Over the last few years, the analysis and modeling of networks as well as the analysis and modeling of networked dynamical systems, has attracted considerable interdisciplinary interest, especially using the complex systems theory. These efforts are driven by the fact that systems, as diverse as genetic networks or the Internet can be effectively described as complex networks. Contrary, despite the unprecedented evolution of technology, basic issues and fundamental principles related to the structural and evolutionary properties of communication networks still remain largely unaddressed. The situation is even more complicated when we attempt to model the mobile communication networks and especially the 5th generation (5G) and eventually the forthcoming 6th generation (6G). In this work, we attempt to review basic models of complex networks from a communication networks perspective, focusing on their structural and evolutionary properties. Based on this review we aim to reveal the models of complex networks, that may apply when modeling the 5G and 6G mobile communication networks. Furthermore, we expect to encourage the collaboration between complex systems and networking theorists toward meeting the challenging demands of 5G networks and beyond. INDEX TERMS Complex systems, complex networks, networked complex system, 5G, 6G, wireless communications, wireless networks, mobile communication networks, modeling.

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Planning and deploying a functional large scale Wireless Sensor Network (WSN) or a Network of Internet of Things (IoTs) is a challenging task, especially in complex urban environments. A main network design bottleneck is the existence and/or correct usage of appropriate cross layer simulators that can generate realistic results for the scenario of interest. Existing network simulators tend to overlook the complexity of the physical radio propagation layer and consequently do not realistically simulate the main radio propagation conditions that take place in urban or suburban environments, thus passing inaccurate results between Open Systems Interconnection (OSI) layers. This work demonstrates through simulations and measurements that, by correctly passing physical information to higher layers, the overall simulation process produces more accurate results at the network layer. It is demonstrated that the resulting simulation methodology can be utilized to accomplish realistic wireless planning and performance analysis of the deployed nodes, with results that are very close to those of real test-beds, or actual WSN deployments.

Congestion control and avoidance in Wireless Sensor Networks (WSNs) is a subject that has attracted a lot of research attention in the last decade. Besides rate and resource control, the utilization of mobile nodes has also been suggested as a way to control congestion. In this work, we present a Mobile Congestion Control (MobileCC) algorithm with two variations, to assist existing congestion control algorithms in facing congestion in WSNs. The first variation employs mobile nodes that create locallysignificant alternative paths leading to the sink. The second variation employs mobile nodes that create completely individual (disjoint) paths to the sink. Simulation results show that both variations can significantly contribute to the alleviation of congestion in WSNs.