Search

Mission Critical Services (MCS) are associated with public safety networks and their support has been progressively introduced in LTE/5G standards. MCS are composed by distinct functions that are required for voice and critical data communications, along with strict security requirements. Service Function Chaining (SFC) allows the delivery of end-to-end services and considers the order of flows (i.e. functions that must be applied before others) and the components on which such functions can be performed (i.e. at cloud or edge nodes). This paper proposes the design of SFC policies to chain Service Functions of MCS, considering the roles of vehicles in wildfire combating scenarios. The evaluated SFC policies consider security functions at edge nodes with distinct computational platforms. The achieved results demonstrate that the SFC policies need to be carefully designed to reduce disruption of services in MCS scenarios.

The scope of this work is to design an Optical Transport Network unifying the physical topology design, virtual topology design and routing and wavelength assignment. The objective is to calculate the global optimal solution, instead of partial solutions. The Mathematical Formulation defined here is based on the Quadratic Assignment Problem, and it could be used for networks with either grooming feature, or not, by allocating sub-wavelength demands, represented by SDH/SONET payload units. Two heuristics to solve this problem are proposed, the EXATO Heuristic, and a GRASP Heuristic. The results showed that the approach was successful to design a low cost optical network.

This paper presents the OOTN - Ontology for Optical Transport Networks: a computational ontology proposal for optical transport networks based on the ITU-T G.805 and G.872 recommendations. It shows the most relevant issues found during the modeling process and presents a case study where the classical concepts of VTD and RWA applications have been mapped to OOTN.

Digital change detection methods have been broadly divided into either pre-classification spectral change detection or post-classification change detection. Since all spectral change detection methods are based on pixel-wise plus operations or scene-wise plus pixel-wise operations, accuracy in image registration and scene-to-scene radiometric normalization is more critical for these methods than for other methods. A wide range of algorithms has been developed to adjust linear models. This paper proposes an automated radiometric normalization process that uses an artificial neural network to adjust a non-linear mapping to minimize the effects of the influences of radiometric differences on image interpretation and classification.

This work investigates the potential of an unsupervised network classifier, the Centroid Neural Network (CNN), for land cover change detection in remotely sensed images. Experiments carried out to evaluate the algorithm include change detection in both approaches: pre-classification and post-classification. Results confirm the effectiveness of this technique.

This paper presents a feedback method for the protection of switching devices used in the fast commutation of inductive circuits in switching power converters. The new protection approach is being studied aiming faster, lighter and more efficient circuits compared with the conventional clampers and snubbers, The circuits proposed in this paper can be easily integrated in the same chip of the power MOS device, using the new MOS power technologies.