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)

Editorial for Special Issue on “Electronic Systems and Energy Harvesting Methods for Automation, Mechatronics and Automotive”

none3noElectronic apparatus have become essential components of civil and industrial systems, including the automotive, home and building automation, Industrial IoT (Internet of Things) and control applications, and playing an essential role in improving security, efficiency, manageability, and rapid feedback [1–3]. Indeed, the increasing demands of electronic systems have led to innovations and findings in electronic networks for automotive and automation plants, replacing efficiently and securely mechanical and hydraulic sections [4]. Also, the researchers have focused their attention on meeting the increasing power demand of vehicles equipment, developing 42-V automotive systems. Moreover, smart buildings and homes represent a very actual research topic in the scientific community, aimed to improve energy conservation and the liveability of everyday life environments, thanks to IoT solutions [5]. In fact, smart homes and buildings comprise innovative solutions enabling communication between users and the infrastructure, as well as performing advanced monitoring tasks, like surveillance, light and water management, HVAC (heating, ventilation and air conditioning) system management, smart energy monitoring and elderly care. IoT technology employs sensors to detect the environmental temperature for the HVAC system, water and energy consumption, and health monitoring and decision-making systems to assist elderly people and detect fires [6,7]. The scientific community is concentrating their efforts to design innovative infrastructures, management models as well as operating scenarios to make production activities simpler and more efficient [8]. In this field, IoT is one of the key elements triggering this revolution, enabling communications between machines (M2M), thus creating a manufacturing environment human-free. The combination of M2M, IoT and CPS (cyber physical systems) makes the manufacturing systems more robust, reliable and efficient. Besides, cloud computing constitutes a powerful tool, promising to solve several difficult issues with previous productive architectures. For instance, in [9], a novel architecture integrating cloud computing, IoT, and smart devices, was presented. The model uses modern manufacturing technologies, allowing highly configurable, flexible manufacturing processes involving human and robotic participants. This Special Issue aimed to cover a wide range of disciplines and application fields, collecting innovative studies on advanced sensing and energy harvesting technologies and applications in automotive, automation and mechatronics fields. The introduced innovations could mitigate the impact of human activities on the environment and revolutionize the production process by employing eco-sustainable production models, preventing climate change and natural resources waste. A total of 5 papers have been published in this special issue; the paper covers a wide range of topics but is deemed relevant to the topics covered by the special issues. The authors are from geographically distributed countries such as Italy, Mexico, Spain, and China. This reflects the great impact of the proposed topic and the effective organization of the guest editorial team of this special issue.openPaolo Visconti, Nicola Ivan Giannoccaro, Roberto de FazioVisconti, Paolo; Giannoccaro, NICOLA IVAN; DE FAZIO, Robert

Guest Editorial: Design and Analysis of Communication Interfaces for Industry 4.0

This special issue (SI) aims to present recent advances in the design and analysis of communication interfaces for Industry 4.0. The Industry 4.0 paradigm aims to integrate advanced manufacturing techniques with Industrial Internet-of-Things (IIoT) to create an agile digital manufacturing ecosystem. The main goal is to instrument production processes by embedding sensors, actuators and other control devices which autonomously communicate with each other throughout the value-chain [1]

HPS-HDS:High Performance Scheduling for Heterogeneous Distributed Systems

Heterogeneous Distributed Systems (HDS) are often characterized by a variety of resources that may or may not be coupled with specific platforms or environments. Such type of systems are Cluster Computing, Grid Computing, Peer-to-Peer Computing, Cloud Computing and Ubiquitous Computing all involving elements of heterogeneity, having a large variety of tools and software to manage them. As computing and data storage needs grow exponentially in HDS, increasing the size of data centers brings important diseconomies of scale. In this context, major solutions for scalability, mobility, reliability, fault tolerance and security are required to achieve high performance. More, HDS are highly dynamic in its structure, because the user requests must be respected as an agreement rule (SLA) and ensure QoS, so new algorithm for events and tasks scheduling and new methods for resource management should be designed to increase the performance of such systems. In this special issues, the accepted papers address the advance on scheduling algorithms, energy-aware models, self-organizing resource management, data-aware service allocation, Big Data management and processing, performance analysis and optimization

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

Editorial: Security and privacy in Internet of Things

J. M. de Fuentes, L. Gonzalez-Manzano and P. Peris-Lopez have been partially supported by MINECO grants TIN2013-46469-R and TIN2016-79095-C2-2-R, and CAM grant S2013/ICE-3095