Fuzzy-EPO Optimization Technique for Optimised Resource Allocation and Minimum Energy Consumption with the Brownout Algorithm

In the context of the wide application of big data technology, it is particularly important to optimize the allocation of teaching methods and learning resources. This study first expounds the key role of big data in the optimization of teaching methods and the allocation of learning resources, and emphasizes how big data technology promotes the transformation and development of education and teaching models. Based on the analysis of traditional models of teaching method optimization and learning resource allocation, this study proposes a new model driven by big data. By accurately identifying students’ learning needs and behavior patterns, the model optimizes teaching methods and allocation of learning resources. This study introduces the whole process of data collection, cleaning, analysis and modeling. In the process, it shows how big data can be integrated, analyzed, and applied to further support the construction and validation of models. Through empirical research and effect evaluation, this study proves the validity of the model of teaching method optimization and learning resource allocation driven by big data, and demonstrates how big data can promote educational equity and improve educational quality.

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Fuzzy Allocation Optimization Algorithm for High-Density Storage Locations with Low Energy Consumptions

Gao,

Huang,

et al. 2024

EAI Endorsed Trans Energy Web

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The global demand for stored and processed data has surged due to the development of IoTs and similar computational structures, which has led to further energy consumption by concentrated data storage facilities and thus the demands of global energy and environmental needs. The current paper introduces Fuzzy Allocation Optimization Algorithm to mitigate energy consumption in high storage density settings. It uses the principles of Fuzzy logic to determine the best way to assign the tasks in relation to storage density necessity, urgency and energy consumption. Thus, the proposed approach incorporates fuzzy inference systems with multi-objective optimization methods where location of storage is dynamically assessed and assigned according to energy efficiency parameters. The findings of the simulation and case study prove that the algorithm is successful in saving energy while at the same time lowering storage I/O response time, which provides a viable solution to energy issues in evolving data centres. This work satisfies the lack of energy efficient algorithms in high density storage areas and responds to the recent calls for green technology and smart utilization of resources in the energy field. The findings are used in the promotion of significant IT infrastructures towards developing the next generation of energy efficient data centers with respect to Future Internet and evolving energy web environments.

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Fuzzy-EPO Optimization Technique for Optimised Resource Allocation and Minimum Energy Consumption with the Brownout Algorithm

Cited by 3 publications

References 31 publications

Big Data Resource Allocation of Animation Design Intelligent Education System Based on Ant Colony Algorithm

Big Data Resource Allocation of Animation Design Intelligent Education System Based on Ant Colony Algorithm

Optimization of teaching methods and allocation of learning resources under the background of big data

Fuzzy Allocation Optimization Algorithm for High-Density Storage Locations with Low Energy Consumptions

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