Optimal Orchestration of Virtual Network Functions

-The emergence of Network Functions Virtualization (NFV) is bringing a set of novel algorithmic challenges in the operation of communication networks. NFV introduces volatility in the management of network functions, which can be dynamically orchestrated, i.e., placed, resized, etc. Virtual Network Functions (VNFs) can belong to VNF chains, where nodes in a chain can serve multiple demands coming from the network edges. In this paper, we formally define the VNF placement and routing (VNF-PR) problem, proposing a versatile linear programming formulation that is able to accommodate specific features and constraints of NFV infrastructures, and that is substantially different from existing virtual network embedding formulations in the state of the art. We also design a math-heuristic able to scale with multiple objectives and large instances. By extensive simulations, we draw conclusions on the trade-off achievable between classical traffic engineering (TE) and NFV infrastructure efficiency goals, evaluating both Internet access and Virtual Private Network (VPN) demands. We do also quantitatively compare the performance of our VNF-PR heuristic with the classical Virtual Network Embedding (VNE) approach proposed for NFV orchestration, showing the computational differences, and how our approach can provide a more stable and closer-to-optimum solution

Efficient Spatial Keyword Search in Trajectory Databases

An increasing amount of trajectory data is being annotated with text descriptions to better capture the semantics associated with locations. The fusion of spatial locations and text descriptions in trajectories engenders a new type of top-$k$ queries that take into account both aspects. Each trajectory in consideration consists of a sequence of geo-spatial locations associated with text descriptions. Given a user location $\lambda$ and a keyword set $\psi$, a top-$k$ query returns $k$ trajectories whose text descriptions cover the keywords $\psi$ and that have the shortest match distance. To the best of our knowledge, previous research on querying trajectory databases has focused on trajectory data without any text description, and no existing work has studied such kind of top-$k$ queries on trajectories. This paper proposes one novel method for efficiently computing top-$k$ trajectories. The method is developed based on a new hybrid index, cell-keyword conscious B$^+$-tree, denoted by \cellbtree, which enables us to exploit both text relevance and location proximity to facilitate efficient and effective query processing. The results of our extensive empirical studies with an implementation of the proposed algorithms on BerkeleyDB demonstrate that our proposed methods are capable of achieving excellent performance and good scalability.Comment: 12 page

Multiscale Fluctuation Features of the Dynamic Correlation between Bivariate Time Series

The fluctuation of the dynamic correlation between bivariate time series has some special features on the time-frequency domain. In order to study these fluctuation features, this paper built the dynamic correlation network models using two kinds of time series as sample data. After studying the dynamic correlation networks at different time-scales, we found that the correlation between time series is a dynamic process. The correlation is strong and stable in the long term, but it is weak and unstable in the short and medium term. There are key correlation modes which can effectively indicate the trend of the correlation. The transmission characteristics of correlation modes show that it is easier to judge the trend of the fluctuation of the correlation between time series from the short term to long term. The evolution of media capability of the correlation modes shows that the transmission media in the long term have higher value to predict the trend of correlation. This work does not only propose a new perspective to analyze the correlation between time series but also provide important information for investors and decision makers

Attenuation of Relapsing Fever Neuroborreliosis in Mice by IL-17A Blockade

Relapsing fever due to Borrelia hermsiiis characterized by recurrent bacteremia episodes. However, infection of B. hermsii, if not treated early, can spread to various organs including the central nervous system (CNS). CNS disease manifestations are commonly referred to as relapsing fever neuroborreliosis (RFNB). In the mouse model of B. hermsiiinfection, we have previously shown that the development of RFNB requires innate immune cells as well as T cells. Here, we found that prior to the onset of RFNB, an increase in the systemic proinflammatory cytokine response followed by sustained levels of IP-10 concurrent with the CNS disease phase. RNA sequencing analysis of the spinal cord tissue during the disease phase revealed an association of the interleukin (IL)-17 signaling pathway in RFNB. To test a possible role for IL-17 inRFNB, we compared B. hermsii infection in wild-type and IL-17A2/2mice. Although the onset of bacteremia and protective anti-B. hermsii antibody responses occurred similarly, the blood-brain barrier permeability, proinflammatory cytokine levels, immune cell infiltration in the spinal cord, and RFNB manifestations were significantly diminished in IL-17A2/2mice compared to wild-type mice. Treatment of B. hermsii-infected wild-type mice with anti-IL-17A antibody ameliorated the severity of spinal cord inflammation, microglial cell activation, and RFNB. These data suggest that the IL-17signaling pathway plays a major role in the pathogenesis of RFNB, and IL-17A blockade may be a therapeutic modality for controlling neuroborreliosis

Modèles et méthodes d’optimisation pour architecture NFV (Network Function Virtualization)

Due to the exponential growth of service demands, telecommunication networks are populated with a large and increasing variety of proprietary hardware appliances, and this leads to an increase in the cost and the complexity of the network management. To overcome this issue, the NFV paradigm is proposed, which allows dynamically allocating the Virtual Network Functions (VNFs) and therefore obtaining flexible network services provision, thus reducing the capital and operating costs. In this thesis, we focus on the VNF Placement and Routing (VNF-PR) problem, which aims to find the location of the VNFs to allocate optimally resources to serve the demands. From an optimization point of view, the problem can be modeled as the combination of a facility location problem (for the VNF location and server dimensioning) and a network design problem (for the demands routing). Both problems are widely studied in the literature, but their combination represents, to the best of our knowledge, a new challenge. We start working on a realistic VNF-PR problem to understand the impact of different policies on the overall network management cost and performance. To this end, we extend the work in [1] by considering more realistic features and constraints of NFV infrastructures and we propose a linear programming model and a math-heuristic to solve it. In order to better understand the problem structure and its properties, in the second part of our work, we focus on the theoretical study of the problem by extracting a simplified, yet significant variant. We provide results on the computational complexity under different graph topology and capacity cases. Then, we propose two mathematical programming formulations and we test them on a common testbed with more than 100 different test instances under different capacity settings. Finally, we address the scalability issue by proposing ILP-based constructive methods and heuristics to efficiently deal with large size instances (with up to 60 nodes and 1800 demands). We show that our proposed heuristics can efficiently solve medium size instances (with up to 30 nodes and 1000 demands) of challenging capacity cases and provide feasible solutions for large size instances of the most difficult capacity cases, for which the models cannot find any solution even with a significant computational time.Avec la croissance exponentielle des demandes de service, les opérateurs ont déployé de nombreux équipements, et par conséquent, la gestion du réseau est devenue de plus en plus difficile et coûteuse. La virtualisation des fonctions réseau (NFV) a été proposée comme un nouveau paradigme pour réduire les coûts liés à l’acquisition et à la maintenance pour les réseaux de télécommunications. Dans ce travail de thèse, nous nous intéressons aux problèmes du chaînage des fonctions virtuelles (VNFs) qui combinent des décisions de localisation des VNFs et de routage des demandes. D'un point de vue d'optimisation, ce problème est une combinaison des problèmes de localisation (pour la partie d'installation des VNFs) et de conception de réseaux (pour la partie de routage). Ces deux problèmes ont été largement étudié dans la littérature. Cependant, leur combinaison représente des divers challenges en termes de modélisation et de résolution. Dans la première partie de cette thèse, nous considérons une version réaliste du problème du chaînage des VNFs (VNF-PR) afin de comprendre l'impact des différents aspects sur les coûts et les performances de gestion du réseau. Dans ce but, nous étendons le travail dans~\cite{Addis2015} en considérant des caractéristiques et des contraintes plus réalistes des infrastructures NFV et nous proposons un modèle de programmation linéaire et une heuristique mathématique pour le résoudre. Dans le but de mieux comprendre la structure du problème et ses propriétés, la deuxième partie de la thèse est orientée vers l'étude théorique du problème, où nous avons étudié une version compacte du problème du chaînage des VNFs. Nous fournissons des résultats sur la complexité de calcul sous divers cas de topologie et de capacité. Ensuite, nous proposons deux modèles et nous les testons sur un testbed avec plus de 100 instances différentes avec différents cas de capacité. Au final, nous abordons la scalabilité du problème en proposant des méthodes constructives et des méthodes heuristiques basées sur la programmation linéaire entière pour traiter efficacement des instances de taille grande (jusqu'à 60 nœuds et 1800 demandes). Nous montrons que les heuristiques proposées sont capables de résoudre efficacement des instances de taille moyenne (avec jusqu'à 30 nœuds et 1 000 demandes) de cas de capacité difficiles et de trouver de bonnes solutions pour les instances dures, où le modèle ne peut fournir aucune solution avec un temps de calcul limité

Motion Deblurring for Single-Pixel Spatial Frequency Domain Imaging

The single-pixel imaging technique is applied to spatial frequency domain imaging (SFDI) to bring significant performance advantages in band extension and sensitivity enhancement. However, the large number of samplings required can cause severe quality degradations in the measured image when imaging a moving target. This work presents a novel method of motion deblurring for single-pixel SFDI. In this method, the Fourier coefficients of the reflected image are measured by the Fourier single-pixel imaging technique. On this basis, a motion-degradation-model-based compensation, which is derived by the phase-shift and frequency-shift properties of Fourier transform, is adopted to eliminate the effects of target displacements on the measurements. The target displacements required in the method are obtained using a fast motion estimation approach. A series of numerical and experimental validations show that the proposed method can effectively deblur the moving targets and accordingly improves the accuracy of the extracted optical properties, rendering it a potentially powerful way of broadening the clinical application of single-pixel SFDI

On the complexity of a Virtual Network Function Placement and Routing problem

The demand for network services, such as proxy or firewall, is ever increasing due to the massive diffusion of applications, both on computers and mobile devices. Virtual Network Functions allow to instantiate network services on clouds in a software based manner, thus allowing to dynamically provide services at a reasonable cost. In this work we consider the problem of placing Virtual Network Function instances (services) and routing the demands so as to guarantee that demands can reach the requested services. We discuss the complexity of a particular version of the Virtual Network Function placement and routing problem and the impact of the network topology on the problem complexity

On a Virtual Network Function Placement and Routing problem: properties and formulations

In recent years, the increasing diffusion of applications, both on computers and mobile devices, has yielded to an increasing demand for network services. So far, the network services, such as firewalls or tunneling, were provided by expensive hardware appliances, which could not keep up with the ever increasing demand nor allow new services to be embedded at a reasonable cost. Network Functions Virtualization has been recently proposed to overcome such issues: hardware appliances are replaced with Virtual Network Functions running on generic servers. Indeed, thanks to the Network Functions Virtualization paradigm, it is possible to flexibly, dynamically and cost-effectively manage network services. A key problem in implementing the Network Functions Virtualization paradigm is the so called Virtual Network Functions chaining problem: Virtual Network Function instances must be located on some network nodes. Demands must be routed so as to guarantee that each demand passes through the functions it requires. In this work we consider a particular case of the VNF chaining problem where each demand requires a single service and must be routed on a simple path. All the demands require the same service. Links and service instances are capacitated. The goal is to minimize the number of VNF instances installed. We investigate the problem properties and we compare two formulations inspired by the two main modeling strategies proposed in the literature