Performance modelling and analysis of software defined networking

Software Defined Networking (SDN) is an emerging architecture for the next-generation Internet, providing unprecedented network programmability to handle the explosive growth of Big Data driven by the popularisation of smart mobile devices and the pervasiveness of content-rich multimedia applications. In order to quantitatively investigate the performance characteristics of SDN networks, several research efforts from both simulation experiments and analytical modelling have been reported in the current literature. Among those studies, analytical modelling has demonstrated its superiority in terms of cost-effectiveness in the evaluation of large-scale networks. However, for analytical tractability and simplification, existing analytical models are derived based on the unrealistic assumptions that the network traffic follows the Poisson process which is suitable to model non-bursty text data and the data plane of SDN is modelled by one simplified Single Server Single Queue (SSSQ) system. Recent measurement studies have shown that, due to the features of heavy volume and high velocity, the multimedia big data generated by real-world multimedia applications reveals the bursty and correlated nature in the network transmission. With the aim of the capturing such features of realistic traffic patterns and obtaining a comprehensive and deeper understanding of the performance behaviour of SDN networks, this paper presents a new analytical model to investigate the performance of SDN in the presence of the bursty and correlated arrivals modelled by Markov Modulated Poisson Process (MMPP). The Quality-of-Service performance metrics in terms of the average latency and average network throughput of the SDN networks are derived based on the developed analytical model. To consider realistic multi-queue system of forwarding elements, a Priority-Queue (PQ) system is adopted to model SDN data plane. To address the challenging problem of obtaining the key performance metrics, e.g., queue length distribution of PQ system with a given service capacity, a versatile methodology extending the Empty Buffer Approximation (EBA) method is proposed to facilitate the decomposition of such a PQ system to two SSSQ systems. The validity of the proposed model is demonstrated through extensive simulation experiments. To illustrate its application, the developed model is then utilised to study the strategy of the network configuration and resource allocation in SDN networksThis work is supported by the EU FP7 “QUICK” Project (Grant NO. PIRSES-GA-2013-612652) and the National Natural Science Foundation of China (Grant NO. 61303241)

Synthesis and characterization of folate-poly(ethylene glycol) chitosan graft-polyethylenimine as a non-viral carrier for tumor-targeted gene delivery

The use of chitosan and chitosan derivatives for gene delivery is limited due to the low transfection efficiency and difficulty in transfecting into a variety of cell types, including some cancer cells overexpressing folate receptor (FRs). In order to solve this problem, folate (FA) and poly(ethylene glycol) (PEG) was conjugated to chitosan-graft-polyethylenimine (CHI-g-PEI) to enhance water-solubility and the transfection efficiency. In the present study, a cell specific targeting molecule FA was linked on PEG and then grafted the FA-PEG onto CHI-g-PEI. The FA-PEG-grafted CHI-g-PEI (FA-PEG-CHI-g-PEI) effectively condensed the plasmid DNA (pDNA) into nanoparticles with positive surface charge under the suitable nitrogen/phosphorus (N/P) ratio. In vitro, transfection efficiency of the FA-PEG-CHI-g-PEI /pDNA complex in 293T cells and LoVo cells (FRs over-expressing cell lines) increased with increasing N/P ratio under N/P = 15 and was more than 50%, but no significant difference in human lung carcinoma cells (A549) cells (FRs deficient cell lines). Importantly, in vivo luciferase expression showed that the efficiency of FA-PEG-CHI-g-PEI -mediated transfection (50 μg luciferase plasmid (pLuc), N/P ratio = 15) was comparable to that of adenovirus-mediated luciferase transduction (1 × 109 pfu) in melanomabearing mice. It was concluded that FA-PEG-CHI-g-PEI, which has improved transfection efficiency and FRs specificity in vitro and in vivo, may be useful in gene therapy.Key words: Folate poly(ethylene glycol)-chitosan-grafted-polyethylenimine (FA-PEG-CHI-g-PEI), gene transfection, non-virus vector, in vitro, in viv

Apoptosis induced by Staphylococcus aureus in human monocytic U937 cells involves Akt and mitogen-activated protein (MAPK) phosphorylation

Staphylococcus aureus (S. aureus) is a leading etiologic agent of nosocomial and community-acquired infectious diseases. Numerous studies have shown that, S. aureus could promote apoptosis in host cells. Unfortunately, the cellular and molecular mechanisms responsible for this phenomenon are still poorly understood. The present study aims to elucidate the signaling mechanisms involved in S. aureus-induced U937 cells apoptosis by investigating the role of phosphatidylinositol 3-kinase/Akt (PI3K/Akt), mitogen-activated protein (MAPK) and caspases. Our results showed that, i decreased the expression of phosphorylation-Akt. In contrast, S. aureus increased phosphorylation-JNK1/2, phosphorylation-ERK1/2 and phosphorylation-p38 MAPK. Treatment of U937 cells with S. aureus resulted in the activation of caspase-3 and -9. Furthermore, caspases inhibitors, SP600125 (JNK inhibitor), SB203580 (p38MAPK inhibitor) and PD98059 (ERK inhibitor) decreased apoptosis in U937 cells. However, LY294002 (Akt inhibitor) increased U937 cells apoptosis. Taken together, our study for the first time suggest that S. aureus is able to enhance apoptosis of U937 cells through inhibition of PI3K/Akt and activation of MAPK signaling pathways.Key words: Staphylococcus aureus, mitogen-activated protein (MAPK), apoptosis, U937

Design optimization of an interior-type permanent magnet BLDC motor using PSO and improved MEC

In this paper, an improved magnetic equivalent circuit (MEC) is applied to calculate the nonlinear magnetic field in an interior-type permanent-magnet (IPM) brushless DC (BLDC) motor. Compared with the finite element method, the MEC method is much more time efficient, whereas compared with the conventional MEC method, the improved MEC is more accurate since it takes the complicate topological structure of the motor into account. A rough design of the IPM BLDC motor was firstly conducted by the improved MEC method. The particle swarm optimization (PSO) algorithm is then employed to refine the design for optimal structural parameters that result in the lowest cost and highest performance

Optimization of fermentation medium for nisin production from Lactococcus lactis subsp. lactis using response surface methodology (RSM) combined with artificial neural network-genetic algorithm (ANN-GA)

Nisin is a bacteriocin approved in more than 50 countries as a safe natural food preservative. Response surface methodology (RSM) combined with artificial neural network-genetic algorithm (ANN-GA) was employed to optimize the fermentation medium for nisin production. Plackett-Burman design (PBD) was used for identifying the significant components in the fermentation medium. After that, the path of steepest ascent method (PSA) was employed to approach their optimal concentrations. Sequentially, Box-Behnken design experiments were implemented for further optimization. RSM combined with ANNGA were used for analysis of data. Specially, a RSM model was used for determining the individual effect and mutual interaction effect of tested variables on nisin titer (NT), an ANN model was used for NT prediction, and GA was employed to search for the optimum solutions based on the ANN model. As the optimal medium obtained by ANN-GA was located at the verge of the test region, a further Box- Behnken design based on the RSM statistical analysis results was implemented. ANN-GA was implemented using the further Box-Behnken design data to locate the optimum solution which was as follow (g/l): Glucose (GLU) 15.92, peptone (PEP) 30.57, yeast extraction powder (YEP) 39.07, NaCl 5.25, KH2PO4 10.00, and MgSO4·7H2O 0.20, with expected NT of 22216 IU/ml. The validation experiments with the optimum solution were implemented in triplicate and the average NT was 21423 IU/ml, which was 2.13 times higher than that without ANN-GA methods and 8.34 times higher than that without optimization.Key words: Response surface methodology, artificial neural network, genetic algorithm, nisin titer

Deep Karaoke: Extracting Vocals from Musical Mixtures Using a Convolutional Deep Neural Network

Identification and extraction of singing voice from within musical mixtures is a key challenge in source separation and machine audition. Recently, deep neural networks (DNN) have been used to estimate 'ideal' binary masks for carefully controlled cocktail party speech separation problems. However, it is not yet known whether these methods are capable of generalizing to the discrimination of voice and non-voice in the context of musical mixtures. Here, we trained a convolutional DNN (of around a billion parameters) to provide probabilistic estimates of the ideal binary mask for separation of vocal sounds from real-world musical mixtures. We contrast our DNN results with more traditional linear methods. Our approach may be useful for automatic removal of vocal sounds from musical mixtures for 'karaoke' type applications

Atomic-scale combination of germanium-zinc nanofibers for structural and electrochemical evolution

Alloys are recently receiving considerable attention in the community of rechargeable batteries as possible alternatives to carbonaceous negative electrodes; however, challenges remain for the practical utilization of these materials. Herein, we report the synthesis of germanium-zinc alloy nanofibers through electrospinning and a subsequent calcination step. Evidenced by in situ transmission electron microscopy and electrochemical impedance spectroscopy characterizations, this one-dimensional design possesses unique structures. Both germanium and zinc atoms are homogenously distributed allowing for outstanding electronic conductivity and high available capacity for lithium storage. The as-prepared materials present high rate capability (capacity of similar to 50% at 20 C compared to that at 0.2 C-rate) and cycle retention (73% at 3.0 C-rate) with a retaining capacity of 546 mAh g(-1) even after 1000 cycles. When assembled in a full cell, high energy density can be maintained during 400 cycles, which indicates that the current material has the potential to be used in a large-scale energy storage system

Anti-cadherin-17 antibody modulates Beta-catenin signaling and tumorigenicity of hepatocellular carcinoma

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Evaluating regional emission estimates using the TRACE-P observations

Measurements obtained during the NASA Transport and Chemical Evolution over the Pacific (TRACE-P) experiment are used in conjunction with regional modeling analysis to evaluate emission estimates for Asia. A comparison between the modeled values and the observations is one method to evaluate emissions. Based on such analysis it is concluded that the inventory performs well for the light alkanes, CO, ethyne, SO2, and NOₓ. Furthermore, based on model skill in predicting important photochemical species such as O₃, HCHO, OH, HO₂, and HNO₃, it is found that the emissions inventories are of sufficient quality to support preliminary studies of ozone production. These are important finding in light of the fact that emission estimates for many species (such as speciated NMHCs and BC) for this region have only recently been estimated and are highly uncertain. Using a classification of the measurements built upon trajectory analysis, we compare observed species distributions and ratios of species to those modeled and to ratios estimated from the emissions inventory. It is shown that this technique can reconstruct a spatial distribution of propane/benzene that looks remarkably similar to that calculated from the emissions inventory. A major discrepancy between modeled and observed behavior is found in the Yellow Sea, where modeled values are systematically underpredicted. The integrated analysis suggests that this may be related to an underestimation of emissions from the domestic sector. The emission is further tested by comparing observed and measured species ratios in identified megacity plumes. Many of the model derived ratios (e.g., BC/CO, SOₓ/C₂H₂) fall within ∼25% of those observed and all fall outside of a factor of 2.5. (See Article file for details of the abstract.)Department of Civil and Environmental EngineeringAuthor name used in this publication: Wang, T