A new model for DPDK-based virtual switches

International audienceIn an SDN/NFV-enabled network, the behavior of virtual switches is a major concern in determining the overall network performance. The prominent open-source solution for virtual switching is Open vSwitch while the DPDK library has been developed to accelerate the packet processing. In this paper, we develop a general framework for the modeling and the analysis of DPDK-based virtual switches, taking into account the switch-over times (amount of time needed for a CPU core to switch from one input queue to another). Our model delivers performance metrics such as the buffer occupancy, the loss rate and the sojourn time of a packet in RX queues. We compare our new model with two existing models. Numerical results show that our model combines the accuracy of one model and the efficiency of the other

Towards including batch services in models for DPDK-based virtual switches

International audienceWith the development of NFV (Network Function Virtualization) paradigm, networking functions would gradually move from specialized and proprietary hardware to open-source software run over a virtual machine (VM) deployed on commodity hardware. Open vSwitch (OVS) is the most prominent open-source solution implementing a virtual switch, while DPDK (Data Plane Development Kit) is a set of specialized libraries to enhance the performance. In particular, DPDK allows packets to be processed by batches. In this paper, we address the issue of modeling the behavior of a DPDK-based virtual switch. First, we investigate the influence of batch services on the overall performance of a virtual switch. Second, we extend two former analytical models to include the processing of packets by batches. We propose a simple means to do it, and we evaluate the accuracy of our solution on two different scenarios. Numerical results show that, despite its simplicity, our approach provides fairly good results when compared to simulation

Towards including batch services in models for DPDK-based virtual switches

International audienceWith the development of NFV (Network Function Virtualization) paradigm, networking functions would gradually move from specialized and proprietary hardware to open-source software run over a virtual machine (VM) deployed on commodity hardware. Open vSwitch (OVS) is the most prominent open-source solution implementing a virtual switch, while DPDK (Data Plane Development Kit) is a set of specialized libraries to enhance the performance. In particular, DPDK allows packets to be processed by batches. In this paper, we address the issue of modeling the behavior of a DPDK-based virtual switch. First, we investigate the influence of batch services on the overall performance of a virtual switch. Second, we extend two former analytical models to include the processing of packets by batches. We propose a simple means to do it, and we evaluate the accuracy of our solution on two different scenarios. Numerical results show that, despite its simplicity, our approach provides fairly good results when compared to simulation

Towards including batch services in models for DPDK-based virtual switches

International audienceWith the development of NFV (Network Function Virtualization) paradigm, networking functions would gradually move from specialized and proprietary hardware to open-source software run over a virtual machine (VM) deployed on commodity hardware. Open vSwitch (OVS) is the most prominent open-source solution implementing a virtual switch, while DPDK (Data Plane Development Kit) is a set of specialized libraries to enhance the performance. In particular, DPDK allows packets to be processed by batches. In this paper, we address the issue of modeling the behavior of a DPDK-based virtual switch. First, we investigate the influence of batch services on the overall performance of a virtual switch. Second, we extend two former analytical models to include the processing of packets by batches. We propose a simple means to do it, and we evaluate the accuracy of our solution on two different scenarios. Numerical results show that, despite its simplicity, our approach provides fairly good results when compared to simulation

A new model for DPDK-based virtual switches

International audienceIn an SDN/NFV-enabled network, the behavior of virtual switches is a major concern in determining the overall network performance. The prominent open-source solution for virtual switching is Open vSwitch while the DPDK library has been developed to accelerate the packet processing. In this paper, we develop a general framework for the modeling and the analysis of DPDK-based virtual switches, taking into account the switch-over times (amount of time needed for a CPU core to switch from one input queue to another). Our model delivers performance metrics such as the buffer occupancy, the loss rate and the sojourn time of a packet in RX queues. We compare our new model with two existing models. Numerical results show that our model combines the accuracy of one model and the efficiency of the other

DNA Detection Using Plasmonic Enhanced Near-Infrared Photoluminescence of Gallium Arsenide

Efficient near-infrared detection of specific DNA with single nucleotide polymorphism selectivity is important for diagnostics and biomedical research. Herein, we report the use of gallium arsenide (GaAs) as a sensing platform for probing DNA immobilization and targeting DNA hybridization, resulting in ∼8-fold enhanced GaAs photoluminescence (PL) at ∼875 nm. The new signal amplification strategy, further coupled with the plasmonic effect of Au nanoparticles, is capable of detecting DNA molecules with a detection limit of 0.8 pM and selectivity against single base mismatches. Such an ultrasensitive near-infrared sensor can find a wide range of biochemical and biomedical applications

Expression of Amyloid-Associated miRNAs in Both the Forebrain Cortex and Hippocampus of Middle-Aged Rat

Background: Aging is associated with the gradual cognitive decline and shows the typical senile plaque formation in the brain, which results from the aggregation of beta amyloid (Aβ) peptide following the abnormal proteolytic processing of amyloid precursor protein (APP) by β-secretase (BACE1) and γ-secretase. Accumulating evidence indicates that several microRNAs (miRNAs) are involved in the Alzheimer's disease (AD) by regulating the expression of APP and BACE1 proteins. However, the cognitive ability and the expression profile of the APP- and BACE1-associated miRNAs in the middle-aged population are largely unknown. Methods: The learning and memory ability in rats were determined by Morris Water Maze test. The protein levels of APP and BACE1 were detected by western blotting. The quantitative polymerase chain reaction was used to identify the miRNAs levels in forebrain cortex and the hippocampus. Results: Middle-aged rats have declined learning ability without changes in the memory ability, and increased APP and BACE1 protein expression in the forebrain cortex. Computational analysis using Targetscan and Pictar databases reveals that totally 4 predicted miRNAs have conserved binding site with APP, namely miR-106b, -17-5p, -153, -101. All of them showed decreased expression in both the forebrain cortex and hippocampus. Among the 10 predicted miRNAs targeting BACE1, different expression profiles were identified in the forebrain cortex (decreased: miR-9, -19a, -135a, -15b, -16, -195, -29c, -214; increased: miR-124; no change: miR-141) and the hippocampus (decreased: miR-9, -15b, -16, -195, -29c, -124; increased: miR-19a, -135a, -214, -141) in the middle-aged rats compared with the young rats. Conclusion: Our results provided the first evidence that middle-aged rats have begun displaying cognitive disability with abnormal expression of APP- and BACE1-related miRNAs in the hippocampus and forebrain cortex

Inverse Spinel Cobalt–Iron Oxide and N‑Doped Graphene Composite as an Efficient and Durable Bifuctional Catalyst for Li–O₂ Batteries

Rational design of efficient bifunctional oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) electrocatalysts are critical for rechargeable Li–O₂ batteries. Here, we report inverse spinel Co­[Co,Fe]­O₄/nitrogen-doped graphene (NG) composite used as a promising catalyst for rechargeable Li–O₂ batteries. The cells with Co­[Co,Fe]­O₄/NG catalyst exhibit high initial capacity, remarkable cyclability, and good rate capability. Moreover, the overpotential of the Li–O₂ batteries is reduced significantly. The improved ORR/OER performances are attributed to the good property of Co­[Co,Fe]­O₄ with an inverse spinel structure toward ORR and the improved electronic conductivity of N-doped graphene. The density functional theory (DFT) calculation shows the rate limitation step for ORR on the inverse spinel surface is the growth of the Li₂O₂ cluster while the rate limitation step for the OER pathway is the oxidation of Li₂O₂. The inverse spinel surface in Co­[Co,Fe]­O₄/NG is more active than that of the normal spinel phases for the Li–O₂ battery reactions. This work not only provides a promising bifunctional catalyst for practical metal air batteries but also offers a general strategy to rationally design catalysts for various applications