TABLE 1 - uploaded by Gholamreza Kakamanshadi
Content may be subject to copyright.
Source publication
Abstract- Fault tolerance is one of the critical issues in Wireless Sensor Network (WSN) applications. The problem of missing sensor node, communication link and data are inevitable in wireless sensor networks. WSNs experience failure problems due to various factors such as power depletion, environmental impact, radio interference, asymmetric commu...
Context in source publication
Similar publications
The reliability of wireless sensor networks (WSN) is affected by faults that may occur due to various reasons such as malfunctioning hardware, software glitches, dislocation, or environmental hazards, e.g. fire or flood. Due to the inherent nature of these networks, a sensor node may fail and hence the route may also fail. A WSN that is not prepare...
Citations
... Since the basic design requirement of a WSNbased Agri-IoT is to maintain the healthy functionality and longevity of the SNs and the BS, any post-deployment impairments that cannot be self-fixed must be tolerated to not interfere with the core function of the network. Therefore, any automated FT mechanism that can be achieved through the self-reconfiguration and self-management for enhanced network availability, reliability, and dependability is encouraged in the WSN sublayer [92]. According to Figure 17, an efficient WSN-based Agri-IoT, therefore, requires a calculated mix of FT mechanisms based on the intended application. ...
This paper presents an in-depth contextualized tutorial on Agricultural IoT (Agri-IoT), covering the fundamental concepts, assessment of routing architectures and protocols, and performance optimization techniques via a systematic survey and synthesis of the related literature. The negative impacts of climate change and the increasing global population on food security and unemployment threats have motivated the adoption of the wireless sensor network (WSN)-based Agri-IoT as an indispensable underlying technology in precision agriculture and greenhouses to improve food production capacities and quality. However, most related Agri-IoT testbed solutions have failed to achieve their performance expectations due to the lack of an in-depth and contextualized reference tutorial that provides a holistic overview of communication technologies, routing architectures, and performance optimization modalities based on users’ expectations. Thus, although IoT applications are founded on a common idea, each use case (e.g., Agri-IoT) varies based on the specific performance and user expectations as well as technological, architectural, and deployment requirements. Likewise, the agricultural setting is a unique and hostile area where conventional IoT technologies do not apply, hence the need for this tutorial. Consequently, this tutorial addresses these via the following contributions: (1) a systematic overview of the fundamental concepts, technologies, and architectural standards of WSN-based Agri-IoT, (2) an evaluation of the technical design requirements of a robust, location-independent, and affordable Agri-IoT, (3) a comprehensive survey of the benchmarking fault-tolerance techniques, communication standards, routing and medium access control (MAC) protocols, and WSN-based Agri-IoT testbed solutions, and (4) an in-depth case study on how to design a self-healing, energy-efficient, affordable, adaptive, stable, autonomous, and cluster-based WSN-specific Agri-IoT from a proposed taxonomy of multi-objective optimization (MOO) metrics that can guarantee an optimized network performance. Furthermore, this tutorial established new taxonomies of faults, architectural layers, and MOO metrics for cluster-based Agri-IoT (CA-IoT) networks and a three-tier objective framework with remedial measures for designing an efficient associated supervisory protocol for cluster-based Agri-IoT networks.
... Fault tolerance [13] is another critical issue in WSN. There are other problems such as failure of SNs, and unreliable communication links which are unavoidable in WSNs. ...
... Single SN failure refers to the failure of one node whereas multi-node failure refers to a failure of more than one SNs at a time. There are mainly three kinds of strategies to achieve FT systems viz., Redundancy based [13], Deployment based [15] and Clustering based [14][15][16]. ...
Network robustness in wireless sensor network (WSN) is an emerging area of research as sensor nodes (SNs) often fail due to limited energy resources, harsh environment, and proliferation of cyber-attacks. Therefore, the energy efficiency and robustness of SNs are the two critical issues that need to be addressed in WSNs. In this paper, we address the above mentioned issues in two phases. In the first phase, we propose an energy efficient SN deployment scheme for WSNs using non-uniform SN deployment scheme. In the second phase, we generate scale-free network topology in order to improve the robustness of WSN so that they can withstand failure issues due to cyber-attacks. For the construction of scale-free topology, we have considered various constraints of SNs viz., communication range, maximum degree, and network growth. This topology construction was proved to be very effective in providing robustness to WSN because of their heterogeneous degree distribution. The performance of the proposed work has been evaluated through simulation using Python 3.7.1 on Spyder 3.3.2 on Ubuntu 19.10 with Linux Kernel 5.0.0.13-generic, X86_64 operating system. The simulation results show that the proposed work significantly outperforms existing state-of-the-art related approaches in terms of robustness of the WSN along with the increase in network lifetime. Also, it produces characteristic at tailed distribution with maximum SNs having fewer degree count.
... A fault tolerance mechanism basically follows the stages including fault detection and diagnosis, and restoration/ repair. In some of the existing approaches, fault tolerance is managed and accomplished using add-on modules, other evaluation tools, and require additional hardware [19]. Moreover, many approaches for achieving fault tolerance in WSNs are generally implemented and controlled centrally, also called centralized or sink based approaches [20][21][22]. ...
Maintaining prolonged service lifetime and adequate quality of sensing coverage are the key challenges in constructing Wireless Sensor Network (WSN) based applications. As such networks usually operate in inhospitable and hostile environment, failures are ineludible and providing resilience is a necessity. However, it is challenging to satisfy the conflicting problems of enhancing energy efficiency and fault tolerance simultaneously. Fault-tolerance is a significant requirement while designing WSN. It is crucial to detect the failures in advance and take necessary measures to maintain durable and efficient functioning of the network. Generally, in the existing face structured WSNs, node faults and failures can induce the formation of coverage holes, disrupt the face structure and consequently curtail the application performance. The coverage quality will affect the monitoring effectiveness of tracking applications, e.g., a moving target tracking. Moreover, node failures can cause the network to be partitioned, further reducing the accuracy in tracking. In this paper, we propose a robust fault-tolerance scheme with coverage preservation using a face structured WSN topology (FCAFT). The key objective of the proposed FCAFT scheme is to sustain the performance of the network by timely healing the faults in the network, to enhance the durability and reliability of the WSN. The results of simulation and comparison with existing methods reveal that FCAFT is efficacious in enhancing the service lifetime of WSN by about 14% and sustains about 96% of coverage even when the failure rate is more than 20%, which is a necessity for critical monitoring and tracking applications of WSNs.
... The virtual backbone scheduling approach is used to discover several Virtual backbones for improving the network lifetime. However, it does not focus on detecting faulty nodes [13]. A WSN involvement failure issues owing to several factors, for examp le, energy reduction, ecological influence, radio intrusion, unequal transmission links, displacement of sensor node and crash. ...
... It consists of cluster groups, the sink/anchor nodes in a cluster group is responsible of its member nodes utilization and reliably control of data transmission based on their relative location and directions. ER-MAC also implements duty cycling, where it incorporates the sleep mode into the communicating members of the cluster group to conserve energy [84]. ...
Underwater wireless sensor networks (UWSNs) have become highly efficient in performing different operations in oceanic environments. Compared to terrestrial wireless sensor networks (TWSNs), MAC and routing protocols in UWSNs are prone to low bandwidth, low throughput, high energy consumption, and high propagation delay. UWSNs are located remotely and do not need to operate with any human involvement. In UWSNs, the majority of sensor batteries have limited energy and very difficult to replace. The uneven use of energy resources is one of the main problems for UWSNs, which reduce the lifetime of the network. Therefore, an energy-efficient MAC and routing techniques are required to address the aforementioned challenges. Several important research projects have been tried to realize this objective by designing energy-efficient MAC and routing protocols to improve efficient data packet routing from Tx anchor node to sensor Rx node. In this article, we concentrate on discussing about different energy-efficient MAC and routing protocols which are presently accessible for UWSNs, categorize both MAC and routing protocols with a new taxonomy, as well as provide a comparative discussion. Finally, we conclude by presenting various current problems and research difficulties for future research.
... Presented a classification of fault diagnosis approaches (From 2013 to 2018) into three categories based on the decision hubs and key characteristics of employed algorithms. [26] Presented an analysis for specific methods in fault tolerance such as deployment, redundancy, and clustering. [27] Presented state of the art for self-healing techniques. ...
The Industrial Revolution 4.0 (IR 4.0) has drastically impacted how the world operates. The Internet of Things (IoT), encompassed significantly by the Wireless Sensor Networks (WSNs), is an important subsection component of the IR 4.0. WSNs are a good demonstration of an ambient intelligence vision, in which the environment becomes intelligent and aware of its surroundings. WSN has unique features which create its own distinct network attributes and is deployed widely for critical real-time applications that require stringent prerequisites when dealing with faults to ensure the avoidance and tolerance management of catastrophic outcomes. Thus, the respective underlying Fault Tolerance (FT) structure is a critical requirement that needs to be considered when designing any algorithm in WSNs. Moreover, with the exponential evolution of IoT systems, substantial enhancements of current FT mechanisms will ensure that the system constantly provides high network reliability and integrity. Fault tolerance structures contain three fundamental stages: error detection, error diagnosis, and error recovery. The emergence of analytics and the depth of harnessing it has led to the development of new fault-tolerant structures and strategies based on artificial intelligence and cloud-based. This survey provides an elaborate classification and analysis of fault tolerance structures and their essential components and categorizes errors from several perspectives. Subsequently, an extensive analysis of existing fault tolerance techniques based on eight constraints is presented. Many prior studies have provided classifications for fault tolerance systems. However, this research has enhanced these reviews by proposing an extensively enhanced categorization that depends on the new and additional metrics which include the number of sensor nodes engaged, the overall fault-tolerant approach performance, and the placement of the principal algorithm responsible for eliminating network errors. A new taxonomy of comparison that also extensively reviews previous surveys and state-of-the-art scientific articles based on different factors is discussed and provides the basis for the proposed open issues.
... Various reasons can cause the sensors in the network to fail or to stop working correctly like environmental factors, physical conditions, energy depletion, and so forth [41,42]. This can influence the functioning of the network and it can also degrade its performance. ...
... Furthermore, in a static network, the transmission of data is carried out following the detection of the events, while in a dynamic network, the transmission is performed in a periodic manner to handle the mobile sensor nodes. A representation of static monitoring is the early detection of forest fires while tracking applications represent an example of the dynamic monitoring of events [41,43]. ...
Wireless sensor networks (WSNs) have turned into a leading area of research over the course of the last few decades as they have been employed in various application domains. Since traditional approaches configure WSNs statically, their dynamic reconfiguration represents a difficult challenge. To address this challenge, clustering techniques can be integrated into WSNs. In the present paper, we present a comprehensive review of some of the recently proposed clustering protocols (from the year 2003 to 2021) that have been applied to WSNs. In this survey, clustering algorithms are categorized into four classes, namely (1) cluster-based protocols for homogeneous nodes, (2) cluster-based protocols for heterogeneous nodes, (3) clustering protocols based on fuzzy logic methods, and (4) clustering protocols based on heuristic methods. This categorization was carried out based on these protocols’ network organization as well as the techniques used for managing the procedures of clustering. For the purpose of evaluating the efficiency of these protocols, we take into account features, performance as well as clustering methodologies as the main parameters used in the comparison of these four categories of clustering approaches.
... Energy is one of fundamental factors in WSNs [25]. Since overhead power lines in distribution power networks are always in open areas, relatively ample sunlight is available. ...
Wireless sensor networks provide a promising technology to surveil overhead transmission lines in smart grid communication. However, a great challenge for researchers is proposed by adverse outdoor environments and essential requirements of strong as well as flexible smart grid communication. Specifically, nearly linear topology, limited energy, and tolerance for faults are entangled to make the surveillance system complex. Because of the need for deep understanding of system, significant efforts have been made in the past few years. We have proposed a fault-tolerance framework for surveillance of overhead transmission lines. In this paper, we follow the framework and further explore deployment problems systematically. Firstly, we present a fault-tolerance placement model. After analyzing the model, we identify the optimal placement for fault tolerance and then propose a placement algorithm with optimal deployment. An extensive experiment highlights some useful observations for design of the fault-tolerance system and demonstrates efficient fault tolerance for relay nodes. Numerical results show that the fault-tolerance ratio is improved by at least 6 % compared to that of previous algorithms.
... In contrast, the effects of soft faults are more subtle as the node continues to provide data, but with reduced or impaired quality. A common soft fault is silent data corruption by incorrect data sensing, erroneous data processing, or corrupted data communication that can result in the reporting of altered or even arbitrary sensor readings [12]. Additionally, such faults can influence the runtime behavior of sensor nodes causing services to time out. ...
Faults in wireless sensor nodes tend to be the norm rather than the exception. Our paper addresses the following problems: How can we make sure the sensed data has not been distorted by faults? And when we experience anomalies in the sensed data, how can we distinguish between rare but correctly measured events and incorrect data due to faults?
The focus of this paper is specifically on soft faults, because (i) they deteriorate the data quality and (ii) are hard to distinguish from irregular but correct events. Many papers on how to detect soft faults have been proposed, but they mostly rely on assumptions on the network’s deployment or the nature of the collected data. Therefore, they are insufficient as they can miss faults or misinterpret correct data.
In this paper, our key idea is to augment the existing fault-detection approaches with node-level information as additional input. Our contribution is to show the existence of such node-level information that can improve (i) the detection of soft faults and (ii) the distinction between faults and events. This node-level information — called fault indicators — can then be included in existing fault detection schemes. Based on practical experiments, we show that using such fault indicators indeed improves the detection rate and reduces the risk of missing fault-induced variations of sensor data.
... (5), if there is no fault, β 1(xs±1,ys) , if fault in imaginary axis, β 2(xs,ys±1) , if fault in real axis ...
In this paper, we have proposed a hybrid fault-tolerant routing to solve fault-tolerant issue in wireless sensor networks (WSNs) based on hierarchical topology. The hierarchical topology is a combination of clustering and the labeling of sensor nodes as Gaussian integers. Accordingly, the network area is divided into small square grids, the cluster head of each grid is represented by a Gaussian integer. These cluster heads are connected together to create a Gaussian network. Through node symmetry, and the shortest distance in the Gaussian network, as well as the advantages of multi-path routing, this paper proposes a hybrid fault-tolerant clustering routing protocol based on Gaussian network for wireless sensor network (FCGW). The purpose of FCGW is to improve fault tolerance, increase data reliability and reduce energy consumption for wireless sensor networks. The experimental results of the proposed scheme show that FCGW protocol has high data reliability. In addition, the FCGW protocol consumes about 48% of the energy in the network, while other protocols consume 70% more energy.
