New Challenges of Networking Technologies and IoT

Dear Colleagues,

Traditionally, mobile data have referred to data from phones, tablets, access points, connected cars, etc. However, NarrowBand IoT (NB-IoT) presents a novelty. NB-IoT allows for low cost, low energy connections of mobile devices to an existing wireless infrastructure. You can take your Apple Watch for a run and maintain full connectivity while leaving your phone at home. In smart cities, traffic lights can react intelligently to the presence of connected cars in real time, or waste bins can even tell you when they are full without the need for a human to check. There are already devices on the market using similar technology, such as the Bigbelly solar compactor, Bluesmart suitcases, or the Whistle activity tracker for dogs. This enables a low-cost ecosystem of independently connected devices. As this technology matures, we will see a whole range of devices becoming connected, from smartwatches to cameras, activity trackers, and more. The richness of IoT that has become commonplace in the home will soon be just as ubiquitous in the mobile world as well.

In addition to a more robust network capacity and an increasing number of connected devices, changing how these systems are maintained will have a dramatic effect on our mobile experience as well. Future network users will have an increasing number of connected devices, which means that there will be even greater amounts of data from which to derive preferences and likely actions. Combine that with the capability to deliver enormous amounts of information with no perceptible delay and the user will experience nearly instantaneous responsiveness from their experiences.

As Artificial Intelligence, including machine learning and deep learning, become more prevalent in network operations, this technology will augment the capabilities of human engineers and help them to perform their jobs better and on a larger scale. Artificial Intelligence can observe how engineers identify and solve problems and can learn how to spot potential service issues before they develop. Artificial Intelligence can also alert engineers to impending problems with a range of viable solutions to select from.

Topics of interest for submission include but are not limited to the following:

• Internetworking
• Next-generation networks;
• Networking technologies;
• Network architectures;
• High-speed networks;
• Routing, switching, and addressing techniques;
• State-of-the-art of network operations and management;
• Network performance, QoS, and resource management;
• Peer-to-peer and overlay networks.
• Wireless Networks
• Ad hoc and sensor networks;
• WiFi and LiFi network technologies;
• Ubiquitous networks;
• Mobile networks and wireless networks;
• Recent trends in WiMedia and multimedia networks.
• Reconfigurable Networks
• Heterogeneous networks;
• Self-organizing/reconfigurable networks and networked systems;
• Interconnection network on chip (NoC);
• Software-defined networks (SDNs);
• Virtualization and network traffic balancer;
• Data center design;
• Data center networks.
• Ultrahigh-Speed Networks
• Optical communications and networks;
• Photonic networks;
• Satellite and space communications;
• ICT and intelligent transportation systems;
• Internet of Things (IoT).
• Intelligent and Advanced Systems
• Next-generation Internet;
• Next-generation web architectures;
• Parallel and distributed computing networks;
• Mobile/wireless computing;
• Intelligent computing systems;
• Cloud computing and Big Data analytics;
• Real-time and embedded systems;
• Modelling and simulation;
• Network security;
• Wireless network attacks;
• Cloud security;
• Cloud document integrity and privacy.
• Intelligent Data Sensing
• Intelligent data sensing and collection;
• Intelligent data processing and mining;
• Scalable data and resource management;
• Mobile computing-based intelligent sensing and data collection, processing, mining, and communication of data;
• Complexity of mobile computing of intelligent sensing and data collection and communication;
• Mobile-computing-based intelligent sensing and data collection and communication in the cloud;
• Large-scale data analysis in mobile computing-based intelligent sensing and data collection and communication;
• Knowledge and service discovery in mobile computing-based sensing and data collection and communication with intelligence;
• Business and societal applications of intelligent sensing and data collection and communication in mobile computing;
• Big Data-based technologies and algorithms for data acquisition, processing, and mining;
• Security and privacy issues;
• IoT-based data sensing, processing, mining, and communication;
• Intelligent integration and exploration of biomedical and industrial data;
• Artificial Intelligence-driven analytics of data;
• Data acquisition techniques (RFID, sensors, etc.);
• Communication, networking, optimization, and performance measuring of trustworthy systems.
• Artificial Intelligence
• Machine learning;
• Deep learning;
• Smart cities;
• Data mining.
• New Network Protocols
• Named data networking (NDN);
• Recursive InterNetwork Architecture (RINA);
• Enhanced IP;
• Easy IP (EZIP).

Prof. Dr. Habib Hamam
Guest Editor

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• internetworking
• wireless networks
• reconfigurable networks
• ultrahigh-speed networks
• intelligent and advanced systems
• intelligent data sensing