دانلود کتاب هوش مصنوعی در لبه با امنیت – مبانی و شیوه ها

The idea for this book took birth in Fremont, California, in a meeting of Naresh Kumar Sehgal and Dhaval N. Shah with Prof. PCP Bhatt, who was visiting California from India in the Summer of 2023. Prof. Bhatt is the author of one of the most widely used Operating Systems book, which is in its 5th edition in India. He and Naresh had co-authored three books on Cloud Computing and noted a trend to move computing out of data centers closer to the customers. Serendipitously, Dhaval, in his AI Consulting work was sensing a need for a book in this area too. Thus a new book on Edge Computing was jointly conceived. Subsequently, Prof. Bhatt intro-duced Naresh and Dhaval to Dr. Manoj Saxena, who had completed his Ph.D. with Prof. Bhatt. Manoj is operating a successful business related to Distributed and Edge Computing in India for over three decades. A traditional data center consists of racks of servers, storage, and network devices in a large, air-conditioned facility. Then scores of clients and IoT (Internet of Things) devices interact with this data center over public and private networks. However, this setup causes latency which is unacceptable for real-time computing applications that can involve instant decision-making using AI. There is a need to support AI applications at or near the edge of computing networks to minimize latency and to address data privacy concerns. Such concerns currently cause many customers such as hospitals to not put their data in the Clouds. In this book, we review the solution architectures and algorithms to support AI in the edge comput-ing devices. Computing growth often mimics biology, which has recently resulted in an explosion of AI and ML applications to the real-life problems. Next step in this evolution is Intelligent IoT devices. Which can perform some AI and ML at the edge of networks. The net result will be alleviation of a need to transfer lots of data to the faraway datacenters and mimic intelligent entities making autonomous decisions while interacting with each other. Such a revolution will turn Cloud computing on its head to de-centralize the control back to the edge devices. There are many books on IoT, Cloud Computing, and AI/ML, but these are treated as three different topics currently. We aim to connect the dots and show read-ers the power of combining these in a single setup. Result will be lower electrical power, latency, and higher security. Next generation of Cloud computing is needed to minimize latency and address privacy/security concerns of many customers. This book highlights the problems and proposes new solutions for performing AI and ML at the Edge of computing networks. We introduce some new concepts such as Collaborative Federated Learning in the context of data privacy and Edge Computing. As a textbook, our target audience are students in Computer Science, Information Technology, and professionals practicing AI or Edge Computing. Readers will learn about new topics to prepare themselves for the next steps in evolution of Cloud Computing in context of Security, AI, and Edge. The book assumes some background and understanding of basic hardware, operating systems, and some aspects of software engineering. To that extent it would suit senior under graduates or graduates in their early semesters. As a technical manuscript, the book has enough in-depth coverage to interest IT managers and architects who need to develop solutions for Edge Computing. Our book provides a strong foundation of Cloud, Security, IoT, AI/ML, and Networking before building a case for “Secure AI on the Edge of the Cloud.” This enables our book to serve as a textbook at the upper UG or graduate level of classes.