-step optimization algorithm jointly designing the control strategy and transmission path routing is proposed when the time delay is considered. First, the minimum hop routing algorithm is used to obtain the set of candidate transmission paths. Then, the optimal control signals for each candidate transmission path can be iteratively derived with a backward recursion method. Finally, the best transmission path is determined under the optimal control strategy to achieve the joint optimization design. The effectiveness of the proposed joint optimization algorithm is verified by the simulations of the application in the power grid system.

The DEWI High-Level Architecture: Wireless Sensor Networks in Industrial Applications

This paper presents the High-Level Architecture (HLA) of the European research project DEWI (Dependable Embedded Wireless Infrastructure). The objective of this HLA is to serve as a reference framework for the development of industrial Wireless Sensor and Actuator Networks (WSANs) based on the concept of the DEWI Bubble. The DEWI Bubble constitutes a set of architecture design rules and recommendations that can be used to integrate legacy industrial sensor networks with a modern, interoperable and flexible IoT (Internet-of-Things) infrastructure. The DEWI Bubble can be regarded as a high-level abstraction of an industrial WSAN with enhanced interoperability (via standardized interfaces), dependability, technology reusability and cross-domain development. The DEWI Bubble aims to resolve the issue on how to integrate commercial WSAN technology to match the dependability, interoperability and high criticality needs of industrial domains. This paper details the criteria used to design the HLA and the organization of the infrastructure internal and external to the DEWI Bubble. The description includes the different perspectives, models, or views of the architecture: the entity model, the layered perspective of the entity model and the functional model. This includes an overview of software and hardware interfaces. The DEWI HLA constitutes an extension of the ISO/IEC 29182 SNRA (Sensor Network Reference Architecture) towards the support of wireless industrial applications in different domains: aeronautics, automotive, railway and building. To improve interoperability with existing approaches, the DEWI HLA also reuses some features from other standardized technologies and architectures. The DEWI HLA and the concept of Bubble allow networks with different industrial sensor technologies to exchange information between them or with external clients via standard interfaces, thus providing consolidated access to sensor information of different industrial domains. This is an important aspect for smart city applications, Big Data, Industry 4.0 and the Internet-of-Things (IoT). The paper includes a non-exhaustive review of the state of the art of the different interfaces, protocols and standards of this architecture. The HLA has also been proposed as the basis of the European projects SCOTT (Secure Connected Trustable Things) for enhanced security and privacy in the IoT and InSecTT (Intelligent Secure Trustable Things) for the convergence of artificial intelligence (AI) and the IoT.

A Tabu list strategy based DQN for AAV mobility in indoor single-path environment: Implementation and performance evaluation

The Deep Q-Network (DQN) is one of the key methods in the deep reinforcement learning algorithm, which has a deep neural network structure used to estimate Q-values in Q-learning methods. We have previously implemented a simulation system considering DQN for control of actuator nodes in Wireless Sensor and Actuator Networks (WSANs). In addition, we have designed and implemented a DQN based Autonomous Aerial Vehicle (AAV) testbed. In this paper, we propose and evaluate a Tabu List Strategy based DQN (TLS-DQN) for AAV mobility control. For evaluation, we compared the simulation results of the mobility control of AAV in indoor single-path environment using normal DQN and the TLS-DQN. The simulation results show that the TLS-DQN has a better performance than the normal DQN.

Time Slotted Channel Hopping and ContikiMAC for IPv6 Multicast-Enabled Wireless Sensor Networks.

Smart buildings benefit from IEEE 802.15.4e time slotted channel hopping (TSCH) medium access for creating reliable and power aware wireless sensor and actuator networks (WSANs). As in these networks, sensors are supposed to communicate to each other and with actuators, IPv6 multicast forwarding is seen as a valuable means to reduce traffic. A promising approach to multicast, based on the Routing Protocol for Low Power and Lossy Networks (RPL) is Bidirectional Multicast RPL Forwarding (BMRF). This paper aimed to analyze the performance of BMRF over TSCH. The authors investigated how an adequate TSCH scheduler can help to achieve a requested quality of service (QoS). A theoretical model for the delay and energy consumption of BMRF over TSCH is presented. Next, BMRF’s link layer (LL) unicast and LL broadcast forwarding modes were analyzed on restricted and realistic topologies. On topologies with increased interference, BMRF’s LL broadcast on top of TSCH causes high energy consumption, mainly because of the amount of energy needed to run the schedule, but it significantly improves packet delivery ratio and delay compared to ContikiMAC under the same conditions. In most cases, the LL unicast was found to outperform the LL broadcast, but the latter can be beneficial to certain applications, especially those sensitive to delays.

Simulation of Scalability in Cloud-Based IoT Reactive Systems Leveraged on a WSAN Simulator and Cloud Computing Technologies

Implementing a wireless sensor and actuator network (WSAN) in Internet of Things (IoT) applications is a complex task. The need to establish the number of nodes, sensors, and actuators, and their location and characteristics, requires a tool that allows the preliminary determination of this information. Additionally, in IoT scenarios where a large number of sensors and actuators are present, such as in a smart city, it is necessary to analyze the scalability of these systems. Modeling and simulation can help to conduct an early study and reduce development and deployment times in environments such as a smart city. The design-time verification of the system through a network simulation tool is useful for the most complex and expensive part of the system formed by a WSAN. However, the use of real components for other parts of the IoT system is feasible by using cloud computing infrastructure. Although there are cloud computing simulators, the cloud layer is poorly developed for the requirements of IoT applications. Technologies around cloud computing can be used for the rapid deployment of some parts of the IoT application and software services using containers. With this framework, it is possible to accelerate the development of the real system, facilitate the rapid deployment of a prototype, and provide more realistic simulations. This article proposes an approach for the modeling and simulation of IoT systems and services in a smart city leveraged in a WSAN simulator and technologies of cloud computing. Our approach was verified through experiments with two use cases. (1) A model of sensor and actuator networks as an integral part of an IoT application to monitor and control parks in a city. Through this use case, we analyze the scalability of a system whose sensors constantly emit data. (2) A model for cloud-based IoT reactive parking lot systems for a city. Through our approach, we have created an IoT parking system simulation model. The model contains an M/M/c/N queuing system to simulate service requests from users. In this use case, the model replication through hierarchical modeling and scalability of a distributed parking reservation service were evaluated. This last use case showed how the simulation model could provide information to size the system through probability distribution variables related to the queuing system. The experimental results show that the use of simulation techniques for this type of application makes it possible to analyze scalability in a more realistic way.

SEA-BREW: A scalable Attribute-Based Encryption revocable scheme for low-bitrate IoT wireless networks

Attribute-Based Encryption (ABE) is an emerging cryptographic technique that allows one to embed a fine-grained access control mechanism into encrypted data. In this paper we propose a novel ABE scheme called SEA-BREW (Scalable and Efficient Abe with Broadcast REvocation for Wireless networks), which is suited for Internet of Things (IoT) and Industrial IoT (IIoT) applications. In contrast to state-of-the-art ABE schemes, ours is capable of securely performing key revocations with a single short broadcast message, instead of a number of unicast messages that is linear with the number of nodes. This is desirable for low-bitrate Wireless Sensor and Actuator Networks (WSANs) which often are the heart of (I)IoT systems. In SEA-BREW, sensors, actuators, and users can exchange encrypted data via a cloud server, or directly via wireless if they belong to the same WSAN. We formally prove that our scheme is secure also in case of an untrusted cloud server that colludes with a set of users, under the generic bilinear group model. We show by simulations that our scheme requires a constant computational overhead on the cloud server with respect to the complexity of the access control policies. This is in contrast to state-of-the-art solutions, which require instead a linear computational overhead.

Smart Energy Management System using Wireless Sensing and Actuator Network

This work presents the use of the Internet of Things (IoT) concept as a tool for developing a wireless network of sensors and actuators to propose a technological update in air conditioning units installed in Saudi educational, industrial, and residential buildings. One way to improve modern buildings' energy efficiency is to apply control and decision mechanisms to decrease power consumption. To achieve this goal, data are collected over several months using a Wireless Sensor and Actuator Network (WSAN). Gathered data then applied to an Energy Efficiency Management System (EEMS) to find suitable solutions to have a maximum energy efficiency ratio. The WSAN hardware system is installed in the Engineering Building of Suhag University. The WSAN is linked to the EEMS software for monitoring and recording data received from sensors. The collected data are analyzed, and energy efficiency solutions are applied. Results were promised, and the efficiency ratio reached 23%.

Overcoming the Communication Challenges in Wireless Sensor and Actuat or Networks Isolated using DTN T echnologies

Wireless Sensor and Actuator Networks (WSAN) have represented a significant advance in wireless communication environments and their convergence with the phenomenon called the Internet of Things (IoT). One of the challenges studied in the WSAN field is to propose communication mechanisms to interconnect wireless sensor networks in isolated areas. Various studies have revealed the difficulty of achieving connectivity in this type of network. In this sense, we address the challenge of interconnecting isolated WSANs, which do not have end-to-end connection, with the Internet network infrastructure. For this, we consider the following characteristics of these environments, disruptive communications, long delays; devices with limited resources, very short transfer times and in contexts of mobility. We propose an integrated architecture that allows us to offer a service management framework based on the capabilities provided by WSAN, through an infrastructure based on cloud technologies. The functionalities that characterize service architectures in telecommunication networks and the integration of WSAN with cloud-based architectures are analyzed. Architectural capabilities such as Machine-to-Machine (M2M) and Machine Type Communication (MTC) are considered. The proposed architecture allows deliver applications and services can be reachable and shared with any host connected to Internet. WSAN data, hosted at remote sites or with limited communications, can be processed, stored and analyzed in the cloud, or locally by components of the architecture. The communication with the sensor network and actuators, is iterant, because of architecture provides support for long-delayed and disruptive tolerant services.

An Effective and Active Bandwidth Distribution in Networked Control Systems

Networked Control System (NCS) is a method composed of physically shared smart devices that can observe the surroundings, work on it, and converse with one another by means of a communication system to attain a widespread purpose. Characteristic examples that fall into this section are Wireless Sensors and Actuators Networks (WSANs) for ecological analyzing and checking, multi-vehicle systems for composed investigation, camera systems for observation, multicamera facilitated movement catch, shrewd lattices for vitality circulation and the executives, and so forth. NCSs changes from increasingly customary control systems as a result of their interdisciplinary which needs the combination of control hypothesis, correspondences, software engineering and programming designing. Plenty of communication modes are available from telephone lines, cell phone networks, satellite networks and most widely used is internet. The choice of network depends upon the application to be served. Internet is the most suitable and inexpensive choice for many applications where the plant and the controller are far from each other. The troubles present in the structure of control systems that are solid to correspondence parameters like transfer speed, arbitrary deferral and packet loss, to computational parameters in light of the tremendous amount of information to be handled or to the mutual idea of the detecting and control to ongoing execution on limited resources and due to the unpredictability to the huge number of untrustworthy agent present. With the limited measure of data transmission accessible, it is improved to use it ideally and proficiently. This further raises the requirement for need choices issue for controlling a series of actuators for a progression of tasks. The proposed methodology deals broadly made in two distinct directions. The first direction aims at a control theoretical analysis while considering the network as a constant parameter like special controllers and altering the sampling rate. The second direction aims the design of new communication network infrastructures, algorithms or protocols like designing static and dynamic message scheduling algorithms. This method combines both directions and depends on the well- recognized results in both communication networks and control theory

Agrinex: A low-cost wireless mesh-based smart irrigation system

Abstract Wireless Sensor Networks in precision agriculture utilize natural resources more efficiently by collecting real-time data on farms to assist agriculture farmers to make intelligent decisions. Using this technology, farmers can effectively use the information to achieve greater yields and earn higher profits. This work presents an alternative to existing monitoring methods in the agricultural lands whilst providing an irrigation mechanism to help in resource conservation efforts by the use of a Wireless Sensor and Actuator Network (WSAN). Agrinex system features a mesh-like configuration of in-field nodes that act both as the sensor for soil moisture, temperature and humidity and actuator on a valve that regulates drip irrigation. The mesh-based network is dynamically design to allow self-reorganization of sensor nodes when changes happen in the network. The resulting Agrinex system is a promising start for a WSAN framework of various applications particularly in agriculture.

A Context-Aware Middleware Cloud Approach for Integrating Precision Farming Facilities into the IoT toward Agriculture 4.0

The adoption of Precision Farming (PF) practices involving ubiquitous computing advancements and conceptual innovations of “smart” agricultural production toward Agriculture 4.0 is a significant factor for the benefit of sustainable growth. In this context, the dynamic integration of PF facility systems into the Internet of Things (IoT) represents an excessive challenge considering the large amount of heterogeneous raw data acquired in agricultural environments by Wireless Sensor and Actuator Networks (WSANs). This paper focuses on the issue of facilitating the management, process, and exchange of the numerous and diverse data points generated in multiple PF environments by introducing a framework of a cloud-based context-aware middleware solution as part of a responsive, adaptive, and service-oriented IoT integrated system. More particularly, the paper presents in detail a layered hierarchical structure according to which all functional elements of the system cope with context, while the context awareness operation is accomplished into a cloud-based distributed middleware component that is the core of the entire system acting as a Decision Support System (DSS). Furthermore, as proof of concept, the functionality of the proposed system is studied in real conditions where some evaluation results regarding its performance are quoted.

Evaluating and improving the scalability of RPL security in the Internet of Things

Wireless Sensor and Actuator Networks (WSANs) will represent a key building block for the future Internet of Things, as a cheap and easily-deployable technology to connect smart devices on a large scale. In WSAN the Routing Protocol for Low-Power and Lossy Networks (RPL) has a crucial role as the standard IPv6-based routing protocol. RPL specifications define a basic set of security features, without which it would be open to disruptive routing attacks. However, the impact of these features on the WSAN performance has not been thoroughly investigated yet. The contribution of this paper is two-fold. First, we extensively evaluate the impact of security mechanisms on the scalability of WSANs by means of both simulations and real experiments. We show that the protection against eavesdropping and forgery has a modest impact on the performance, whereas the protection against replay has a more considerable impact, especially on the network formation time which increases noticeably. Despite this, we show that protecting against replay reduces the number of control messages exchanged and improves routes optimality. For these reasons, we recommend to always use the security mechanisms. Finally, we propose a standard-compliant optimization for defending against replay that reduces the impact on the overall performance.

A Novel Hybrid Optimization Scheme on Connectivity Restoration Processes for Large Scale Industrial Wireless Sensor and Actuator Networks

In the wireless sensor and actuator networks (WSANs) of industrial field monitoring, maintaining network connectivity with coverage perception plays a decisive role in many industrial process scenarios. The mobile actuator node is responsible for collecting data from the sensing nodes and performing diverse specific collaborative operation tasks. However, the failure of the nodes usually causes coverage vulnerability and partition of the network. Urgent and time-sensitive applications expect a minimum coverage loss to complete an instant connectivity restoration. This paper presents a hybrid coverage perception-based connectivity restoration algorithm, which is designed to restore network connectivity with minimal coverage area loss. The algorithm uses a backup node, which is selected nearby the critical node, to ensure a timely restoration when the critical node encounters failure. In the process of backup node migration, the optimal destination will be reselected to maintain the best network coverage after network connectivity recovery. The effectiveness of the proposed algorithm was verified by some simulation experiments.

WSN Based Tariff and Electrical Loads Theft Identification

Energy storing has turned into a notable statement for the society of nowadays. This paper displays a Wireless Sensor and Actuator Network (WSN) intended to offer help to a programmed framework, based on the GSM, which empowers a mindful utilization of vitality. The proposed system plays out a proficient administration of devices, machines and procedures, upgrading their activity to accomplish a decrease in their general vitality use at some random time. For this reason, significant information is gathered from smart sensors, which are placed at the required areas, just as from the vitality showcase through the wireless communication. This data analysis is to give learning about load use, and to enhance proficiency.