Guest Editorial: Special section on embracing artificial intelligence for network and service management

Artificial Intelligence (AI) has the potential to leverage the immense amount of operational data of clouds, services, and social and communication networks. As a concrete example, AI techniques have been adopted by telcom operators to develop virtual assistants based on advances in natural language processing (NLP) for interaction with customers and machine learning (ML) to enhance the customer experience by improving customer flow. Machine learning has also been applied to finding fraud patterns which enables operators to focus on dealing with the activity as opposed to the previous focus on detecting fraud

Guest Editorial: Special issue on data analytics and machine learning for network and service management-Part II

Network and Service analytics can harness the immense stream of operational data from clouds, to services, to social and communication networks. In the era of big data and connected devices of all varieties, analytics and machine learning have found ways to improve reliability, configuration, performance, fault and security management. In particular, we see a growing trend towards using machine learning, artificial intelligence and data analytics to improve operations and management of information technology services, systems and networks

Guest Editorial: Special issue on data analytics and machine learning for network and service management-Part II

Network and Service analytics can harness the immense stream of operational data from clouds, to services, to social and communication networks. In the era of big data and connected devices of all varieties, analytics and machine learning have found ways to improve reliability, configuration, performance, fault and security management. In particular, we see a growing trend towards using machine learning, artificial intelligence and data analytics to improve operations and management of information technology services, systems and networks

A heuristic approach to network optimized mapping of a distributed resource discovery architecture

A heuristics was developed to optimally map a physical network to a VT structure that was used to provide a query forwarding mechanism for fuzzy information retrieval. Extensive simulations were carried out to test the performance of the new algorithm and considerable improvement over the unoptimized case was obtained. As such, the tests were repeated under fairly different conditions such as the varying query loads and even the worst case improvement figures showed that the optimal map leads to better results

Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning

Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning delivers a comprehensive overview of the impact of artificial intelligence (AI) and machine learning (ML) on service and network management. 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. Readers will also enjoy topics like: A thorough introduction to network and service management, machine learning, and artificial intelligence An exploration of artificial intelligence and machine learning for management models, including autonomic management, policy-based management, intent based ­management, and network virtualization-based management Discussions of AI and ML for architectures and frameworks, including cloud ­systems, software defined networks, 5G and 6G networks, and Edge/Fog networks An examination of AI and ML for service management, including the automatic ­generation of workload profiles using unsupervised learning Perfect for information and communications technology educators, Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning will also earn a place in the libraries of engineers and professionals who seek a structured reference on how the emergence of artificial intelligence and machine learning techniques is affecting service and network management

Summarizing Web Sites Automatically

Abstract. This research is directed towards automating the Web Site summarization task. To achieve this objective, an approach, which applies machine learning and natural language processing techniques, is employed. The automatically generated summaries are compared to manually constructed summaries from DMOZ Open Directory Project. The comparison is performed via a formal evaluation process involving human subjects. Statistical evaluation of the results demonstrates that the automatically generated summaries are as informative as human authored DMOZ summaries and significantly more informative than home page browsing or time limited site browsing.

Mirror Site Organization On Packet Switched Networks Using A Social

An approach making use of social insect metaphor and potential function clustering is employed to identify the connectivity pattern between clients and servers in order to ease the selection of mirror sites for application servers on computer networks