ADAPTIVE AI-ORCHESTRATION AND ZERO-TRUST SECURITY WITH FEDERATED THREAT INTELLIGENCE FOR SUSTAINABLE ENTERPRISE CLOUD ARCHITECTURES
DOI:
https://doi.org/10.63519/IJCSERD_12_01_013Keywords:
Cloud Computing, Artificial Intelligence, Secure Cloud, Green Computing, Resource Optimization, Sustainable ComputingAbstract
Scalability, security and energy efficiency are critical components of computing infrastructure for Artificial Intelligence (AI) applications. Cloud-based architectures face many obstacles, including dynamic management of workloads, security issues, optimizing resources, and growing energy usage. This paper puts forward a scalable cloud architecture, which combines the integration of AI-based resource orchestration with secure computing mechanisms and sustainable cloud optimization techniques. The proposed architecture is a mix of technologys which are cloud-native, use machine learning for workload prediction, automatically allocate resources and are based on the “Zero trust” approach in security and green computing technologies. It allows for intelligent decisions on VMs/containers deployment to resources, adaptive threat detection for security resiliency and workload-aware resource management for energy savings. The scalability, latency, resource usage, security efficiency, and energy optimization are the metrics that were used to evaluate the proposed model. The architecture proposed is validated experimentally and it is found that the proposed architecture is more energy efficient, lower latency and better resource utilization in comparison to traditional cloud architectures. It provides a comprehensive architecture to support next generation cloud scenarios, to mitigate AI workloads, business applications and large distributed systems.
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