Robust energy harvesting aware clustering with fuzzy petri net reasoning algorithm

Mostafa, Aya; Hassan, Khaled

doi:10.1109/wimob.2014.6962198

Cited by 6 publications

(5 citation statements)

References 14 publications

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“…The detailed summery is provided in tabular form as described in Table 3. In clustering-routing based schemes [28][29][30][31], even if they are meant for EH-WSN, the selection of the cluster head is based on residual energy of the node with no consideration of the predicted energy harvesting of the node. The question is: Will those schemes still ensure the energy harvesting capability when the energy harvesting system is uncontrollable and difficult to predict?…”

Section: Discussionmentioning

confidence: 99%

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Energy Harvesting in wireless communication: A survey

Yakine

Kenzi

2022

E3S Web Conf.

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Wireless Sensor Network is an emerging technology that has the potential to be used in futuristic applications. Sensor nodes are energy-constrained. They rely on batteries with limited capacity which impact their lifetime or mobility. To address this problem, energy harvesting technology is a solution that aims to avoid the premature energy depletion of nodes. It recharges their batteries using an energy harvesting system from the environment. In this review work, we present the concept of energy harvesting technology (EH) and Energy-Harvesting for Wireless Sensor Network (EH-WSN). We then discuss many schemes in the literature to save energy consumption of the energy harvesting sensor networks. We study their protocol design strategies and working principals. We also summarize their merits, demerits along with some future research directions.

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Section: Discussionmentioning

confidence: 99%

“…EHOR has maximized goodput and efficiency of the network. Energy Harvesting aware clustering with Fuzzy Petri (EHFP) was proposed in [29]. It selects the cluster heads considering the harvested energy, concentration and the centrality of each node.…”

Section: Clustering and Routing Based Schemesmentioning

confidence: 99%

Energy Harvesting in wireless communication: A survey

Yakine

Kenzi

2022

E3S Web Conf.

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“…This algorithm optimizes the energy consumption at the utmost level. In [17], by using fuzzy PNs, an energy harvesting aware algorithm for selecting cluster heads was introduced to keep the WSN alive for much longer time. However, its impact on the functionality of WSNs was not considered.…”

Section: Related Workmentioning

confidence: 99%

Evaluation of the functionality of mobile wireless sensor networks using stochastic reward nets

Naghash Asadi,

Abdollahi Azgomi,

Entezari-Maleki

2023

Scientia Iranica

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In this paper, the functionality of Mobile Wireless Sensor Networks (MWSNs) is analytically modeled and evaluated using Stochastic Reward Nets (SRNs). In MWSNs, mobile nodes can move around to collect data from the environment and send them to the sink. These nodes use a limited battery as the power source which can be charged according to environmental conditions. If the battery does not have enough power, the mobile node is disabled and, therefore, it cannot move around to collect/send data. The data collected by the nodes will expire if they are not received by the sink in a timely manner. In order to avoid data expiration, mobile nodes can send their data to other nodes around themselves, but this also increases the power consumption because of further communication. Furthermore, moving faster in the environment, the power consumption of the nodes increases. Therefore, environmental and movement conditions as well as communication between nodes can have a major impact on the functionality of the MWSNs. These challenges are considered in the paper and the proposed models analyze the impact of di erent conditions on the functionality of MWSNs. The results obtained from the comparison of di erent scenarios demonstrate that the environmental and movement conditions have a greater impact on system functionality than the communication conditions.

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“…Mostafa and Hassan [133] Number of alive nodes (i) A new clustering algorithm has been presented for EH-WSNs in which three factors are considered primarily such as sensor node centrality, amount of energy harvested, and the total neighbors. (ii) Next, fuzzy petri nets are used in the proposed algorithm for selecting the cluster heads.…”

Section: Challenges In Eh-wsns For Formulatingmentioning

confidence: 99%

Green Communication for Next‐Generation Wireless Systems: Optimization Strategies, Challenges, Solutions, and Future Aspects

Rathore

Sangwan

Kaiwartya

et al. 2021

Wireless Communications and Mobile Computing

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Wireless sensor networks (WSNs) have emerged as a backbone technology for the wireless communication era. The demand for WSN is rapidly increasing due to their major role in various applications with a wider deployment and omnipresent nature. The WSN is rapidly integrated into a large number of applications such as industrial, security, monitoring, tracking, and applications in home automation. The widespread use in many different areas attracts research interest in WSNs. Therefore, researchers are taking initiatives in exploring innovation day by day particularly towards the Internet of Things (IoT). But, WSN is having lots of challenging issues that need to be addressed, and the inherent characteristics of WSN severely affect the performance. Energy constraints are one of the primary issues that require urgent attention from the research community. Optimal energy optimization strategies are needed to counter the issue of energy constraints. Although one of the most appropriate schemes for handling energy constraints issues is the appropriate energy harvesting technique, the optimal energy optimization strategies should be coupled together for effectively utilizing the harvested energy. In this high-level systematic and taxonomical survey, we have organized the energy optimization strategies for EH-WSNs into eleven factors, namely, radio optimization schemes, optimizing the energy harvesting process, data reduction schemes, schemes based on cross-layer optimization, schemes based on cross-layer optimization, sleep/wake-up policies, schemes based on load balancing, schemes based on optimization of power requirement, optimization of communication mechanism, schemes based on optimization of battery operations, mobility-based schemes, and finally energy balancing schemes. We have also prepared the summarized view of various protocols/algorithms with their remarkable details. This systematic and taxonomy survey also provides a progressive detailed overview and classification of various optimization challenges for the EH-WSNs that require attention from the researcher followed by a survey of corresponding solutions for corresponding optimization issues. Further, this systematic and taxonomical survey also provides a deep analysis of various emerging energy harvesting technologies in the last twenty years of the era.

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Robust energy harvesting aware clustering with fuzzy petri net reasoning algorithm

Cited by 6 publications

References 14 publications

Energy Harvesting in wireless communication: A survey

Energy Harvesting in wireless communication: A survey

Evaluation of the functionality of mobile wireless sensor networks using stochastic reward nets

Green Communication for Next‐Generation Wireless Systems: Optimization Strategies, Challenges, Solutions, and Future Aspects

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