This book presents innovative research works to automate, innovate, design, and deploy AI fo real-world applications. It discusses AI applications in major cutting-edge technologies and details about deployment solutions for different applications for sustainable development. The application of Blockchain techniques illustrates the ways of optimisation algorithms in this book. The challenges associated with AI deployment are also discussed in detail, and edge computing with machine learning solutions is explained. This book provides multi-domain applications of AI to the readers to help find innovative methods towards the business, sustainability, and customer outreach paradigms in the AI domain.

• Focuses on virtual machine placement and migration techniques for cloud data centres

• Presents the role of machine learning and meta-heuristic approaches for optimisation in cloud computing services

• Includes application of placement techniques for quality of service, performance, and reliability improvement

• Explores data centre resource management, load balancing and orchestration using machine learning techniques

• Analyses dynamic and scalable resource scheduling with a focus on resource management

The reference work is for postgraduate students, professionals, and academic researchers in computer science and information technology.

This book presents innovative research works to automate, innovate, design, and deploy AI fo real-world applications. It discusses AI applications in major cutting-edge technologies and details about deployment solutions for different applications for sustainable development. The application of Blockchain techniques illustrates the ways of optimisation algorithms in this book. The challenges associated with AI deployment are also discussed in detail, and edge computing with machine learning solutions is explained. This book provides multi-domain applications of AI to the readers to help find innovative methods towards the business, sustainability, and customer outreach paradigms in the AI domain.

• Focuses on virtual machine placement and migration techniques for cloud data centres

• Presents the role of machine learning and meta-heuristic approaches for optimisation in cloud computing services

• Includes application of placement techniques for quality of service, performance, and reliability improvement

• Explores data centre resource management, load balancing and orchestration using machine learning techniques

• Analyses dynamic and scalable resource scheduling with a focus on resource management

The reference work is for postgraduate students, professionals, and academic researchers in computer science and information technology.