LISA: a lean information service architecture for SLA management in multi-cloud environments

Sfondrini, Nicola; Motta, Gianmario

doi:10.1504/ijguc.2021.114824

Cited by 4 publications

(2 citation statements)

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“…Some scholars believe that using intelligent algorithms in cloud computing server management can effectively simplify the amount of data in cloud computing and reduce the complexity of data [4]. Some scholars believe that applying intelligent algorithms in cloud computing server management can better conduct data analysis [5], identify characteristic data from multiple angles [6], and improve the accuracy of management [7].…”

Section: Introductionmentioning

confidence: 99%

An Empirical Study on Machine Learning for Enterprise Cloud Computing Service Management

Liu

2023

AJEBA

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A machine learning method is proposed to aim at the problems of large data processing, complex data, and limited system resources in cloud computing service management. First, multi-department analysis is carried out on cloud service management data, and relevant management data is standardized to form a standardized management data collection; Machine learning is used to classify, mine, and extract service management data, and corresponding management measures are taken promptly to improve the management level of cloud computing services. MATLAB simulation shows that machine learning can improve the level of cloud computing service management, simplify the process of cloud computing service management, shorten the management time of cloud computing services, and meet the actual needs of service management.

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Section: Introductionmentioning

confidence: 99%

An Empirical Study on Machine Learning for Enterprise Cloud Computing Service Management

Liu

2023

AJEBA

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“…To begin, it is proposed that cloud technology may mature sooner than expected, providing a chance for businesses to obtain a competitive edge in the face of technological breakthroughs and uncertainties(Srivastava et al, 2021). Second, testing results show that cloud computing is effective and e cient, including its capacity to prevent SLA violations, optimize QoS, and manage service components across numerous cloud providers(Fuzes, 2020;Sfondrini & Motta, 2021). Furthermore, the study emphasizes the revolutionary impact of cloud computing on the industry, particularly in emerging markets, and the rami cations for companies such as Oracle (BruqueCamara et al, 2015).…”

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confidence: 99%

Examining the Role of Digital Technology as an Enabler of Digital Disruption: A Systematic Review

lei,

Indiran,

Kohar

et al. 2023

Preprint

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This systematic review critically analyzes the intricate relationship between digital technology and digital disruption by examining 83 papers from the Scopus database. Utilizing a systematic literature review methodology, the study delves into the impact of key technologies like artificial intelligence, blockchain, 3D printing, Internet of Things, big data, and cloud computing. Findings underscore the substantial role of digital tech in prompting disruption, challenging norms, and reshaping industry boundaries. Notably, artificial intelligence emerges as a major influencer, prompting organizations to reassess business strategies. The analysis explores collaborative and democratizing effects driven by platforms like IoT, blockchain, big data, and cloud computing. The results offer practical insights for enterprises, policymakers, and practitioners, emphasizing the transformative potential of digital technologies. Key drivers include operational efficiency, predictive analytics, personalization, and supply chain integration. Recognition of synergies among digital technologies provides strategic guidance for fostering innovation and gaining a competitive edge. Societal consequences and adoption challenges are examined, highlighting the importance of stakeholder reactions, decision-making processes, governance, and user acceptance in successful implementation.

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Conformance checking for autonomous multi-cloud SLA management and adaptation

et al. 2022

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LISA: a lean information service architecture for SLA management in multi-cloud environments

Cited by 4 publications

References 0 publications

An Empirical Study on Machine Learning for Enterprise Cloud Computing Service Management

An Empirical Study on Machine Learning for Enterprise Cloud Computing Service Management

Examining the Role of Digital Technology as an Enabler of Digital Disruption: A Systematic Review

Conformance checking for autonomous multi-cloud SLA management and adaptation

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