IEEE Transactions on Network Science and Engineering Call for Papers

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        #Announcement(IoTStack) #Invitation #Pitch [ via IoTGroup ]
        #Organizer : IEEE #DueDateTime : 1 October 2020 #StartDateTime : 1 Jan 2021 #EndDateTime : 1 June 2021 #IsTraining : Machine Learning Enabled Reconfigurable Wireless Networks


        Reconfigurable Wireless Networks (RWNs) are composed of a set of communicating nodes such that each one executes reconfigurable software tasks to control local networking nodes. RWNs can include reconfiguration of software, hardware and protocols. Software reconfiguration allows the inclusion, exclusion or updation of tasks, hardware reconfiguration allows the activation and deactivation of nodes, and protocol reconfiguration allows the modification of routing protocols between nodes. In recent years, we have witnessed rapid proliferation of the following: (1) development of fully programmable, protocol-independent data planes and languages for programming and (2) the emergence of new platforms, tools, and algorithms for Artificial Intelligence (AI) and Machine Learning (ML). Wireless networks possess perception, learning, reasoning, and decision-making capabilities, which make AI/ML an indispensable tool to optimize and to efficiently operate it. 5G wireless networks are rapidly evolving towards an intelligent and software-defined design paradigm, where different parts of the network might be configured and controlled via user-centric AI. The future of wireless networks, giving rise to intelligent processing, which aims at enabling the system to perceive and assess the available resources, to autonomously learn to adapt to the perceived wireless environment, and to reconfigure its operating mode to maximize the utility of the available resources. Perception capability and reconfigurability are essential features of cognitive technology while modern ML techniques project effectiveness in system adaptation. Further, due to massive data explosion currently there is a problem of huge spectrum scarcity, which can be solved with the help of reconfigurable wireless networks where nodes are capable of changing their frequencies. Therefore, there is a requirement of AI and ML assisted algorithms for spectrum and energy efficient communication, wireless security, MAC issues etc. The Special issue will give emphasis on novel techniques for building reconfigurable wireless networks and coupling the technological advances in wireless networking with scientific innovations in AI and ML.

        This SI seeks contributions from experts in areas such as network programming, formal methods, control theory, distributed systems, machine learning, data science, data structures and algorithms, and optimization in the view of reconfigurable wireless networks as well as improving the performance of AI and ML solutions.


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