Guest editorial—special issue on service modeling and design for the future Internet

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IEEE Access special section editorial: Artificial intelligence enabled networking

With today’s computer networks becoming increasingly dynamic, heterogeneous, and complex, there is great interest in deploying artificial intelligence (AI) based techniques for optimization and management of computer networks. AI techniques—that subsume multidisciplinary techniques from machine learning, optimization theory, game theory, control theory, and meta-heuristics—have long been applied to optimize computer networks in many diverse settings. Such an approach is gaining increased traction with the emergence of novel networking paradigms that promise to simplify network management (e.g., cloud computing, network functions virtualization, and software-defined networking) and provide intelligent services (e.g., future 5G mobile networks). Looking ahead, greater integration of AI into networking architectures can help develop a future vision of cognitive networks that will show network-wide intelligent behavior to solve problems of network heterogeneity, performance, and quality of service (QoS)

Introduction: Advances in E-Business Engineering

(First Paragraph) E-business is one of the most exciting and challenging research areas. Today, not only large companies, but also medium or small-sized companies are learning that e-business is a required component of doing business. E-business has rapidly evolved in the last decade and this trend will continue. In this rapid process, a variety of e-business engineering methods and techniques have been developed. There are many research issues needed to be addressed. As a result, there is a growing demand for insights into challenges, issues, and solutions related to the design, implementation, and management of e-business systems

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

Ad Hoc Networking for Pervasive Systems

The hardware and software progresses of the last ten years provided the basic elements (wearable computers, several wireless-network technologies, devices for sensing and remote control, etc.) for the realization of pervasive computing and communication systems. In these systems the environment is saturated with computing and communication capabilities, completely integrated with the surrounding environment, aimed at helping the users in the everyday life. In a pervasive computing environment, the infrastructure-based wireless communication model is often not adequate: it takes time to set up the infrastructure network, while the costs associated with installing infrastructure can be quite high. These costs and delays may not be acceptable for dynamic environments where people and/or vehicles need to be temporarily interconnected in areas without a pre-existing communication infrastructure (e.g., inter-vehicular and disaster networks), or where the infrastructure cost is not justified (e.g., in-building networks, specific residential communities networks, etc.). In these cases, infrastructure-less or ad hoc networks provide a more efficient solution

Internet scalability: properties and evolution

Copyright © 2008 IEEEMatthew Roughan; Steve Uhlig; Walter Willinge

Editorial: Special Issue on Recent Advances in Computer and Communication Networks Technology

Dramatic improvements in networking technologies over the past couple of decades have yielded substantial increase in computer and communication capabilities. A number of new networking technologies such as middleware, wireless mesh networks anWiMAX, global IPv6, new generation multimedia, and modern network security started taking off. To date, some of these development efforts have mainly focused on protocol standardization, product development, and network operations besides being research targets. We believe that the accumulated experience in new networking practices now provide interesting research opportunities, not only for the broader network research community, but also for those who have been involved in these advancement developments