Current networks are designed for peak loads leading to low utilization of power resources.In order to solve this problem, a heuristic energy-saving virtual network embedding algorithm based on the Katz centrality (Katz-VNE) is proposed.For solving an energy-saving virtual network embedding problem, we introduce the Katz centrality to represent the
The 2030 Agenda constitutes a plan of action in favor of the people, the planet and the prosperity approved by the United Nations (UN) that has among its purposes to eliminate poverty and inequality, and strengthen peace in the world within a broad Coolant Fittings concept of freedom, contributing to implement the human rights of all the inhabitant
This study proposes the use of a Quadruple Deep Q-Network (QDQN) for optimizing the energy management strategy of Plug-in Hybrid Electric Analgesic Balms Vehicles (PHEVs).The aim of this research is to improve energy utilization efficiency by employing reinforcement learning techniques, with a focus on reducing energy consumption while maintaining