Enabling Artificial Intelligence Analytics on The Edge

This thesis introduces a novel distributed model for handling in real-time, edge-based video analytics. The novelty of the model relies on decoupling and distributing the services into several decomposed functions, creating virtual function chains (V F C model). The model considers both computational and communication constraints. Theoretical, simulation and experimental results have shown that the V F C model can enable the support of heavy-load services to an edge environment while improving the footprint of the service compared to state-of-the art frameworks. In detail, results on the V F C model have shown that it can reduce the total edge cost, compared with a monolithic and a simple frame distribution models. For experimenting on a real-case scenario, a testbed edge environment has been developed, where the aforementioned models, as well as a general distribution framework (Apache Spark ©), have been deployed. A cloud service has also been considered. Experiments have shown that V F C can outperform all alternative approaches, by reducing operational cost and improving the QoS. Finally, a migration model, a caching model and a QoS monitoring service based on Long-Term-Short-Term models are introduced

On the existence of minimal models for log canonical pairs

We show that minimal models of log canonical pairs exist, assuming the existence of minimal models of smooth varieties.Comment: v3: minor changes; title changed; to appear in Publ. Res. Inst. Math. Sc

Video surveillance systems-current status and future trends

Within this survey an attempt is made to document the present status of video surveillance systems. The main components of a surveillance system are presented and studied thoroughly. Algorithms for image enhancement, object detection, object tracking, object recognition and item re-identification are presented. The most common modalities utilized by surveillance systems are discussed, putting emphasis on video, in terms of available resolutions and new imaging approaches, like High Dynamic Range video. The most important features and analytics are presented, along with the most common approaches for image / video quality enhancement. Distributed computational infrastructures are discussed (Cloud, Fog and Edge Computing), describing the advantages and disadvantages of each approach. The most important deep learning algorithms are presented, along with the smart analytics that they utilize. Augmented reality and the role it can play to a surveillance system is reported, just before discussing the challenges and the future trends of surveillance

A Generic Framework for Deploying Video Analytic Services on the Edge

This paper introduces a novel distributed model for handling in real-time, edge-based Artificial Intelligence analytics, such as the ones required for smart video surveillance. The novelty of the model relies on decoupling and distributing the services into several decomposed functions which are linked together, creating virtual function chains (VFC model). The model considers both computational and communication constraints. Theoretical, simulation and experimental results have shown that the VFC model can enable the support of heavy-load services to an edge environment while improving the footprint of the service compared to state-of-the art frameworks. In detail, results on the VFC model have shown that it can reduce the total edge cost, compared with a Monolithic and a Simple Frame Distribution models. For experimenting on a real-case scenario, a testbed edge environment has been developed, where the aforementioned models, as well as a general distribution framework (Spark ©) and an edge-deployement framework (Kubernetes©), have been deployed. A cloud service has also been considered. Experiments have shown that VFC can outperform all alternative approaches, by reducing operational cost and improving the QoS. Finally, a caching and a QoS monitoring service based on Long-Term-Short-Term models are introduced and evaluated

Enabling Real-Time AI Edge Video Analytics

This paper introduces a novel distributed AI model for managing in real-time, edge based intelligent analytics, such as the ones required for smart video surveillance. The novelty relies on distributing the applications in several decomposed functions which are linked together, creating virtual chain func- tions, where both computational and communication limitations are considered. Both theoretical analysis and simulation analysis in a real-case scenario have shown that the proposed model can enable real-time surveillance analytics on a low-cost edge network. Finally, a caching mechanism is proposed and evaluated, reducing further the operational costs of the edge network

On Minimal Models and the Termination of Flips for Generalized Pairs

Das Ziel dieser Arbeit ist die Untersuchung zweier offener Probleme in der höherdimensionalen birationalen Geometrie, nämlich der Vermutung zur Existenz von minimalen Modellen und der Vermutung zur Terminierung von Flips. Wir arbeiten haupts ächlich mit verallgemeinerten Paaren und untersuchen demzufolge die entsprechenden Versionen der oben genannten Vermutungen des Minimal-Modell-Programms in diesem breiteren Rahmen. Der erste Teil der Dissertation widmet sich daher der Entwicklung der grundlegenden Aspekte der Theorie der verallgemeinerten Paare. Um die Vermutung zur Existenz von minimalen Modellen anzugehen, betrachten wir zunächst bestimmte Zariski-Zerlegungen in höheren Dimensionen, die sogennanten schwachen Zariski-Zerlegungen und NQC Nakayama-Zariski-Zerlegungen. Anschließend beweisen wir, dass die Existenz von minimalen Modellen für log-kanonische verallgemeinerte Paare aus der Existenz von minimalen Modellen für glatte Varietäten folgt, und ferner, dass die Existenz von minimalen Modellen im Wesentlichen zur Existenz dieser Zariski-Zerlegungen äquivalent ist. Der letzte Teil dieser Arbeit befasst sich mit der Vermutung zur Terminierung von Flips. Wir zeigen zuerst die Spezielle Terminierung für log-kanonische verallgemeinerte Paare. Danach beweisen wir die Terminierung von Flips für log-kanonische verallgemeinerte Paare der Dimension 3 sowie für pseudo-effektive log-kanonische verallgemeinerte Paare der Dimension 4.The aim of this thesis is the investigation of two open problems in higher-dimensional birational geometry, namely the existence of minimal models conjecture and the termination of ips conjecture. We mainly work with generalized pairs and we therefore study the corresponding versions of the aforementioned conjectures of the Minimal Model Program in this wider context. Consequently, the first part of the thesis is devoted to the development of the basic aspects of the theory of generalized pairs. In order to deal with the existence of minimal models conjecture, we first study particular Zariski decompositions in higher dimensions, the so-called weak Zariski decompositions and NQC Nakayama-Zariski decompositions. Subsequently, we prove that the existence of minimal models for log canonical generalized pairs follows from the existence of minimal models for smooth varieties, and we also demonstrate that the existence of minimal models is essentially equivalent to the existence of those Zariski decompositions. The last part of this thesis focuses on the termination of ips conjecture. First, we show the special termination for log canonical generalized pairs. Afterwards, we establish the termination of ips for log canonical generalized pairs of dimension 3 as well as for pseudo-effective log canonical generalized pairs of dimension 4

Comparison and uniruledness of asymptotic base loci

We prove that the asymptotic base loci of a klt generalized pair with big canonical class are uniruled. We also show that the non-nef locus and the diminished base locus of the adjoint divisor of a log canonical generalized pair coincide. As applications, we study the uniruledness of the asymptotic base loci associated with pseudo-effective divisors on generalized log Calabi-Yau type varieties

Remarks on the existence of minimal models of log canonical generalized pairs

Given an NQC log canonical generalized pair $(X,B+M)$, we prove that we may run a $(K_X+B+M)$-MMP with scaling of an ample divisor which terminates, provided that $(X,B+M)$ has a minimal model in a weaker sense or that $K_X+B+M$ is not pseudo-effective. Consequently, we establish the existence of Mori fibre spaces for non-pseudo-effective NQC log canonical generalized pairs of arbitrary dimension. In addition, we obtain several results concerning the existence of minimal models for pseudo-effective NQC log canonical generalized pairs. For example, we show that any such generalized pair whose boundary contains an ample divisor has a good minimal model. Finally, we reduce the problem of the existence of minimal models of NQC log canonical generalized pairs to the problem of the existence of minimal models of smooth varieties

On the termination of flips for log canonical generalized pairs

We prove the termination of flips for 4-dimensional pseudo-effective NQC log canonical generalized pairs. As main ingredients, we verify the termination of flips for 3-dimensional NQC log canonical generalized pairs, and show that the termination of flips for pseudo-effective NQC log canonical generalized pairs which admit NQC weak Zariski decompositions follows from the termination of flips in lower dimensions