Integrating Green Infrastructure With AI-Driven Dynamic Workload Optimization for Sustainable Cloud Computing DOI

Vamshidhar Reddy Vemula

Advances in public policy and administration (APPA) book series, Год журнала: 2024, Номер unknown, С. 423 - 442

Опубликована: Дек. 5, 2024

The rapid growth of cloud computing has raised concerns about its environmental impact, particularly in terms energy consumption and carbon emissions. This chapter explores the integration green infrastructure with AI-driven dynamic workload optimization to promote sustainable practices. By leveraging AI algorithms, service providers can dynamically adjust resource allocation, optimize use, enhance overall operational efficiency. implementation infrastructure, including renewable sources energy-efficient data centers, further supports reduction ecological footprint associated services. examines principles strategies for achieving synergy between technologies presenting case studies that demonstrate successful implementations. findings indicate this integrated approach not only enhances sustainability but also improves cost-effectiveness resilience, positioning organizations meet both goals business objectives.

Язык: Английский

Leveraging Artificial Intelligence (AI) for Resilience in Industry 5.0 DOI
Tunde Toyese Oyedokun,

James Aransiola Ishola

Advances in business strategy and competitive advantage book series, Год журнала: 2025, Номер unknown, С. 35 - 68

Опубликована: Янв. 31, 2025

The incorporation of Artificial Intelligence (AI) within Industry 5.0 significantly enhances resilience among small businesses. This chapter explores how AI transforms resilience, sustainability, and customer engagement strategies. With Small businesses can analyze large datasets to identify risks, optimize operations, deliver personalized experiences that align with consumer expectations. AI's ability process data efficiently allows anticipate market changes navigate uncertainties. Additionally, adopting fosters a culture encouraging employees embrace change. also supports sustainable practices by optimizing resource use reducing waste. Customer improves through AI-driven personalization, allowing tailor products services individual preferences. concludes recommendations for businesses: invest in employee training collaboration, ensure leadership commitment, prioritize foster adaptability thrive today's 5.0.

Язык: Английский

Процитировано

1
AI-driven Dynamic Workload Balancing for Real-time Applications on Cloud Infrastructure DOI

Madhusudhan Dasari Sreeramulu,

Abdul Sajid Mohammed,

Dinesh Kalla

и другие.

Опубликована: Сен. 18, 2024

Язык: Английский

Процитировано

0
Integrating Green Infrastructure With AI-Driven Dynamic Workload Optimization for Sustainable Cloud Computing DOI

Vamshidhar Reddy Vemula

Advances in public policy and administration (APPA) book series, Год журнала: 2024, Номер unknown, С. 423 - 442

Опубликована: Дек. 5, 2024

The rapid growth of cloud computing has raised concerns about its environmental impact, particularly in terms energy consumption and carbon emissions. This chapter explores the integration green infrastructure with AI-driven dynamic workload optimization to promote sustainable practices. By leveraging AI algorithms, service providers can dynamically adjust resource allocation, optimize use, enhance overall operational efficiency. implementation infrastructure, including renewable sources energy-efficient data centers, further supports reduction ecological footprint associated services. examines principles strategies for achieving synergy between technologies presenting case studies that demonstrate successful implementations. findings indicate this integrated approach not only enhances sustainability but also improves cost-effectiveness resilience, positioning organizations meet both goals business objectives.

Язык: Английский

Процитировано

0