- Prof. Dr. Giovanni Pau
- Kore University of Enna, Enna, Italy.
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Special Issue Introduction
The future wireless communications, involving the Internet of Things (IoT) mobile devices and associated sensors/actuators, are remodeling to networks where the radio environment converts as manageable, programmable, and intelligent. These networks become reconfigurable and hold knowledge, training, rationalizing, and decision-making capacities; various network sections might be developed and managed through artificial intelligence or software-defined network criteria. Reconfigurable wireless networks intend to facilitate “intelligence” within the present system to recognize and evaluate the available resources, adapt to the dynamic wireless conditions, and reconfigure the running method to maximize the performance. Energy Efficiency is a crucial problem in these environments. Consequently, the necessity to enhance energy efficiency becomes self-evident as the number of power-consuming functionalities demanded from these devices increases. The current wireless communication architectures and technologies may not address most of these concerns. Hence, new procedures are expected, aiming at which spectrum and energy resources can be efficiently managed and effectively handled.
This Special Issue solicits the submission of high-quality and unpublished papers that strive to resolve open technical issues typical of energy-efficient management of mobile computing in IoT environments. The primary purpose is to combine innovative methods efficiently, concentrating on the performance evaluation and comparing existing solutions. Both theoretical and experimental studies are encouraged. Furthermore, high-quality reviews and survey papers are also welcomed.
Topics of interest include, but are not limited to:
● energy-efficient techniques for reconfigurable wireless communication and networks;
● energy-aware resource management;
● energy-efficient hardware architectures for mobile devices;
● energy-efficient mobile computing for artificial intelligence applications;
● machine-learning algorithms for spectrum and energy-efficient transmissions in reconfigurable wireless situations;
● energy-friendly software and applications maintaining sustainability and the adoption of renewable energy sources.
Submission Deadline31 Dec 2021