Multi-Objective Optimization with Mayfly Algorithm for Periodic Charging in Wireless Rechargeable Sensor Networks

Sandrine, M; Xia, Kewen

doi:10.3390/wevj13070120

Cited by 7 publications

(4 citation statements)

References 56 publications

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“…In our previous publication, we aimed to reduce system energy consumption and mobile charger travel distance while increasing its vacation time. Based on energy usage analysis, the mayfly algorithm (MA) was proposed [24]. Our technique had the mobile charger charge energy-hungry nodes based on their energy levels rather than all nodes at once.…”

Section: Preliminariesmentioning

confidence: 99%

Synthetic on-demand charging optimization with ADCMA for energy conservation in WRSN

Mukase,

Xia,

Owoola

2024

Preprint

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Recently, the research community has shown a growing interest in using mobile chargers to recharge the energy supply of sensor nodes in wireless rechargeable sensor network (WRSN). Mobile energy chargers offer a more dependable energy source compared to devices that harvest dynamic energy from the surrounding environment. This research introduces a synthetic on-demand charging optimization approach using Adaptive Crossover Mayfly Algorithm (ADCMA) to enhance the charging performance in WRSN. The genetic operator of roulette wheel selection is employed to choose possibly valuable solutions for crossover and the objective is to reduce the overall energy consumption of the system and the mobile charger's total distance traveled, while simultaneously enhancing its vacation time ratio. Unlike prior systems that required the mobile charger to visit and charge all nodes in every cycle, this strategy simply requires the mobile charger to visit a subset of nodes. The proposed ADCMA is also tested on 46 benchmark functions and applied to the on-demand charging model by comparing it with other well-known seven algorithms. The mathematical results demonstrate that the ADCMA effectively decreases the overall energy consumption and distance traveled by the mobile charging device, while still maintaining performance. This algorithm is particularly advantageous for real-world networks as it allows for the network to remain operational with reduced complexity compared to other approaches.

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Section: Preliminariesmentioning

confidence: 99%

Synthetic on-demand charging optimization with ADCMA for energy conservation in WRSN

Mukase,

Xia,

Owoola

2024

Preprint

Self Cite

View full text Add to dashboard Cite

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“…Also, wireless sensor network technology can be used to transmit audio data-an intercom system and multimedia system with low power consumption. Based on wireless technology and telecommunication networks based on them, it has well-known advantages among flexible configuration and low installation costs [2]. Currently, wireless communication systems can account for the mass and most popular number of systems in the consumer market.…”

Section: Related Workmentioning

confidence: 99%

“…Wireless sensor network technology has been developing intensively recently. However, only at the beginning, it was possible to produce a very cheap element base for devices such as the development of microelectronics [2]. Modern wireless networks are mainly based on the ZigBee standard [3].…”

Section: Introductionmentioning

confidence: 99%

Multicluster Analysis and Design of Hybrid Wireless Sensor Networks Using Solar Energy

Vino

Sivaraju²,

Krishna

et al. 2022

International Journal of Photoenergy

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A wireless touch network is a distributed, self-organizing network of multiple sensors and actuators in combination with multiple sensors and a radio channel. Also, the security area of such a network can be several meters to several meters. The main difference between wireless sensor networks from traditional computer and telephone networks is the lack of a fixed infrastructure owned by a specific operator or provider. Each user terminal in a touch network is capable of acting as a terminal device only. Despite the long history of sensor networks, the concept of building a sensor network is not finally imposed and expressed in some software and hardware (platform) solutions. In this paper, the design and analysis of multicluster model of the sensor nodes in wireless sensor network with the help of solar energy. This proposed model provides the required energy to transmit the information between two end nodes in different cluster. The communication between the end to end clusters was increased based on this design. The implementation of sensory networks at the current stage depends largely on the specific needs of the industrial problem. The architecture, software, and hardware implementation technology is at an intensive development stage, attracting the attention of developers looking for a technological niche of future makers.

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“…The purpose of quality control is to detect defects after a product has been developed, but before it is placed on the market [9]. In short, quality assurance is preferred to establish a good quality management system and assess its effectiveness in solar energy consumption analysis, while quality control is used to find and eliminate the sources of quality problems to meet customer requirements [10,11]. As such, with quality assurance, it is a technique that attempts to prevent quality problems in planned and systematic activities including certification [12].…”

Section: Introductionmentioning

confidence: 99%

An IOT Innovation of Smart Solar Energy Consumption Analysis and Control in Micro Grid

Krishnan

Sheela²,

Muthuraj³

et al. 2022

International Journal of Photoenergy

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Solar energy consumption is a systematic study used to review the design of facilities, services, and equipment in an organization against specifications of solar panel. The solar panel energy consumption analysis is a work that should be done at the beginning of a solar energy. This way, potential changes can be highlighted before they affect the solar energy budget and schedule. The proposed model provides the IOT-based smart solar energy consumption analysis and control model by using solar photovoltaic micro grid. The proposed IOT design must meet product and process requirements. The solar panel energy should properly address important aspects of production processes. This should include risks related to product quality and safety. Finally, unacceptable risks must be minimized by design. In the solar energy consumption analysis process, the deliverables should be evaluated; customers should precheck the proposed design and identify problematic areas, if any. Solar energy consumption analysis reveals whether user requirements and features are sufficient to achieve the desired outcome. Likewise, there should be corrective actions for discrepancies found in design reviews.

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Multi-Objective Optimization with Mayfly Algorithm for Periodic Charging in Wireless Rechargeable Sensor Networks

Cited by 7 publications

References 56 publications

Synthetic on-demand charging optimization with ADCMA for energy conservation in WRSN

Synthetic on-demand charging optimization with ADCMA for energy conservation in WRSN

Multicluster Analysis and Design of Hybrid Wireless Sensor Networks Using Solar Energy

An IOT Innovation of Smart Solar Energy Consumption Analysis and Control in Micro Grid

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