A novel complex system approach for the determination of renewable energy sources impact on electricity infrastructures

The increasing environmental awareness, associated with the increasing demand and price of fossil fuels, is leading to the implementation of novel energy models based on renewable energy sources (RES) and sustainable mobility. However, the actual physical and economic models on which power system management rules are based on, are not able to properly manage the high amount of unwanted power fluctuations introduced by RES power generation. For such reason, major issues has been pointed out in term of energy security and access, inspiring changes in methods and paradigms associated to energy supply management. Moreover, the transaction towards an emission free mobility must be based on the interaction between RES generation and Electric Vehicles (EV) mobility, pointing out the need of a new approach able to combine mobility and energy supply infrastructures. In order to describe and model power systems with an high amount of RES generation, is important to indicate that such systems are made by a great number of microscopical interacting elements which behave in a stochastic way. For this reason, these systems can not easily be described in a deterministic way, but must be described by a statistical representation of the system observables. In this thesis, a novel approach based on statistical mechanics methods is presented, able to model the impact of such sources over the system. By using such approach, has been possible to evaluate the possible impact of such sources in terms of power system stability and sustainable mobility

Matching Theory for Future Wireless Networks: Fundamentals and Applications

The emergence of novel wireless networking paradigms such as small cell and cognitive radio networks has forever transformed the way in which wireless systems are operated. In particular, the need for self-organizing solutions to manage the scarce spectral resources has become a prevalent theme in many emerging wireless systems. In this paper, the first comprehensive tutorial on the use of matching theory, a Nobelprize winning framework, for resource management in wireless networks is developed. To cater for the unique features of emerging wireless networks, a novel, wireless-oriented classification of matching theory is proposed. Then, the key solution concepts and algorithmic implementations of this framework are exposed. Then, the developed concepts are applied in three important wireless networking areas in order to demonstrate the usefulness of this analytical tool. Results show how matching theory can effectively improve the performance of resource allocation in all three applications discussed

A framework for the joint placement of edge service infrastructure and User Plane Functions for 5G

Achieving less than 1 ms end-to-end communication latency, required for certain 5G services and use cases, is imposing severe technical challenges for the deployment of next-generation networks. To achieve such an ambitious goal, the service infrastructure and User Plane Function (UPF) placement at the network edge, is mandatory. However, this solution implies a substantial increase in deployment and operational costs. To cost-effectively solve this joint placement problem, this paper introduces a framework to jointly address the placement of edge nodes (ENs) and UPFs. Our framework proposal relies on Integer Linear Programming (ILP) and heuristic solutions. The main objective is to determine the ENs and UPFs’ optimal number and locations to minimize overall costs while satisfying the service requirements. To this aim, several parameters and factors are considered, such as capacity, latency, costs and site restrictions. The proposed solutions are evaluated based on different metrics and the obtained results showcase over 20% cost savings for the service infrastructure deployment. Moreover, the gap between the UPF placement heuristic and the optimal solution is equal to only one UPF in the worst cases, and a computation time reduction of over 35% is achieved in all the use cases studied.Postprint (author's final draft

Efficient cellular load balancing through mobility-enriched vehicular communications

Supporting effective load balancing is paramount for increasing network utilization efficiency and improving the perceivable user experience in emerging and future cellular networks. At the same time, it is becoming increasingly alarming that current communication practices lead to excessive energy wastes both at the infrastructure side and at the terminals. To address both these issues, this paper discusses an innovative communication approach enabled by the implementation of device-to-device (d2d) communication over cellular networks. The technique capitalizes on the delay tolerance of a significant portion of Internet applications and the inherent mobility of the nodes to achieve significant performance gains. For delay-tolerant messages, a mobile node can postpone message transmission—in a store–carry and forward manner—for a later time to allow the terminal to achieve communication over a shorter range or to postpone communication to when the terminal enters a cooler cell, before engaging in communication. Based on this framework, a theoretical model is introduced to study the generalized multihop d2d forwarding scheme where mobile nodes are allowed to buffer messages and carry them while in transit. Thus, a multiobjective optimization problem is introduced where both the communication cost and the varying load levels of multiple cells are to be minimized. We show that the mathematical programming model that arises can be efficiently solved in time. Furthermore, extensive numerical investigations reveal that the proposed scheme is an effective approach for both energy-efficient communication and offering significant gains in terms of load balancing in multicell topologies