Exploring online virtual networks mapping with stochastic bandwidth demand in multi-datacenter

Network virtualization serves as a promising technique for providing a flexible and highly adaptable shared substrate network to satisfy the diversity of demands and overcoming the ossification of Internet infrastructure. As a key issue of constructing a virtual network (VN), various state-of-the-art algorithms have been proposed in many research works for addressing the VN mapping problem. However, these traditional works are efficient for mapping VN which with deterministic amount of network resources required, they even deal with the dynamic resource demand by using over-provisioning. These approaches are obviously not advisable, since the network resources are becoming more and more scarce. In this paper, we investigate the online stochastic VN mapping (StoVNM) problem, in which the VNs are generated as a Poisson process and each bandwidth demand x _i follows a normal distribution, i.e., x _i ~ N(μ _i , σ _i ²). Firstly, we formulate the model for StoVNM problem by mixed integer linear programming, which with objective including minimum-mapping-cost and load balance. Then, we devise a sliding window approach-based heuristic algorithm w-StoVNM for tackling this NP-hard StoVNM problem efficiently. The experimental results achieved from extensive simulation experiments demonstrate the effectiveness of the proposed approach and superiority than traditional solutions for VN mapping in terms of VN mapping cost, blocking ratio, and total net revenue in the long term.     

Morphological dilation image coding with context weights prediction

This paper proposes an adaptive morphological dilation image coding with context weights prediction. The new dilation method is not to use fixed models, but to decide whether a coefficient needs to be dilated or not according to the coefficient’s predicted significance degree. It includes two key dilation technologies: (1) controlling dilation process with context weights to reduce the output of insignificant coefficients and (2) using variable-length group test coding with context weights to adjust the coding order and cost as few bits as possible to present the events with large probability. Moreover, we also propose a novel context weight strategy to predict a coefficient’s significance degree more accurately, which can be used for two dilation technologies. Experimental results show that our proposed method outperforms the state of the art image coding algorithms available today.     

Non‐dominated sorting particle swarm optimization (NSPSO) and network security policy enforcement for Policy Space Analysis

Network operators depend on security services with the aim of safeguarding their IT infrastructure. Various types of network security policies are employed on a global scale and are disseminated among several security middleboxes implemented in networks. But, owing to the complications in security policies, it is not quite efficient to directly use the path‐wise enforcement schemes that are prevalent. The major motivation of this work is to improve security levels and solve the policy enforcement problem. For the first time, this work reports the issue of policy enforcement on middleboxes. The major contribution of this work is to design security policy enforcement as a Weighted K Set Covering Problem, and we designed a Policy Space Analysis (PSA) tool intended for a group of operations in the security policy. This PSA tool was developed based on range‐signified hyper‐rectangles, which are indexed by the Hilbert R‐tree. Leveraging the PSA, we first investigated the topological features of various kinds of policies. Balancing the PSA tool in a non‐dominated sorting particle swarm optimization technique exposes the intrinsic difficulties of this security strategy and provides guidance for designing the enforcement approach. In addition, in this research, a new fuzzy rule‐based classification system is introduced for packet classification. A scope‐wise policy enforcement algorithm was proposed, which chooses a moderate number of enforcement network nodes for deploying multiple policy subsets in a greedy manner. This scheme is much quicker compared with the first one and therefore has found its application in real‐time deployments.     

Enhanced Binary Hexagonal Extrema Pattern (EBHXEP) Descriptor for Iris Liveness Detection

Wireless Personal Communications - Biometric traits are frequently used by security agencies for automatic recognition of a person. There are numerous biometric traits used for person...     

Evidence for the Band‐Edge Exciton of CuInS2 Nanocrystals Enables Record Efficient Large‐Area Luminescent Solar Concentrators

Ternary I‐III‐VI₂ nanocrystals (NCs), such as CuInS₂, are receiving attention as heavy‐metals‐free materials for solar cells, luminescent solar concentrators (LSCs), LEDs, and bio‐imaging. The origin of the optical properties of CuInS₂ NCs are however not fully understood. A recent theoretical model suggests that their characteristic Stokes‐shifted and long‐lived luminescence arises from the structure of the valence band (VB) and predicts distinctive optical behaviours in defect‐free NCs: the quadratic dependence of the radiative decay rate and the Stokes shift on the NC radius. If confirmed, this would have crucial implications for LSCs as the solar spectral coverage ensured by low‐bandgap NCs would be accompanied by increased re‐absorption losses. Here, by studying stoichiometric CuInS₂ NCs, it is revealed for the first time the spectroscopic signatures predicted for the free band‐edge exciton, thus supporting the VB‐structure model. At very low temperatures, the NCs also show dark‐state emission likely originating from enhanced electron‐hole spin interaction. The impact of the observed optical behaviours on LSCs is evaluated by Monte Carlo ray‐tracing simulations. Based on the emerging device design guidelines, optical‐grade large‐area (30×30 cm²) LSCs with optical power efficiency (OPE) as high as 6.8% are fabricated, corresponding to the highest value reported to date for large‐area devices.     

Engineering Iron Oxide Hollow Nanospheres to Enhance Antimicrobial Property: Understanding the Cytotoxic Origin in Organic Rich Environment

Engineered magnetic iron oxide nanoparticles with surprisingly high antimicrobial activity and excellent safety profiles to mammalian cell lines have been developed. Hematite hollow nanospheres (HNSs) are prepared by a facile hard templating method; reduction of hematite HNSs by H₂ leads to magnetite HNSs. The antimicrobial activity of magnetite HNSs towards Gram negative (Escherichia coli) and Gram positive (Staphylococcus epidermidis) bacteria is evaluated against hematite HNSs and conventional magnetite (C‐magnetite; diameter <50 nm). Superior antibacterial performance is observed for magnetite HNSs towards both E. coli and S. epidermidis over hematite HNSs and C‐magnetite. The origin of the antimicrobial activity of magnetite HNSs is the high leaching of iron ions in the presence of microorganisms, which leads to high generation of reactive oxygen species. Magnetite HNSs allow multiple‐fold increase in the generation of soluble iron ions over hematite HNSs and C‐magnetite, showing that control over both the composition and nanostructure is crucial to tune the antimicrobial activity of iron oxides. Based on the current findings, magnetic HNSs show promising potential antimicrobial applications.     

Steady-State Analysis of a Permanent Magnet Synchronous Motor Drive with Current Source Inverter

A steady-state analysis is presented of a permanent magnet (PM) synchronous motor drive with a current source inverter (CSI). The torque-speed profile required of the drive is a constant torque region from zero to base speed and a constant power region above base speed. The analysis assumes position feedback control. Optimum control strategies are obtained for the two regions of the torque-speed profile. Using these optimum strategies, performance curves of the drive are predicted and experimentally verified. The time harmonics in the motor are a function of the presence and configuration of the dampers in the motor. An expression is obtained for the equivalent inductance seen by the harmonics for different damper configurations. A Fourier series approach is used to predict the line-to-line voltage waveforms. Even though the presence of the dampers is not essential to the operation of the drive, their presence reduces the voltage spikes present in the line-to-line voltage.     

Isotropic Constitutive Model for Sintering Particle Packings

This paper presents an isotropic model for the effective viscosities of sintering particle packings. The relationship between the macroscopic stress and deformation rate is based on the behavior of individual interparticle contacts, represented by contact viscosities, and the statistics of the packing. The contact viscosities depend on the contact area, which is the primary variable used to describe the state of the packing. A direct consequence of this choice of state variable is that the effective viscosities are identically zero for an undeformed and unsintered packing. Specific results are presented for the case of Newtonian viscous materials. The model is compared with existing models for porous Newtonian viscous materials. Experiments conducted with spherical glass powder packings show good agreement with the model. Finite-element simulations using the model have been used to study forging of a pellet.