Balancing the Migration of Virtual Network Functions with Replications in Data Centers

The Network Function Virtualization (NFV) paradigm is enabling flexibility, programmability and implementation of traditional network functions into generic hardware, in form of the so-called Virtual Network Functions (VNFs). Today, cloud service providers use Virtual Machines (VMs) for the instantiation of VNFs in the data center (DC) networks. To instantiate multiple VNFs in a typical scenario of Service Function Chains (SFCs), many important objectives need to be met simultaneously, such as server load balancing, energy efficiency and service execution time. The well-known \emph{VNF placement} problem requires solutions that often consider \emph{migration} of virtual machines (VMs) to meet this objectives. Ongoing efforts, for instance, are making a strong case for migrations to minimize energy consumption, while showing that attention needs to be paid to the Quality of Service (QoS) due to service interruptions caused by migrations. To balance the server allocation strategies and QoS, we propose using \emph{replications} of VNFs to reduce migrations in DC networks. We propose a Linear Programming (LP) model to study a trade-off between replications, which while beneficial to QoS require additional server resources, and migrations, which while beneficial to server load management can adversely impact the QoS. The results show that, for a given objective, the replications can reduce the number of migrations and can also enable a better server and data center network load balancing

The Interacting Multiple Models Algorithm with State-Dependent Value Assignment

The value of a state is a measure of its worth, so that, for example, waypoints have high value and regions inside of obstacles have very small value. We propose two methods of incorporating world information as state-dependent modifications to the interacting multiple models (IMM) algorithm, and then we use a game\u27s player-controlled trajectories as ground truths to compare the normal IMM algorithm to versions with our proposed modifications. The two methods involve modifying the model probabilities in the update step and modifying the transition probability matrix in the mixing step based on the assigned values of different target states. The state-dependent value assignment modifications are shown experimentally to perform better than the normal IMM algorithm in both estimating the target\u27s current state and predicting the target\u27s next state

The Interacting Multiple Models Algorithm with State-Dependent Value Assignment

The value of a state is a measure of its worth, so that, for example, waypoints have high value and regions inside of obstacles have very small value. We propose two methods of incorporating world information as state-dependent modifications to the interacting multiple models (IMM) algorithm, and then we use a game\u27s player-controlled trajectories as ground truths to compare the normal IMM algorithm to versions with our proposed modifications. The two methods involve modifying the model probabilities in the update step and modifying the transition probability matrix in the mixing step based on the assigned values of different target states. The state-dependent value assignment modifications are shown experimentally to perform better than the normal IMM algorithm in both estimating the target\u27s current state and predicting the target\u27s next state

Multi-Label Latent Spaces with Semi-Supervised Deep Generative Models

Expert labeling, tagging, and assessment are far more costly than the processes of collecting raw data. Generative modeling is a very powerful tool to tackle this real-world problem. It is shown here how these models can be used to allow for semi-supervised learning that performs very well in label-deficient conditions. The foundation for the work in this dissertation is built upon visualizing generative models\u27 latent spaces to gain deeper understanding of data, analyze faults, and propose solutions. A number of novel ideas and approaches are presented to improve single-label classification. This dissertation\u27s main focus is on extending semi-supervised Deep Generative Models for solving the multi-label problem by proposing unique mathematical and programming concepts and organization. In all naive mixtures, using multiple labels is detrimental and causes each label\u27s predictions to be worse than models that utilize only a single label. Examining latent spaces reveals that in many cases, large regions in the models generate meaningless results. Enforcing a priori independence is essential, and only when applied can multi-label models outperform the best single-label models. Finally, a novel learning technique called open-book learning is described that is capable of surpassing the state-of-the-art classification performance of generative models for multi-labeled, semi-supervised data sets

Detailed analysis of the lattice Boltzmann method on unstructured grids

The lattice Boltzmann method has become a standard for efficiently solving problems in fluid dynamics. While unstructured grids allow for a more efficient geometrical representation of complex boundaries, the lattice Boltzmann methods is often implemented using regular grids. Here we analyze two implementations of the lattice Boltzmann method on unstructured grids, the standard forward Euler method and the operator splitting method. We derive the evolution of the macroscopic variables by means of the Chapman-Enskog expansion, and we prove that it yields the Navier-Stokes equation and is first order accurate in terms of the temporal discretization and second order in terms of the spatial discretization. Relations between the kinetic viscosity and the integration time step are derived for both the Euler method and the operator splitting method. Finally we suggest an improved version of the bounce-back boundary condition. We test our implementations in both standard benchmark geometries and in the pore network of a real sample of a porous rock.Comment: 42 page

Significance of voiding urosonography in diagnosis of urinary tract infections and in congenital anomalies of kidney and urinary tract in pediatric patients

Introduction Vesicoureteral reflux (VUR) is defined as the retrograde influx of urine from the bladder to the ureters or to the renal pelvis and calyces. VUR is associated with urinary tract infections (UTI) and congenital urogenital anomalies. Voiding cystourethrography (VCUG) used to be the gold standard for diagnosing VUR. However, because of the associated radiation exposure, the importance of VCUG has decreased in the clinical practice. Thus, voiding urosonography (VUS) has emerged as it allows for radiation-free detection and the reliable classification of different grades of reflux. However, according to current recommendations from the American Academy of Pediatrics and the National Institute for Health and Care Excellence, conventional ultrasound examination is the only primary diagnostic method of choice for children following their first UTI or those with congenital anomalies. Only if sonographic irregularities are observed, further diagnostics is prompted. Timely identification of VUR, however, is critical for the initiation of the appropriate therapy. In this study, we evaluated the detection of VUR using conventional ultrasound as well as VUS to determine the significance of VUS as a diagnostic tool. We assumed that by using only conventional ultrasound, not all relevant grades of VUR would be detected. Therefore, we believe, that the significance of CUS as a complimentary diagnostic modality has increased, and, as its radiation-free, should be preferred to VCUG. Methods We retrospectively analyzed data from 225 patients, who had presented to Vivantes Klinikum Neukölln between 2016 and 2020 with a first or recurring UTI (n=200) or with a suspected congenital urogenital anomaly (n=25), in which VUS was performed in addition to conventional ultrasound of the kidney and urinary tract. Results In our cohort, 95 (≙ 42,2%) female and 130 (≙ 57,8%) male patients were included. Their median age was 4 months (range between 11 days and 9 years). Out of 157 patients with normal findings in the conventional renal and urinary tract sonography, VUR grade I-V was shown in 67 (≙42,7%) patients, and VUR grade III and higher in 42 (≙26,8%) patients following VUS. The sensitivity of the detection of VUR using conventional ultrasound was only 40% (specificity 70%). There was no patient with normal sonography findings and VUR ≥ grade III in the suspected congenital anomaly group. Had only conventional ultrasound been performed, VUR ≥ grade III would have remained undetected in 26,8% of patients in the UTI group. Without the additional use of VUS, those patients wouldn’t have received adequate therapy. Conclusion In summary, we were able to show the benefits of establishing VUS as a complementary diagnostic tool, alongside conventional ultrasound examination, in patients following UTI. Additional VUS allows for the early detection of VUR and helps to quickly initiate optimal therapy, which is can contribute to avoid potentially irreversible damage to the kidneys and urinary tract.Einleitung Vesikouretraler Reflux (VUR) ist definiert als retrograder Fluss von Urin aus der Harnblase in die Ureteren oder das Nierenbeckenkelchsystem. Das Auftreten von VUR ist assoziiert mit Harnwegsinfektionen (HWI) und angeborenen Fehlbildungen des Harntraktes. Den Goldstandard in der Diagnostik stellte bisher die Miktionszystourethrographie (MCU) dar. Aufgrund der Strahlenexposition sinkt jedoch ihre Bedeutung im klinischen Alltag. Als alternative Untersuchungsmethode rückt die Miktionsurosonographie (MUS) zunehmend in den Vordergrund. Sie ermöglicht eine strahlenfreie und sensitive Diagnostik mit zuverlässiger Einteilung der verschiedenen Refluxgrade. Aktuellen Empfehlungen der American Academy of Pediatrics und des National Institute for Health and Care Excellence folgend, erhalten Patienten mit erstem HWI oder angeborenen Fehlbildungen allerdings lediglich eine Sonographie des Harntraktes als Primärdiagnostik. Nur bei Auffälligkeiten wird weitere Diagnostik in Form einer MCU oder MUS veranlasst. Die rechtzeitige Diagnosestellung des VUR hat jedoch Einfluss auf Therapie und Langzeitoutcome. Die Arbeit soll die Ergebnisse der Sonographie und MUS im Hinblick auf das Erkennen von VUR untersuchen, um die Bedeutung der MUS in der Diagnostik von HWI und bei Patienten mit V.a. angeborene Fehlbildungen im Kindesalter zu beurteilen. Wir nehmen an, dass rein sonographisch nicht alle relevanten Refluxgrade erkannt werden und daher die Rolle der MUS als Alternative zur MCU an Bedeutung gewinnt. Methoden Es erfolgte eine retrospektive Datenanalyse von 225 Patientendaten, die nach erster oder rezidivierender HWI (n=200) beziehungsweise bei V.a. angeborener Fehlbildung (n=25) zwischen 2016 und 2020 im Vivantes Klinikum Neukölln vorgestellt wurden und sowohl eine Sonographie des Harntraktes als auch eine MUS erhielten. Ergebnisse In unserer Kohorte wurden 95 weibliche Patientinnen (≙ 42,2%) und 130 (≙ 57,8%) männliche Patienten eingeschlossen. Das mediane Alter betrug 4 Monate (Altersbandbreite 11 Tage bis 9 Jahre). Von 157 Patienten mit unauffälliger Sonographie zeigten sich 67 (≙ 42,7%) mit einem VUR Grad I-V, und 42 (≙ 26,8%) wiesen einen VUR Grad III und höher in der MUS auf. Die Sensitivität der Sonographie für die Entdeckung eines Refluxes betrug damit 40%, die Spezifität 70%. Es zeigte sich kein Patient aus der Kohorte der angeborenen Fehlbildungen, der bei unauffälliger Sonographie einen VUR ≥ Grad III aufwies. Nach alleiniger Sonographie wäre bei 26,8% der Patienten mit HWI ein VUR ≥ Grad III übersehen worden. Diese Patienten hätten ohne ergänzende MUS keine adäquate Therapie erhalten. Schlussfolgerung Zusammenfassend hat sich die MUS bei uns als sinnvolle, komplementäre Diagnostik zur Sonographie bei Kindern mit HWI erwiesen. Sie ermöglicht das frühzeitige Erkennen von behandlungsbedürftigen Refluxgraden und kann damit zum rechtzeitigen Therapiebeginn und unter Umständen zur Verhinderung von Langzeitschäden beitragen

Influence of 1 Alpha, 25-Dihydroxyvitamin D3 on T helper 17 cells and related cytokines in systemic lupus erythematosus

Background: Systemic lupus erythematosus (SLE) is a multisystem autoimmune disease. Emerging data suggests that T helper 17 (Th17) cells play a pathogenic role in SLE and the increased number of these cells correlates with disease activity. In recent years, 1α, 25-dihydroxyvitamin D3 (1,25VitD3) has been considered as an immunomodulatory factor. Objective: To investigate the effect of 1,25VitD3 on Th17 cells and on the expression of related cytokines in SLE patients. Method: Thirty SLE patients (newly diagnosed or in remission) were sampled for 10 ml whole blood to isolate peripheral blood mononuclear cells (PBMCs) using Ficoll-Hypaque density gradient centrifugation. Isolated cells were cultured in the presence and absence of 50 nM 1,25VitD3. After incubation, cells were harvested and stimulated for 4-5 hours with phorbol myristate acetate (PMA) and ionomycin in the presence of brefeldin A. IL-17 secreting cells were analyzed by flowcytometry. RNA was extracted from cultured cells, cDNA was synthesized, and the expression levels of IL-6, IL-17, IL-23 and TGF-β genes were assessed by real-time PCR. Results: The percentage of Th17 cells (CD3+CD8- IL-17+ T cells) decreased significantly in 1,25VitD3-treated cells (3.67 ± 2.43%) compared to untreated cells (4.65 ± 2.75%) (p=0.003). The expression of TGF-β up regulated (1.38-fold) and the expression of IL-6 (50%), IL-17 (27%) and IL-23 (64%) down regulated after 1,25VitD3 treatment. Conclusion: This study showed that 1,25VitD3 modulates Th17 related pathways in SLE patients and revealed the immunomodulatory effect of 1,25VitD3 on the Th17 mediated autoimmunity. © 2015, Shiraz University of Medical Sciences. All rights reserved