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Beginning with a fulsome description of ML and AI, the book moves on to discuss management models, architectures, and frameworks. The authors also explore how AI and ML can be used in service management functions like the generation of workload profiles, service provisioning, and more.   The book includes a handpicked selection of applications and case studies, as well as a treatment of emerging technologies the authors predict could have a significant impact on network and service management in the future. Statistical analysis and data mining are also discussed, particularly with respect to how they allow for an improvement of the management and security of IT systems and networks. 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IPAM applies management disciplines to these core services, including configuration, change control, auditing, reporting and so on, and they are necessary given the absolute requirement for properly managing IP space and DHCP and DNS servers. The linkages among an IP address plan, DHCP server configuration and DNS server configuration are inseparable; a change of an IP address will affect DNS information and perhaps DHCP as well. These functions provide the foundation for today's converged services IP networks, so they need to be managed using a rigorous approach.     Today, there is no single book that covers the management of these linkages and services they provide; IP Address Management Principles and Practice will fill that gap. While several books are available for leading vendors' DHCP and DNS services implementations, few exist for IP address planning, and none exist that unifies these three topics.     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In addition, the authors introduce their large-scale intelligent network management and operation system and elaborate on how the aforementioned areas can be integrated into this system, plus how the network service can benefit.    Sample ideas covered in this thought-provoking work include:      How cognitive means, e.g., knowledge transfer, can help with network and security management  How different advanced AI and machine learning techniques can be useful and helpful to facilitate network automation  How the introduced techniques can be applied to many other related network and security management tasks   Network engineers, content service providers, and cybersecurity service providers can use AI and Machine Learning for Network and Security Management to make better and more informed decisions in their areas of specialization. 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