In this work, a neural-based approach for inverse problems in the field of electromagnetic devices design is presented. A multilayer perceptron neural network is first trained to solve the analysis problem of the studied system. As a design problem can be formulated as an inverse problem, i.e., starting from the design requirements the optimal values of the design parameters have to be obtained, the input of the neural network will correspond to the design parameters while the output is the objective function of the optimization problem. In this work, a procedure is presented which performs the inversion of the trained neural network when the design requirements are assigned to the output

Abstract-The paper describes an optimization model which aims at minimizing the maximum link utilization of IP telecommunication networks under the joint use of the traditional IGP protocols and the more sophisticated MPLS-TE technology. The survivability of the network is taken into account in the optimization process implementing the path restoration scheme. This scheme benefits of the Fast Re-Route (FRR) capability allowing service providers to offer high availability and high revenue SLAs (Service Level Agreements). The hybrid IGP/MPLS approach relies on the formulation of an innovative Linear Programming mathematical model that, while optimizing the network utilization, provides optimal user performance, efficient use of network resources, and 100% survivability in case of single link failure. The possibility of performing an optimal exploitation of the network resources throughout the joint use of the IGP and MPLS protocols provides a flexible tool for the ISP (Internet Service Provider) networks traffic engineers.The efficiency of the proposed approach is validated by a wide experimentation performed on synthetic and real networks. The obtained results show that a limited number of LSP tunnels have to be set up in order to significantly reduce the congestion level of the network while at the same time guaranteeing the survivability of the network.

This paper aims to highlight the importance of end-to-end service quality for cloud services, with a focus on telecom carrier-grade services. In multi-tenant distributed and virtualized cloud infrastructures, the enhanced level of resource sharing raises issues in terms of performance stability and reliability of cloud services, threatening the possibility to offer precise service levels in end-to-end scenarios.

Contemporary Cloud Computing infrastructures are being challenged by an increasing demand for evolved cloud services characterised by heterogeneous performance requirements including real-time, data-intensive and highly dynamic workloads. The classical way to deal with dynamicity is to scale computing and network resources horizontally. However, these techniques must be coupled effectively with advanced routing and switching in a multi-path environment, mixed with a high degree of flexibility to support dynamic adaptation and live-migration of virtual machines (VMs). We propose a management strategy to jointly optimise computing and networking resources in cloud infrastructures, where Software Defined Networking (SDN) plays a key enabling role.

No abstract