Management of cloud resources and social change in a multi-tier environment: A novel finite automata using ant colony optimization with spanning tree

Aliyu, Muhammad; Murali, M.; Zhang, Zuopeng; Gital, Abdulsalam Ya’u; Boukari, Souley; Huang, Yongbin; Yakubu, Ismail Zahraddeen

doi:10.1016/j.techfore.2021.120591

Cited by 9 publications

(3 citation statements)

References 24 publications

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“…If there is a link in w i to w j , the ant in w i will decide whether to move from w i to w j according to certain conditions. Each link sequence represents a possible ant movement route [15]. Individual ants transmit information through pheromones during movement.…”

Section: Collection Of College English Teaching Information Resourcesmentioning

confidence: 99%

Construction of College English Teaching Information Resource Integration Model Based on Fuzzy Clustering Algorithm

Hua

2022

Mobile Information Systems

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The existing college English teaching information resource integration methods have problems of low recall rate, low accuracy rate, and long integration time. Therefore, this paper constructs a college English teaching information resource integration model based on fuzzy clustering algorithm. The ant colony algorithm is used to optimize the topic crawler, the optimized topic crawler is used to collect the college English teaching information resources in the mixed teaching mode, and the weight and naive Bayes algorithm are combined to classify the collected resources. According to the results of resource classification, fuzzy clustering algorithm is used to construct the integration model of college English teaching information resources. The experimental results show that the recall rate of the proposed model is more than 95%, the accuracy rate is more than 94%, and the average resource integration time is only 0.71 s, indicating that the model has relatively reliable performance.

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Section: Collection Of College English Teaching Information Resourcesmentioning

confidence: 99%

Construction of College English Teaching Information Resource Integration Model Based on Fuzzy Clustering Algorithm

Hua

2022

Mobile Information Systems

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“…In the above equations, N is the number of requests for cloud resource storage, and p drop ' represents the packet loss rate of data storage under the data storage behavior of university financial system process operation under the specific network blockchain environment [19]. Through the above data structure design of cloud resources, the packet loss rate can be effectively reduced, and the storage performance can be improved through the map design [20].…”

Section: University Financial Data Structure Analysis and Information...mentioning

confidence: 99%

A Secure Cloud Storage Algorithm for University Financial Data Based on the Blockchain Technology

Zhang

Geng

2022

Mobile Information Systems

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In order to increase the secure storage capacity of university financial system process operation data under the blockchain environment, a secure cloud storage algorithm of university financial data based on the blockchain technology is proposed. The blockchain storage structure model of university financial system process operation data is first constructed, and then the mapping method of Atlas features is adopted. Finally, the blockchain equilibrium configuration parameter analysis model of university financial system process operation data is established. According to the outcomes of the feature extraction process of cloud resource storage Atlas of university financial system process operation data, the fuzzy clustering method is implemented to comprehend the rational planning of cloud storage space. The resource cloud storage structure configuration of university financial system process operation data in cloud environment is realized by using the method of block link fusion and channel equilibrium configuration. The multi-layer modal structure decomposition and fuzzy clustering processing are carried out on university financial system process operation data storage information in blockchain environment by using the empirical mode decomposition method. According to the data graph clustering results, the cloud resource graph of university financial system process operation data becomes smooth in the adjacent wave domain through cloud information fusion and block clustering, which effectively reduces the data storage overhead and improves the secure cloud storage capability of university financial data. The simulation outcomes indicate that this approach can significantly increase the storage performance of process operation data of university financial system under blockchain environment, with better data classification storage, internal structure information fusion performance of university financial data, and lower storage overhead than other methods. We observed that this improvement, in terms of storage overhead costs, can be as high as 43.67% higher than the wavelet method and 30.45% higher than the mode decomposition approach.

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“…These studies analyzed data center energy estimates published between 2007 and 2021 and identified two main areas of focus in this published research: (1) data center energy consumption and reduction, and (2) measures that could be used to mitigate the environmental impact of GHG emissions, particularly by transitioning to cleaner energy sources for power generation (Mytton and Ashtine 2022;Zhao and Zhou 2022). Researchers have proposed various strategies to reduce carbon emissions from data centers, such as improving their power usage effectiveness (PUE) and managing the data centers via new algorithms (Deymi-Dashtebayaz et al 2019;Lei and Masanet 2020;Aliyu et al 2021). Additionally, authors have discussed how carbon emissions reductions could be accomplished by shifting from fossil-based energy to renewable energy sources (Zhao and Zhou 2022;Shen et al 2023).…”

Section: Introductionmentioning

confidence: 99%

Greening China’s digital economy: exploring the contribution of the East–West Computing Resources Transmission Project to CO2 reduction

Xie,

Han,

Tan

2024

Humanit Soc Sci Commun

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China’s East–West Computing Resources Transmission Project (EWCRT Project) is a unique and innovative path toward developing China’s green digital economy. The EWCRT Project consists of building transregional digital infrastructure, including eight data center hubs and 10 data center clusters across China. Our estimations indicate that the EWCRT Project could result in a reduction of 2125 metric tons (Mt) of CO2 between 2020 and 2050. Combined with other improvement measures, such as an increase in power usage effectiveness (PUE) and a boost in the use of green electricity in these data centers, the project could result in a reduction of 9500 Mt of carbon emissions over the next three decades. Recognizing the heterogeneous makeup of data centers in general, it is crucial to identify diverse strategies that can transform each into “green engines” for the digital economy. Therefore, in this study, we use fuzzy-set qualitative comparative analysis (fsQCA) to characterize the complex conditions of different data center configurations. By doing so, we highlight differentiated strategies for data centers to support the greening of the digital economy.

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Management of cloud resources and social change in a multi-tier environment: A novel finite automata using ant colony optimization with spanning tree

Cited by 9 publications

References 24 publications

Construction of College English Teaching Information Resource Integration Model Based on Fuzzy Clustering Algorithm

Construction of College English Teaching Information Resource Integration Model Based on Fuzzy Clustering Algorithm

A Secure Cloud Storage Algorithm for University Financial Data Based on the Blockchain Technology

Greening China’s digital economy: exploring the contribution of the East–West Computing Resources Transmission Project to CO2 reduction

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