Towards Sustainable Distributed Sensor Networks: An Approach for Addressing Power Limitation Issues in WSNs

Alaerjan, Alaa

doi:10.3390/s23020975

Cited by 15 publications

(5 citation statements)

References 41 publications

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“…Their approach optimizes the network among sensor hubs and powerfully alters clustering to adjust to changing natural conditions, progressing the proficiency and unwavering quality of rural observing [10]. Alaerjan (2023) tended to control impediment issues in WSNs by proposing approaches for maintainable dispersed sensor systems. Their research investigates methods to moderate control imperatives and drag out the operational life expectancy of sensor hubs, guaranteeing economical operation in different applications [11].…”

Section: Related Workmentioning

confidence: 99%

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Enhancing Security and Energy Efficiency in Wireless Sensor Networks for IoT Applications

Aqeel

2024

jes

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Wireless Sensor Networks (WSNs) are fundamental components within the Internet of Things (IoT) scene, empowering information collection and transmission in different applications. This research papers on upgrading the security and vitality effectiveness of WSNs for ideal IoT usefulness. Novel strategies were created and assessed to address these vital perspectives. Security improvements included the usage of lightweight cryptographic calculations, intrusion detection systems (IDS), and secure directing conventions. These measures essentially reinforced organized strength against cyber dangers, with interruption discovery rates surpassing 95% and secure steering conventions accomplishing a strength score of over 97%. Vitality productivity optimizations enveloped communication convention improvements, information accumulation strategies, and energetic control administration methodologies. These procedures come about in outstanding decreases in vitality utilization, with optimized conventions diminishing vitality utilization by up to 30% and information conglomeration techniques yielding vitality reserve funds of up to 50%. Test assessments were conducted utilizing both simulation-based approaches and real-world organizations. Recreation comes about, obtained utilizing NS-3, showcasing the viability of the proposed strategies over different network topologies, activity designs, and attack scenarios. Real-world experimentation employing a WSN testbed approved the viable achievability and viability of the techniques. Comparative investigations with existing writing highlighted the oddity and importance of the commitments, checking considerable progressions in WSN security and vitality proficiency.

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Section: Related Workmentioning

confidence: 99%

“…Alaerjan (2023) tended to control impediment issues in WSNs by proposing approaches for maintainable dispersed sensor systems. Their research investigates methods to moderate control imperatives and drag out the operational life expectancy of sensor hubs, guaranteeing economical operation in different applications [11]. [12].…”

Section: Related Workmentioning

confidence: 99%

Enhancing Security and Energy Efficiency in Wireless Sensor Networks for IoT Applications

Aqeel

2024

jes

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“…5G wireless communication is considered as a suitable technology to connect different devices and equipment in RESs [21]. This is mainly due to the nature of the utilized devices in RESs (e.g., smart meters, sensors, UE) since they inherently support wireless communication [22]. Fifth generation communication technology provides multiple benefits for distributed RESs.…”

Section: G Network In Distributed Ressmentioning

confidence: 99%

Automatic Recognition of Beam Attachment for Massive MIMO System in Densely Distributed Renewable Energy Resources

Alaerjan

2023

Sustainability

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Several large-scale and distributed systems such as renewable energy systems (RESs) require ubiquitous and reliable communication. RESs are designed to provide efficient power management and improve both energy production and consumption. Decision making in RESs heavily depends on real-time communication. Fifth and sixth-generation (5G, 6G) wireless networks promise to deliver significant communication advantages to RESs including ultra-low latency, high throughput and improved coverage. However, the communication behavior in RESs is categorized as unpredictable due to aspects such as system flexibility and equipment heterogeneity. This may affect the stability of the entire RES, which results in further issues such as signal reliability and degraded coverage. Therefore, precise identification of user equipment’s (UE) location greatly improves the sustainability of 5G and 6G wireless services. In this work, we propose a novel low-complexity technique to automatically recognize UE locations in an area of interest. The approach aims at providing precise identification of UE with minimum memory and feature requirements. We use the lazy learning approach to build a prediction model to construct beam-attachment maps. We then train the model to provide distributed intelligent models to automatically recognize beam-attachment indexes. We compare the proposed approach with instance-based techniques to measure its ability at predicting beam-attachment maps. The results show that the proposed model has the ability to provide an accurate prediction with respect to the beam-attachment index (around 100%) with minimal complexity.

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“…Wireless communication also improves the management of applications that adopt the edge computing paradigm. For example, wireless network slicing allows an application to create different management layers based on exchanged data and communicating devices [43]. Figure 1 shows how wireless communication contributes to moving data among different domains in a smart city.…”

Section: Wireless Communication In New Applicationsmentioning

confidence: 99%

Automatic Clustering for Improved Radio Environment Maps in Distributed Applications

Chikha

Alaerjan

2023

Applied Sciences

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Wireless communication greatly contributes to the evolution of new technologies, such as the Internet of Things (IoT) and edge computing. The new generation networks, including 5G and 6G, provide several connectivity advantages for multiple applications, such as smart health systems and smart cities. Adopting wireless communication technologies in these applications is still challenging due to factors such as mobility and heterogeneity. Predicting accurate radio environment maps (REMs) is essential to facilitate connectivity and improve resource utilization. The construction of accurate REMs through the prediction of reference signal received power (RSRP) can be useful in densely distributed applications, such as smart cities. However, predicting an accurate RSRP in the applications can be complex due to intervention and mobility aspects. Given the fact that the propagation environments can be different in a specific area of interest, the estimation of a common path loss exponent for the entire area produces errors in the constructed REM. Hence, it is necessary to use automatic clustering to distinguish between different environments by grouping locations that exhibit similar propagation characteristics. This leads to better prediction of the propagation characteristics of other locations within the same cluster. Therefore, in this work, we propose using the Kriging technique, in conjunction with the automatic clustering approach, in order to improve the accuracy of RSRP prediction. In fact, we adopt K-means clustering (KMC) to enhance the path loss exponent estimation. We use a dataset to test the proposed model using a set of comparative studies. The results showed that the proposed approach provides significant RSRP prediction capabilities for constructing REM, with a gain of about 3.3 dB in terms of root mean square error compared to the case without clustering.

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Towards Sustainable Distributed Sensor Networks: An Approach for Addressing Power Limitation Issues in WSNs

Cited by 15 publications

References 41 publications

Enhancing Security and Energy Efficiency in Wireless Sensor Networks for IoT Applications

Enhancing Security and Energy Efficiency in Wireless Sensor Networks for IoT Applications

Automatic Recognition of Beam Attachment for Massive MIMO System in Densely Distributed Renewable Energy Resources

Automatic Clustering for Improved Radio Environment Maps in Distributed Applications

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