Abstract
Complex systems are fully described by the connectedness of their elements studying how these develop a collective behavior, interacting with each other following their inner features, and the structure and dynamics of the entire system. The forthcoming 6G will attempt to rewrite the communication networks’ perspective, focusing on a radical revolution in the way entities and technologies are conceived, integrated and used. This will lead to innovative approaches with the aim of providing new directions to deal with future network challenges posed by the upcoming 6G, thus the complex systems could become an enabling set of tools and methods to design a self-organized, resilient and cognitive network, suitable for many application fields, such as digital health or smart city living scenarios. Here, we propose a complex profiling approach of heterogeneous nodes belonging to the network with the goal of including the multiplex social network as a mathematical representation that enables us to consider multiple types of interactions, the collective dynamics of diffusion and competition, through social contagion and evolutionary game theory, and the mesoscale organization in communities to drive learning and cognition. Through a framework, we detail the step by step modeling approach and show and discuss our findings, applying it to a real dataset, by demonstrating how the proposed model allows us to detect deeply complex knowable roles of nodes.
Highlights
The ongoing process of telecommunications evolution towards 6th generation (6G), along with the growing number of mobile users and the demand of bandwidth-intensive services and high data-rate applications, are creating a large volume of traffic, making a complex dare which needs to be addressed with innovative approaches [1,2]
We propose a node profiling process based on a complex network approach, which embeds, step by step, the knowledge extracted from the introduction of the multiplex dimension, the analysis of the dynamics of collective phenomena as diffusion and competition, applying the epidemics spreading modeling and the evolutionary game theory, from the mesoscale hierarchical organization of the network in communities
The scheme put in evidence the introduction of the multiplex dimension to detect a profiling in structural terms, enabling the analysis of the diffusion and the competition dynamics with the aim at analyzing the collective contribution to the characterization of nodes
Summary
The ongoing process of telecommunications evolution towards 6G, along with the growing number of mobile users and the demand of bandwidth-intensive services and high data-rate applications, are creating a large volume of traffic, making a complex dare which needs to be addressed with innovative approaches [1,2]. The worldwide research activity is focused on defining the next-generation 6G systems in order to take into consideration a confluence of trends as densification, higher rate, massive antenna and emerging trends that include innovations in terms of services and devices, complexity and artificial intelligence (AI), computing and sensing [3]. Taking into consideration the forthcoming 6th generation (6G) communication networks, it will address the constraints and the performance requirements of the applications and innovative services which need highly increasing resources, introducing new approaches and technologies as well as revolutionary network features [2,4]. Future Internet 2021, 13, 135 of nodes It can be achieved through the introduction of a complex systems approach
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
