A review on rendezvous based data acquisition methods in wireless sensor networks with mobile sink

Mehto, Anjula; Tapaswi, Shashikala; Pattanaik, K. K.

doi:10.1007/s11276-019-02022-6

Cited by 31 publications

(14 citation statements)

References 81 publications

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“…A considerable number of higher vocational students are unable to handle the difficulties they encounter correctly, making them feel lost and confused, and some of them even develop psychological disorders. To make students develop comprehensively, they must first have a good and healthy mind to form a stable and healthy personality [11]. With a healthy mind, we can face difficulties and setbacks in life, learning, and emotions; actively cope with challenges and competition and other pressures; face success and failure optimistically; and face gains and losses frankly.…”

Section: Related Workmentioning

confidence: 99%

Construction of an Intelligent Evaluation Model of Mental Health Based on Big Data

Zhang¹,

Liang²

2022

Journal of Sensors

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In this paper, mental health data were used to evaluate the educational effects, in which the high and low scorers of three emotions, autism, positivity, and anxiety, are compared separately to explore the subtle differences in the long-term trends of the sensing traits of people with opposite characteristics. Based on the fusion of multiple kinds of sensing traits, the differences in physical and mental health assessment of positive and negative emotions by different fusion trait approaches are explored, and speech and behavioural traits are fused to build a physical and mental health assessment system for positive and negative emotions. Energy gravity uses physical distance to estimate the residual energy of nodes and considers the energy distribution of downstream nodes. The main work is to combine the data of mental health of higher education students using data mining techniques, to analyze the feasibility study of mental health education of college students. Relevant definitions, classifications, tasks, processes, and application areas of data mining techniques are introduced, and the basic principles of data mining are analyzed in detail. Taking the mental health assessment data of new students as the research object, the decision tree algorithm is used to construct a decision tree model for students with depressive symptoms, and an association rule algorithm is used to data mine the relationship between factors of psychological dimensions. Finally, it can find out the hidden laws and knowledge behind the data information and analyze the relationship that exists between psychological problems and students.

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Section: Related Workmentioning

confidence: 99%

Construction of an Intelligent Evaluation Model of Mental Health Based on Big Data

Zhang¹,

Liang²

2022

Journal of Sensors

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“…A method for improving WSN connection is presented by Renato et al [22]. In addition, Kim and Kim [23] have provided an IEEE 802.15.4 clustering technique that is effective for the frequency series. Most of the works provided more energy consumption.…”

Section: Related Workmentioning

confidence: 99%

Modern Energy Optimization Approach for Efficient Data Communication in IoT-Based Wireless Sensor Networks

Kumar

Ahmad

Routray

et al. 2022

Wireless Communications and Mobile Computing

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Many researchers are drawn to mobile wireless sensor networks (WSN) and the Internet of Things (IoT) because of the significant challenges of power consumption and network connectivity. A technique that takes into consideration the characteristics such as network probability, the identified region of individual nodes, and the radius of the whole identified region is presented in this article. Free-space propagation is carried out in the region of interest. This approach assures network connection, long-term communication sustainability, and maximum energy efficiency. It was discovered that a mathematical network model can be built using the probability theory. It has been possible to examine and evaluate the changes in sensor nodes as a function of distance from the detection region using this approach. As a result, a correlation has been established between a network’s communication radius and the identified region. Additionally, a novel method has been developed to reduce energy consumption and sustain connectivity through boosting the connectivity feature. Notably, IoT-based WSN architectures require more energy optimization than any other network, because they have resource-limited nodes. Also, a simulation plot of the proposed approach’s mathematical network scheme is shown to show if it works. The proposed method consumes much less energy averagely 40% compared to the existing methods, which are LEACH, ZTR, and DSR when the radius is 100.

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“…For critical applications, TEEN is applied well and it is also implemented with efficiency in terms of response time and energy conservation. In [12], the context of mobile sink is proposed by author for solving the energy-hole problem. In [13], a novel hierarchical approach termed as distributed energy efficient adaptive clustering protocol with data gathering (DEACP) is presented.…”

Section: Related Workmentioning

confidence: 99%

Energy efficient routing in wireless sensor network based on mobile sink guided by stochastic hill climbing

Raghavendra¹,

Mahadevaswamy²

2020

IJECE

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In Wireless Sensor Networks (WSNs), the reduction of energy consumption in the batteries of a sensor node is an important task. Sensor nodes of WSNs perform three significant functions such as data sensing, data transmitting and data relaying. Routing technique is one of the methods to enhance the sensor nodes battery lifetime. Energy optimization is done by using one of the heuristic routing methods for sensing and transmitting the data. To enhance the energy optimization mainly concentrated on data relaying. In this work stochastic hill climbing is adapted. The proposed solution for data relaying utilizes geographical routing and mobile sink technique. The sink collects the data from cluster heads and movement of the sink is routed by stochastic hill climbing. Network simulator 2 is used for experimentation purpose. This work also compares with the existing routing protocols like Energy-efficient Low Duty Cycle (ELDC), Threshold sensitive Energy Efficient sensor Network (TEEN) and Adaptive clustering protocol. The proposed work shows promising results with respect to lifetime, average energy of nodes and packet delivery ratio.

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A review on rendezvous based data acquisition methods in wireless sensor networks with mobile sink

Cited by 31 publications

References 81 publications

Construction of an Intelligent Evaluation Model of Mental Health Based on Big Data

Construction of an Intelligent Evaluation Model of Mental Health Based on Big Data

Modern Energy Optimization Approach for Efficient Data Communication in IoT-Based Wireless Sensor Networks

Energy efficient routing in wireless sensor network based on mobile sink guided by stochastic hill climbing

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