Enhanced-Pro: A New Enhanced Solar Energy Harvested Prediction Model for Wireless Sensor Networks

Deb, Moumita; Roy, Sarbani

doi:10.1007/s11277-020-07913-y

Cited by 12 publications

(4 citation statements)

References 8 publications

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“…Through experimental comparison, IPro-Energy achieves satisfactory performance in short-, medium-, and long-term prediction. Deb et al [25] combined past and current harvested energy information to improve Pro-Energy and proposed a new energy-prediction algorithm, Enhanced-Pro, which uses the correlation coefficient to select matching configuration files and selects a tuning algorithm to check the difference between the selected file and the specific situation of the day. Finally, the prediction equation is used to obtain the prediction result.…”

Section: Pro-energy and Its Related Methodsmentioning

confidence: 99%

Energy Prediction for Energy-Harvesting Wireless Sensor: A Systematic Mapping Study

Yuan,

Ge,

Wei

et al. 2023

Electronics

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Energy prediction plays a significant role in energy-harvesting wireless sensors (EHWS), as it helps wireless sensors regulate their duty cycles, achieve energy neutrality, and extend their lifespan. To explore and analyze advanced technologies and methods regarding energy prediction for EHWS, this study identifies future research directions and addresses the challenges faced based on the current research status, assisting with future literature research. This scholarly inquiry delineates future research prospects and addresses prevailing challenges within the context of the extant research landscape, thereby facilitating prospective scholarly endeavors. This study employed the systematic mapping study (SMS) approach to screen and further investigate the relevant literature. After searching and screening for papers from the ACM, IEEE Xplore, and Web of Science (WOS) databases from January 2007 to December 2022, 98 papers met the requirements of this study. Subsequently, the SMS was conducted for five research questions. The results showed that the solution proposal type category had the largest proportion among all research types, accounting for 58% of the total number, indicating that the research focusing on this field is placed on improving the existing methods or proposing new ones. Additionally, based on the SMS analysis, this study provides a systematic review of the technical utilization and improvement approaches, as well as the strengths and limitations of the selected prediction methods. Furthermore, by considering the current research landscape, this paper identifies the existing challenges and suggests future research directions, thereby offering valuable insights to researchers for making informed decisions regarding their chosen paths. The significance of this study lies in its contribution to driving advancements in the field of energy-harvesting wireless sensor networks. The importance of this study is underscored by its contribution to advancing the domain of energy-harvesting wireless sensor networks, thereby serving as a touchstone for forthcoming researchers in this specialized field.

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Section: Pro-energy and Its Related Methodsmentioning

confidence: 99%

Energy Prediction for Energy-Harvesting Wireless Sensor: A Systematic Mapping Study

Yuan,

Ge,

Wei

et al. 2023

Electronics

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“…In this model, various nodes have different EH rates, depending on several uncontrollable factors (e.g., position, shadows, light intensity). Using the conclusions of previous works [33,34], the variation of EH rate at different instants of a day can be abstracted as Fig. 5.…”

Section: Eh Modelmentioning

confidence: 99%

A Biodynamics Inspired Routing Algorithm for Energy Harvesting-aided 3-D Wireless Sensor Networks

Hao,

Chen,

Hong

et al. 2024

Preprint

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Energy Harvesting (EH) has emerged as a signiffcant technology capable of constructing future wireless sensor networks (WSNs). Although a signiffcant body of studies has focused on designing routing algorithms for EH-aided WSN so that the harvested energy can be efffciently used, most of them do not adequately consider energy overffow and waste caused by the limited battery capacity and data buffer. In addition, these works only concentrated on twodimensional (2-D) plane scenario. In practical environment, sensor nodes are generally deployed in three-dimensional (3-D) space. In light of the above limitations, a brand-new biodynamics inspired energy-efffcient routing algorithm used for EH-aided 3-D WSN is proposed (BDRATD for short). Firstly, through fully considering the spatial distribution of nodes (including planar and vertical dimensionality), we design a classiffed channel model adapted to 3-D spatial communication conditions. On this basis, an energy assessment model is is built to determine the energy state of nodes. Next, we establish a buffer queuing model to detect the blocking level of nodes. Combining the above models, we further consider the inffuence of IEEE 802.11b medium access control (MAC) protocol, and design an idle energy prediction mechanism to improve power utilization. With the help of hemodynamics, we provide the path selection strategy of BDRA-TD for EH-aided 3-D WSN. Moreover, we analyze the complexity of our algorithm and demonstrate it has convergent property. Extensive simulation results show that our algorithm performs superior in terms of average end-to-end delay, average energy dissipation, packet success ratio, average residual energy and acceptable performance in average energy variance compared to other algorithms.

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“…This paper designs the Medium Access Control (MAC) protocol [9][10][11], which operates on the basis of Predicted Maximum Duty Cycle. This designed protocol is calculated on using the forecasted Harvested and Residual Energy.…”

Section: Major Contributionsmentioning

confidence: 99%

Facebook Prophet Library prediction-based Energy Harvested MAC Protocol (FPEH-MAC)

Verma,

Srikant

2023

ijmst

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Data transfer within severe time constraints is crucial for wireless sensor networks used in mission-critical applications, such as industrial control and disaster monitoring. In such applications, exceeding time constraints and facing limitations in longevity can pose threats to human life. The primary option for powering wireless sensor networks is to utilize ambient energy sources like solar energy, thermal energy, etc., which are abundant in nature The lifetime and latency of these networks depend on a well-implemented duty cycle-based MAC protocol, and maximizing the duty cycle is achieved through efficient utilization of harvested and residual energy. Since harvested energy is inherently unpredictable, appropriate forecasting techniques are required. In this study, a prediction-based Energy Harvested MAC protocol (FPEH-MAC) based on the Facebook Prophet library is proposed to maximize the predicted duty cycle of the MAC protocol by forecasting harvested and residual energy. Additionally, this MAC protocol demonstrates an increase in residual energy and duty cycle, ensuring an extended lifecycle for the wireless sensor network. The suggested protocol was evaluated for latency, throughput, percentage increase in residual energy, and packet delivery ratio using OMNET, INET, Python, and MATLAB. The results of the analysis indicate that the proposed technique increases residual energy by 1.2%, enhances throughput by 33.33%, and reduces latency by 9.6% when compared to previous work.

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Enhanced-Pro: A New Enhanced Solar Energy Harvested Prediction Model for Wireless Sensor Networks

Cited by 12 publications

References 8 publications

Energy Prediction for Energy-Harvesting Wireless Sensor: A Systematic Mapping Study

Energy Prediction for Energy-Harvesting Wireless Sensor: A Systematic Mapping Study

A Biodynamics Inspired Routing Algorithm for Energy Harvesting-aided 3-D Wireless Sensor Networks

Facebook Prophet Library prediction-based Energy Harvested MAC Protocol (FPEH-MAC)

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