Optimizing Quality of Service of Clustering Protocols in Large-Scale Wireless Sensor Networks with Mobile Data Collector and Machine Learning

Gantassi, Rahma; Gouissem, Bechir Ben; Cheikhrouhou, Omar; Khediri, Salim El; Hasnaoui, Salem

doi:10.1155/2021/5531185

Cited by 16 publications

(16 citation statements)

References 15 publications

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“…When the nanofluid is heated to the temperature required by the experiment in the constant temperature tank, the circulating pump is turned on to make the nanofluid circulate through the radiator of the car and circulate in the whole system, and the flow required for the experiment can be obtained by adjusting the shut-off valve. After the whole system is stable, the surface temperature signals of 6 thermocouples, the temperature signals of 2 inlets and outlets, and the current signals of pressure difference and flow rate are recorded by the data collector, and the change of the power indicator of the power meter is recorded in real-time [19].…”

Section: Preparation Of Nanofluids and Determination Of Experimental ...mentioning

confidence: 99%

Application of Nanofluid Electrochemistry in Heat Dissipation of Permanent Magnet Synchronous Motors

Lin

Xie

2022

Journal of Chemistry

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In order to solve the problem of heat dissipation of permanent magnet synchronous motors, a technology using the principle of nanofluid electrochemistry is proposed. The main content of this technology is based on the characteristics and applications of nanofluids; according to the experimental system, the preparation and experimental parameters of nanofluids were determined; finally, by studying the influence of ultrasonic oscillation time and dispersant on the stability of nanofluids, it was concluded that the improvement of the thermal conductivity of nanofluids contributed to the improvement of the heat transfer rate of nanofluids. Experimental results show that when the volume fraction is 0.5, the increase rate of thermal conductivity is 1.51, the increase rate of convective heat transfer coefficient is 20.33, and the increase rate of convective heat transfer coefficient is greater than that of thermal conductivity, which shows that nanofluids have very good heat dissipation ability. It is proved that the technical research of nanofluid can meet the heat dissipation requirements of a permanent magnet synchronous motor.

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Section: Preparation Of Nanofluids and Determination Of Experimental ...mentioning

confidence: 99%

Application of Nanofluid Electrochemistry in Heat Dissipation of Permanent Magnet Synchronous Motors

Lin

Xie

2022

Journal of Chemistry

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“…They used clustering and data filtering within the CHS. An application of the proposed protocol where the urban buses carry the mobile sinks was also explained [ 22 ]. This application was able to achieve maximum energy balance, connectivity, and throughput.…”

Section: Resultsmentioning

confidence: 99%

“…ey used clustering and data filtering within the CHS. An application of the proposed protocol where the urban buses carry the mobile sinks was also explained [22].…”

Section: Resultsmentioning

confidence: 99%

Optimization of Leach Protocol in Wireless Sensor Network Using Machine Learning

Ramesh

Rajasekaran

Dwivedi

et al. 2022

Computational Intelligence and Neuroscience

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The Wireless Sensor Network is a network formed in areas human beings cannot access. The data need to be sensed by the sensor and transferred to the sink node. Many routing protocols are designed to route data from a single node to the sink node. One of the routing protocols is the hierarchical routing protocol, which passes on the sensed data hierarchically. The Low Energy Adaptive Clustering Hierarchy (LEACH) is one of the hierarchical methods in which communication happens in two steps: the setup phase and the steady-state phase. The efficiency of the LEACH has to be optimized to improve the network lifetime. Therefore, the k-means clustering algorithm, which comes under the unsupervised machine learning method, is incorporated with the LEACH algorithm and has shown better results. But the selection of cluster head needs to improvise because it will transfer the summed-up data to the sink node, so it is to be efficient enough. So, this paper proposes the modified k-means algorithm with LEACH protocol for optimizing the Wireless Sensor Network. In the modified k-means algorithm, the weight of the cluster head is tested and elected, and the clusters are formed using the Euclidean distance formula. The proposed work yields 48.85% efficiency compared to the existing protocol. It is also proven that the proposed work showed more successful data transfer to the sink node. The cluster head selection process elects the more efficient node as the head with less failure rate. The proposed work optimistically balanced the whole network in terms of energy and successful data transfer.

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“…Many studies have been conducted to evaluate the effect of K-Means on the LEACH protocol performance in WSN [1], [8]- [13]. Other studies, apply the Grid-sizes clustering on LEACH to enhance the WSNs performances as in [5], [8], [14], [15]. Several other studies have been carried out to develop MDC routing protocols [16]- [20] in which they have concentrated on increasing the lifetime of the WSN.…”

Section: Related Workmentioning

confidence: 99%

“…[14], [15] This approach is based on a shutdown timer. This is calculated based on the residual energy levels of each node in the network.…”

Section: Studymentioning

confidence: 99%

Enhancing QoS and Residual Energy by Using of Grid-Size Clustering, K-Means, and TSP Algorithms With MDC in LEACH Protocol

2022

Self Cite

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Some recent researches have shown that the energy consumption problem caused by data collection in a wireless sensor network (WSN) based on a static data collector is a main threat to the network lifetime. However, with the progress of the mobile terminal technology, the implementation of mobile data collectors (MDCs) has become more popular in large-scale WSNs, but it remains a big problem to improve the Quality of Service (QoS) criteria and minimize the energy consumption at the same time. However, most existing systems based on MDCs do not successfully strike a balance between routing energy consumption and QoS. In addition, most WSN protocols fail to maintain their impact when the network topology changes. Thus, for a dynamic WSN, it is important to support an intelligent MDC to continue data propagation despite the inevitable changes in the WSN topology. Considering all the above challenges, we propose a new intelligent MDC based on the traveling salesman problem (TSP) to determine the optimal path traveled by the MDC for energy efficiency and latency. Specifically, our proposed Mobile Data Collectors-Traveling Salesman Problem-Low Energy Adaptive Clustering Hierarchy-K-Means (MDC-TSP-LEACH-K) protocol uses K-Means and Grid clustering algorithm to decrease energy consumption in the cluster head (CH) election phase. Additionally, MDC is utilized as an intermediate between CH and the sink to further enhance the QoS of WSNs, to reduce delays while collecting data, and improve the transmission phase of the LEACH protocol.INDEX TERMS Energy consumption, large-scale wireless sensor networks, optimal path, QoS.

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Optimizing Quality of Service of Clustering Protocols in Large-Scale Wireless Sensor Networks with Mobile Data Collector and Machine Learning

Cited by 16 publications

References 15 publications

Application of Nanofluid Electrochemistry in Heat Dissipation of Permanent Magnet Synchronous Motors

Application of Nanofluid Electrochemistry in Heat Dissipation of Permanent Magnet Synchronous Motors

Optimization of Leach Protocol in Wireless Sensor Network Using Machine Learning

Enhancing QoS and Residual Energy by Using of Grid-Size Clustering, K-Means, and TSP Algorithms With MDC in LEACH Protocol

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