Engineering topics
Liu, Qiang
Publications and source records attributed to Liu, Qiang.
Measurements and analytics of wide-area file transfers over dedicated connections
Distributed scientific and big-data computations are becoming increasingly dependent on access to remote files. Wide-area file transfers are supported by two basic schemes: (i) application-level tools, such as GridFTP, that provide transport services between file systems housed at geographically separated sites, and (ii) file systems mounted over wide-area networks, using mechanisms such as LNet routers that make them transparently available. In both cases, the file transfer performance critically depends on the configuration consisting of host, file, IO, and disk subsystems, which are complex by themselves, as well as on their complex compositions implemented using buffers and IO-network data transitions. We present extensive file transfer rate measurements collected over dedicated 10 Gbps connections with 0-366 ms round-trip times, using GridFTP and XDD file transfer tools, and Lustre file system extended over wide-area networks using LNet routers. Our test configurations are composed of: three types of host systems; XFS, Lustre, and ext3 file systems; and Ethernet and SONET wide-area connections. We present analytics based on the convexity-concavity of throughput profiles which provide insights into throughput and its superior or inferior trend compared to linear interpolations. We propose the utilization-concavity coefficient, a scalar metric that characterizes the overall performance of any file transfer method consisting of specific configuration and scheme. Our results enable performance optimizations by highlighting the significant roles of (i) buffer sizes and parallelism in GridFTP and XDD, and (ii) buffer utilization and credit mechanism in LNet routers.
Deletion of JDP2 improves neurological outcomes of traumatic brain injury (TBI) in mice: Inactivation of Caspase-3
Highlights: • JDP2 deficiency attenuates cognitive performance induced by TBI in mice. • JDP2 deficiency attenuates apoptosis in cortex of TBI mice. • JDP2 increases Caspase-3 activation to promote inflammation and apoptosis in LPS-stimulated astrocytes. Traumatic brain injury (TBI) is a major cause of death and disability, also resulting in long-term serious neurological impairment in survivors. However, the pathogenesis of TBI has not been fully understood. Jun dimerization protein 2 (JDP2) is a member of the AP-1 family of transcription factors, containing a basic region-leucine zipper motif. JDP2 plays essential roles in various cellular processes, including differentiation, apoptosis, senescence and aging. In the study, we attempted to explore the effects of JDP2 on TBI progression both in vivo and in vitro. The wild type (WT) and JDP2 knockout (KO) mice were employed in our study and were subjected to TBI. The results showed that JDP2-deficient mice exhibited improved cognitive functions in TBI mice. The inflammatory cytokines, glial amount and apoptosis, as well as the protein of cleaved Caspase-3 were significantly increased after TBI in WT mice, and all these up-regulation were significantly mitigated by JDP2 knockout in mice. We also found that TBI induced JDP2 expression in hippocampus of mice. Lipopolysaccharide (LPS) also stimulated JDP2 expression levels in astrocytes isolated from WT mice, indicating the critical role of JDP2 in TBI. Suppressing Caspase-3 activation could reduce LPS-induced inflammation in astrocytes. Consistent with the results in vivo, LPS-induced inflammatory response and apoptosis were reversed by JDP2 deficiency in cells. Notably, we found that over-expressing JDP2 could further promoted inflammation, apoptosis and Caspase-3 activation induced by LPS. Collectively, JDP2 knockout effectively attenuate TBI in vivo and in vitro through blocking Caspase-3 activation, providing a potential therapeutic target for TBI or even other neurological disorders.
Transcriptome of porcine alveolar macrophages activated by interferon-gamma and lipopolysaccharide
The molecular repertoire of porcine alveolar macrophages (PAMs) is greatly affected by the microenvironment they are exposed to, and specifically by inflammatory cytokines, such as interferon gamma (IFN-γ) released by activated lymphocytes, and microbial products, such as lipopolysaccharide (LPS). In our previous study, we found that IFN-γ- and LPS-activated PAMs (M1) could inhibit porcine reproductive and respiratory syndrome virus (PRRSV) replication. In this study, comprehensive analysis of the expression profiles of the genes associated with the polarization of M0-type PAMs (resting) toward M1 phenotypes (activated by IFN-γ and LPS) led to the following main results: 1) 1551 and 1823 genes were upregulated or downregulated in M1-type PAMs, respectively, compared with M0-type PAMs; 2) Among these, genes encoding ASS1 and CRTAM were the most upregulated and downregulated, respectively; 3) Genes involved in cytokine-cytokine receptor interaction and the JAK/STAT signaling pathway were significantly upregulated, suggesting their critical role in cellular activation; and 4) Genes involved in antigen proteolysis and presentation (immunoproteasome subunits), and inhibition of virus replication (host restriction factors) were significantly upregulated, emphasizing the critical role of these cytokines in immunity. Thus, our results provide important information for future studies on the role of PAM polarization in modulation of infection.
Anti-viral immune response in the lung and thymus: Molecular characterization and expression analysis of immunoproteasome subunits LMP2, LMP7 and MECL-1 in pigs
Both the lung and the thymus are vital target organ for pathogens including viruses. The immunoproteasome (i-proteasome) enhances antigen presentation for MHC class I molecules to activate CD8+T lymphocyte. These facilitate antiviral adaptive immune response. Our previous study found that, expression of i-proteasome subunits in porcine lung was altered during normal and inflammatory conditions. To date, the expression of i-proteasome subunits in porcine thymus to viruses has not been investigated. In the present study, LMP2, LMP7, and MECL-1 were cloned, identified and their sequences encoded predicted proteins of 216, 275, and 278 amino acids, respectively. Expression of LMP2, LMP7, and MECL-1, in the cytoplasm and nucleus, was markedly altered in the porcine reproductive and respiratory syndrome virus (PRRSV)-infected lung and thymus. And dendritic cells and epithelial cells readily expressed the i-proteasome subunit LMP2 in the thymus of PRRSV-infected pigs compared to that in mock-infected pigs. Additionally, the in vitro stimulation of a PAM cell line with PolyI:C for 12 and 24 h resulted in increased LMP2, LMP7, and MECL-1 expression. These results suggest a central role for these complexes in the activation of an antiviral immune response in pigs. A better understanding of the role of the i-proteasome in different cell types, tissues, and hosts could improve vaccine design and facilitate the development of effective treatment strategies for viral infections.
Performance Tradeoffs of Spectrum Sensing and Target State Estimation and Fusion
We consider a scenario where a cognitive radio sensor performs spectrum sensing and target tracking alternately. Both tasks may impose certain performance guarantee requirements that necessitate considerations of how to schedule these tasks over time. In addition, multiple such cognitive radio sensors can perform collaborative spectrum sensing and target tracking, where a fusion center serves to collect the sensor estimates and their covariances to generate fused target state estimates. We study the performance tradeoffs of these two tasks from variable scheduling intervals. The effect of sensing errors on the target tracking performance due to induced loss from perceived channel unavailability is investigated and conclusions are drawn based on the observed performance tradeoffs.
Dosimetric Evaluation of Incorporating Patient Geometric Variations Into Adaptive Plan Optimization Through Probabilistic Treatment Planning in Head and Neck Cancers
Four-dimensional (4D) adaptive radiation therapy (ART) treatment planning is an alternative to the conventional margin-based treatment planning approach. In 4D ART, interfraction patient geometric variations, gathered from computed tomography (CT) or cone beam CT (CBCT) images acquired during the patient treatment course, are directly incorporated into the adaptive plan optimization using a probabilistic treatment planning method. The goal of the present planning study was to evaluate the dosimetric differences between 4D ART and conventional margin-based adaptive planning strategies for head and neck cancers. In addition, we examined whether the dose differences achieved with 4D ART would translate into clinically relevant toxicity reductions using the existing normal tissue complication probability (NTCP) models.
Performance of State Estimation and Fusion with Elliptical Motion Constraints
We consider tracking of a target with known elliptical nonlinear constraints on its motion dynamics. The state estimates are generated by sensors and sent over long-haul links to a remote fusion center for fusion. We show that the constraints can be projected onto the ellipse and hence incorporated into the estimation and fusion process. In particular, two methods based on (i) direct connection to the center, and (ii) shortest distance to the ellipse are discussed. A tracking example is used to illustrate the tracking performance using projection-based methods with various fusers in a lossy long-haul tracking environment.
On Effect of Information Loss on Fuser Quality and Utility
We abstract the accuracy performance of any fuser into a fusion quality measure that is within the range [0; 1] and monotonically decreases with increasing errors. Although there are many possible ways to map the actual error to this quality measure, we adopt a mapping function consisting of both concave and convex regions and its parameters can be tuned based on system design requirements. The effect of communication loss over the links from the sensors, where estimates are generated, to the fuser is then considered, and based on the variations of the quality measure with loss, we define the overall fuser utility that characterizes the resilience of a fuser with increasingly adverse communication constraints. Tracking examples are shown to demonstrate the comparative quality and utility performances of several closed-form fusers.
Regression-Based Analytics for Response Dynamics of SDN Solutions and Components
We consider Software-Defined Network (SDN) solutions that dynamically setup and teardown connections, and also their response dynamics of connectivity and TCP throughput. There is a wide variety of choices for controllers, switches, andsoftware modules, and objective analytics of measurements are needed to compare the response dynamics of solutions based on their combinations. Throughput and ping measurements during connection changes contain significant statistical variations due to the complexities of controllers, northbound scripts, and network devices. We propose analytical methods to estimate response regression functions, which provide a rigorous and objective comparison of different SDN solutions and their components, namely, controllers, switches, and OpenFlow versions. We apply this approach in two scenarios: (a) switching of long-haul connections emulated in hardware by ANUE devices over a testbed consisting of HP and Cisco switches, and (b) multi-site science infrastructure emulated using VMs and Mininet. The results provide useful practical insights including: (i) the dpctl method responds seconds faster than the OpenDayLight (ODL) method on average under OpenFlow 1.0, but performs similar to ODL under OpenFlow 1.3, and (ii) the ping response of dpctl is about 0.6 sec faster than ODL for the second scenario.
Evaluation of Delamination of X80 Pipeline Steel Coating Under Alternating Stray Current Via Scanning Electrochemical Microscopy
The delamination of epoxy coating on X80 pipeline steel was evaluated under various stray alternating current (AC) interferences (0-300 A/m{sup 2}). Qualitative and quantitative analyses were carried out using scanning electrochemical microscopy (SECM), electrochemical impedance spectroscopy (EIS), and three-dimensional digital microscopy. The results show that the SECM current is directly proportional to the soaking time and applied current density. The variation in SECM current curve shape indicates the delamination distance of epoxy coatings at the defect area. The depths of corrosion pits at 50, 100, and 300 A/m{sup 2} stray currents were 140, 160, and 240 μm, respectively. The corrosion pits also became wider with increasing current densities. With increasing stray AC densities, both the coating delamination and pit depth became more severe at the same soaking time. The EIS results show that the change in impedance was not significant without stray current, whereas the impedance first decreased and then increased when stray current was applied. These results are consistent with the SECM measurements.
Virtual Environment for Testing Software-Defined Networking Solutions for Scientific Workflows
Recent developments in software-defined infrastructures promise that scientific workflows utilizing supercomputers, instruments, and storage systems will be dynamically composed and orchestrated using software at unprecedented speed and scale in the near future. Testing of the underlying networking software, particularly during initial exploratory stages, remains a challenge due to potential disruptions, and resource allocation and coordination needed over the multi-domain physical infrastructure. To overcome these challenges, we develop the Virtual Science Network Environment (VSNE) that emulates the multi-site host, storage, and network infrastructure using Virtual Machines (VMs), wherein the production and nascent software can be tested. Within each VM, which represents a site, the hosts and local-area networks are emulated using Mininet, and the Software-Defined Network (SDN) controllers and service daemon codes are natively run to support dynamic provisioning of network connections. Additionally, Lustre filesystem support at the sites and an emulation of the long-haul network using Mininet, are provided using separate VMs. As case studies, we describe Lustre file transfers using XDD, Red5 streaming service demonstration, and an emulated experiment with remote monitoring and steering modules, all supported over dynamically configured connections using SDN controllers.
On Concavity and Utilization Analytics of Wide-Area Network Transport Protocols
Wide-area data transfers in high-performance computing infrastructures and big data applications are increasingly carried over dynamically provisioned dedicated network connections, which provide high capacities with no competing traffic. Throughput of TCP and UDT over wide-area connections depends, often in a complex non-linear way, on the congestion control mechanism, buffer sizes, and the number of parallel streams. In addition, our extensive TCP and UDT throughput measurements and time traces over a suite of physical and emulated 10 Gbps connections with 0-366 ms round-trip times (RTTs) show significant statistical and temporal variations. Consequently, parameter selection and optimization for transport methods require data analytics to complement analytical throughput models. We present analytics based on the concavity-convexity of throughput profiles which provide insights into peak throughput and superior/inferior trend compared to linear interpolations based on RTT. In particular, we propose the utilization-concavity coefficient, a scalar metric that incorporates both utilization and concavity profile to characterize the overall performance of a transport protocol. These measurements-based anaytics enable us to select a transport protocol and its parameters for a given host and connection configuration to achieve high throughput with statistical guarantees.
Projection-Based Constrained Fusion Performance with Link Loss and Measurement Bias
Sensor networks have been deployed in many real-world applications for tracking and monitoring of dynamic targets over large geographical areas. We consider a scenario where a number of ground and/or airborne sensors are used to jointly track a ground target with certain constraints on its motion dynamics, such as those defined by roadways. The state estimates from these sensors are sent over a lossy communications network to a remote fusion center for fusion. We propose both centralized and distributed projection-based methods to incorporate known constraints into the estimation and fusion process. In addition to presenting simple closed-form projected fusion solutions, we also show how to utilize knowledge of the constraints into the fusion process by two distance-based weighting methods. Wealso explore the effect of link loss and sensor measurement bias on tracking accuracy performance of constrained fusion using illustrative tracking examples. Performance evaluation results demonstrate the potential of adopting weighted average fusers in improving the overall tracking performance in the presenceof link loss and measurement bias.
Software-Defined Network Solutions for Science Scenarios: Performance Testing Framework and Measurements
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Scheduling of Collaborative Sequential Compressed Sensing Over Wide Spectrum Band
The cognitive radio (CR) technology holds promise to significantly increase spectrum availability and wireless network capacity. With more spectrum bands opened up for CR use, it is critical yet challenging to perform efficient wideband sensing. In this work, we propose an integrated sequential wideband sensing scheduling framework that concurrently exploits sequential detection and compressed sensing (CS) techniques for more accurate and lower-cost spectrum sensing. First, to ensure more timely detection without incurring high overhead involved in periodic recovery of CS signals, we propose smart scheduling of a CS-based sequential wideband detection scheme to effectively detect the PU activities in the wideband of interest. Second, to further help users under severe channel conditions identify the occupied sub-channels, we develop two collaborative strategies, namely, joint reconstruction of the signals among neighboring users and wideband sensing-map fusion. Third, to achieve robust wideband sensing, we propose the use of anomaly detection in our framework. Lastly, extensive simulations demonstrate that our approach outperforms peer schemes significantly in terms of sensing delay, accuracy and overhead.
On Data Transfers Over Wide-Area Dedicated Connections
Dedicated wide-area network connections are employed in big data and high-performance computing scenarios, since the absence of cross-traffic promises to make it easier to analyze and optimize data transfers over them. However, nonlinear transport dynamics and end-system complexity due to multi-core hosts and distributed file systems make these tasks surprisingly challenging. We present an overview of methods to analyze memory and disk file transfers using extensive measurements over 10 Gbps physical and emulated connections with 0–366 ms round trip times (RTTs). For memory transfers, we derive performance profiles of TCP and UDT throughput as a function of RTT, which show concave regions in contrast to entirely convex regions predicted by previous models. These highly desirable concave regions can be expanded by utilizing large buffers and more parallel flows. We also present Poincar´e maps and Lyapunov exponents of TCP and UDT throughputtraces that indicate complex throughput dynamics. For disk file transfers, we show that throughput can be optimized using a combination of parallel I/O and network threads under direct I/O mode. Our initial throughput measurements of Lustre filesystems mounted over long-haul connections using LNet routers show convex profiles indicative of I/O limits.
So ware-Defined Network Solutions for Science Scenarios: Performance Testing Framework and Measurements
High-performance scientific work flows utilize supercomputers, scientific instruments, and large storage systems. Their executions require fast setup of a small number of dedicated network connections across the geographically distributed facility sites. We present Software-Defined Network (SDN) solutions consisting of site daemons that use dpctl, Floodlight, ONOS, or OpenDaylight controllers to set up these connections. The development of these SDN solutions could be quite disruptive to the infrastructure, while requiring a close coordination among multiple sites; in addition, the large number of possible controller and device combinations to investigate could make the infrastructure unavailable to regular users for extended periods of time. In response, we develop a Virtual Science Network Environment (VSNE) using virtual machines, Mininet, and custom scripts that support the development, testing, and evaluation of SDN solutions, without the constraints and expenses of multi-site physical infrastructures; furthermore, the chosen solutions can be directly transferred to production deployments. By complementing VSNE with a physical testbed, we conduct targeted performance tests of various SDN solutions to help choose the best candidates. In addition, we propose a switching response method to assess the setup times and throughput performances of different SDN solutions, and present experimental results that show their advantages and limitations.