Performance Evaluation of Brahmagupta-Bhaskara Equation Based Algorithm Using OpenMP

Narayanan, V.G.; Kavitha, R.; Ryali, Srikanth

doi:10.1007/978-981-16-6289-8_3

Cited by 3 publications

(1 citation statement)

References 10 publications

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“…Parallel computing is a computing model relative to serial computing [ 92 ]. In this mode, multiple computing processes are performed simultaneously, which is different from the conventional computing method that is performed sequentially [ 93 ]. As shown in Figure 7 , users write a series of computer instructions for specific problems to form tasks.…”

Section: Parallel Computingmentioning

confidence: 99%

Big Data Analytics Using Cloud Computing Based Frameworks for Power Management Systems: Status, Constraints, and Future Recommendations

AL-Jumaili

Muniyandi

Hasan

et al. 2023

Sensors

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Traditional parallel computing for power management systems has prime challenges such as execution time, computational complexity, and efficiency like process time and delays in power system condition monitoring, particularly consumer power consumption, weather data, and power generation for detecting and predicting data mining in the centralized parallel processing and diagnosis. Due to these constraints, data management has become a critical research consideration and bottleneck. To cope with these constraints, cloud computing-based methodologies have been introduced for managing data efficiently in power management systems. This paper reviews the concept of cloud computing architecture that can meet the multi-level real-time requirements to improve monitoring and performance which is designed for different application scenarios for power system monitoring. Then, cloud computing solutions are discussed under the background of big data, and emerging parallel programming models such as Hadoop, Spark, and Storm are briefly described to analyze the advancement, constraints, and innovations. The key performance metrics of cloud computing applications such as core data sampling, modeling, and analyzing the competitiveness of big data was modeled by applying related hypotheses. Finally, it introduces a new design concept with cloud computing and eventually some recommendations focusing on cloud computing infrastructure, and methods for managing real-time big data in the power management system that solve the data mining challenges.

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Section: Parallel Computingmentioning

confidence: 99%

Big Data Analytics Using Cloud Computing Based Frameworks for Power Management Systems: Status, Constraints, and Future Recommendations

AL-Jumaili

Muniyandi

Hasan

et al. 2023

Sensors

View full text Add to dashboard Cite

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Analyzing Programming Effort Model Accuracy of High-Level Parallel Programs for Stream Processing

Andrade

Griebler

Santos

et al. 2022

2022 48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

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An Extensive Review of the Literature Using the Diophantine Equations to Study Fuzzy Set Theory

Abirami,

Veena,

Srikanth

et al. 2024

International Journal of Mathematics and Mathematical Sciences

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Every field in mathematics has made significant progress in research with fuzzy sets. Numerous application fields were discovered in both empirical and theoretical investigations, ranging from information technology to medical technology, from the natural sciences to the physical sciences, and from technical education to fine arts education. However, it has limitations of its own and has not been able to function in real‐world situations. An interdisciplinary approach of fuzzy theory with number theory, especially Diophantine equations, needs to be accomplished to overcome this problem. A thorough literature study of the Diophantine equations, fuzzy sets, and the combination known as the linear Diophantine fuzzy set (LDFS) is accomplished in the present study. New forms of LDFSs have been added recently, and these additions have found use in a variety of fields, including the disciplines of pharmacology, power, healthcare, goods, and finance. The genesis of these expansions is also examined in this study of the literature. Hence, in the present work, some applications of LDFS are described in detail. Further in the present study, the existing primary constraints in the research on LDFS are highlighted. Also, the last section of the review is dedicated to outlining some future directions for the study of LDFS.

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Performance Evaluation of Brahmagupta-Bhaskara Equation Based Algorithm Using OpenMP

Cited by 3 publications

References 10 publications

Big Data Analytics Using Cloud Computing Based Frameworks for Power Management Systems: Status, Constraints, and Future Recommendations

Big Data Analytics Using Cloud Computing Based Frameworks for Power Management Systems: Status, Constraints, and Future Recommendations

Analyzing Programming Effort Model Accuracy of High-Level Parallel Programs for Stream Processing

An Extensive Review of the Literature Using the Diophantine Equations to Study Fuzzy Set Theory

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