Enhanced Algorithms for Fault Nodes Recovery in Wireless Sensors Network

Im, Darwish; Sm, Elqafas

doi:10.4172/2090-4886.1000150

Cited by 2 publications

(7 citation statements)

References 17 publications

(20 reference statements)

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“…By implication, FM algorithms for WSNs must not be stand-alone as currently seen in the state-of-the-art [74], instead, they must be an integral aspect of the routing protocol that agrees with the core participants of the PHY layer, such as the SN, wireless communication medium, and the BS. As illustrated on the left of Figure 15, the WSN sublayer is the most prevalent source of faults in the Agri-IoT ecosystem, in which the SNs are the central origin of faults that can propagate to the upper layers [25,44,74]. This is because the BS is resource-sufficient mainly, and the link's reliability also hinges upon the SNs' availability, as indicated in Figure 15.…”

Section: High-levelmentioning

confidence: 99%

“…Secondly, it is discernible that SNs' power mismanagement is the most prevalent origin of faults [44,82,83], which then propagate to the backend or application level (refer to the right side of Figure 15). For instance, communication, sensing, and computational accuracies of a node can be impaired when the battery energy falls below certain thresholds [44]. Also, network faults can be traced to power exhaustion and node failures, which create holes in the topology that divide the network into multiple disjointed segments [44].…”

Section: Staticmentioning

confidence: 99%

“…For instance, communication, sensing, and computational accuracies of a node can be impaired when the battery energy falls below certain thresholds [44]. Also, network faults can be traced to power exhaustion and node failures, which create holes in the topology that divide the network into multiple disjointed segments [44]. On that account, faults can be avoided in WSN-based Agri-IoT if the energy-saving strategies presented in Figure 10 and Figure 9 are effectively implemented.…”

Section: Staticmentioning

confidence: 99%

“…Limited Power Supply: The SNs are frequently battery-powered, which does not only constrain their data transmission rate, computational capabilities, and communication distance but also subjects Agri-IoT to possible SN-out-of-service and data outlier faults due to rapid power depletion beyond certain thresholds [26,44]. Consequently, network power management through data-management-related, architectural-related, and communication-related parameters has been one of the principal research focuses in WSN-based IoT applications to improve network lifetime.…”

mentioning

confidence: 99%

“…Data inconsistency faults can also result from faulty sensing, processing, and communication, which is frequently caused by power depletion below a certain threshold, while power failure occurs when a node exhausts its battery power completely [44,79,81].…”

mentioning

confidence: 99%

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A Tutorial on Agricultural IoT: Fundamental Concepts, Architectures, Routing, and Optimization

Effah¹,

Thiaré²,

Wyglinski³

2023

Preprint

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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 systematic survey and synthesis of 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 specific performance and users expectations as well as its 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 3-tier objective framework with remedial measures for designing an efficient associated supervisory protocol for cluster-based Agri-IoT networks.

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Section: High-levelmentioning

confidence: 99%