Application of overlay techniques to network monitoring

Measurement and monitoring are important for correct and efficient operation of a network, since these activities provide reliable information and accurate analysis for characterizing and troubleshooting a network’s performance. The focus of network measurement is to measure the volume and types of traffic on a particular network and to record the raw measurement results. The focus of network monitoring is to initiate measurement tasks, collect raw measurement results, and report aggregated outcomes. Network systems are continuously evolving: besides incremental change to accommodate new devices, more drastic changes occur to accommodate new applications, such as overlay-based content delivery networks. As a consequence, a network can experience significant increases in size and significant levels of long-range, coordinated, distributed activity; furthermore, heterogeneous network technologies, services and applications coexist and interact. Reliance upon traditional, point-to-point, ad hoc measurements to manage such networks is becoming increasingly tenuous. In particular, correlated, simultaneous 1-way measurements are needed, as is the ability to access measurement information stored throughout the network of interest. To address these new challenges, this dissertation proposes OverMon, a new paradigm for edge-to-edge network monitoring systems through the application of overlay techniques. Of particular interest, the problem of significant network overheads caused by normal overlay network techniques has been addressed by constructing overlay networks with topology awareness - the network topology information is derived from interior gateway protocol (IGP) traffic, i.e. OSPF traffic, thus eliminating all overlay maintenance network overhead. Through a prototype that uses overlays to initiate measurement tasks and to retrieve measurement results, systematic evaluation has been conducted to demonstrate the feasibility and functionality of OverMon. The measurement results show that OverMon achieves good performance in scalability, flexibility and extensibility, which are important in addressing the new challenges arising from network system evolution. This work, therefore, contributes an innovative approach of applying overly techniques to solve realistic network monitoring problems, and provides valuable first hand experience in building and evaluating such a distributed system

Detection and attribution of nitrogen runoff trend in China's croplands

Reliable detection and attribution of changes in nitrogen (N) runoff from croplands are essential for designing efficient, sustainable N management strategies for future. Despite the recognition that excess N runoff poses a risk of aquatic eutrophication, large-scale, spatially detailed N runoff trends and their drivers remain poorly understood in China. Based on data comprising 535 site-years from 100 sites across China's croplands, we developed a data-driven upscaling model and a new simplified attribution approach to detect and attribute N runoff trends during the period of 1990–2012. Our results show that N runoff has increased by 46% for rice paddy fields and 31% for upland areas since 1990. However, we acknowledge that the upscaling model is subject to large uncertainties (20% and 40% as coefficient of variation of N runoff, respectively). At national scale, increased fertilizer application was identified as the most likely driver of the N runoff trend, while decreased irrigation levels offset to some extent the impact of fertilization increases. In southern China, the increasing trend of upland N runoff can be attributed to the growth in N runoff rates. Our results suggested that increased SOM led to the N runoff rate growth for uplands, but led to a decline for rice paddy fields. In combination, these results imply that improving management approaches for both N fertilizer use and irrigation is urgently required for mitigating agricultural N runoff in China

Analysis of service performance characteristics of debris flow check dams: A case study in Wudu District, Longnan City, Gansu Province

Check dams play a pivotal role in debris flow prevention and control engineering. However, their disaster prevention and mitigation capacity gradually decrease over service time due to repeated debris flow impacts. The study was carried out in 15 ditches and 55 check dams within Wudu District, Longnan City, Gansu Province. Seven key evaluation factors were selected for effectiveness and safety: reservoir siltation ratio, slope stability, drainage hole blockage, dam body damage, dam foundation damage, dam shoulder damage, and safety. The evaluation model of the serviceability of the indivusual dam and the comprehensive serviceability of the single trench of the barrage was established by using hierarchical analysis and fuzzy comprehensive evaluation method, and the serviceability was divided into four grades: excellent, good, medium and poor. The evaluation results show that the serviceability rating of individual dams is predominately "poor", accounting for 34.5%. Similarly, the collective serviceability rating of single trench dams for debris flow is predominately "poor", at 33.3%. The results of the evaluation are consistent with the fieldwork observations, providing a valuable reference for predicting the service performance and service life of barrage dams

Application of upscaling methods for fluid flow and mass transport in multi-scale heterogeneous media : A critical review

Physical and biogeochemical heterogeneity dramatically impacts fluid flow and reactive solute transport behaviors in geological formations across scales. From micro pores to regional reservoirs, upscaling has been proven to be a valid approach to estimate large-scale parameters by using data measured at small scales. Upscaling has considerable practical importance in oil and gas production, energy storage, carbon geologic sequestration, contamination remediation, and nuclear waste disposal. This review covers, in a comprehensive manner, the upscaling approaches available in the literature and their applications on various processes, such as advection, dispersion, matrix diffusion, sorption, and chemical reactions. We enclose newly developed approaches and distinguish two main categories of upscaling methodologies, deterministic and stochastic. Volume averaging, one of the deterministic methods, has the advantage of upscaling different kinds of parameters and wide applications by requiring only a few assumptions with improved formulations. Stochastic analytical methods have been extensively developed but have limited impacts in practice due to their requirement for global statistical assumptions. With rapid improvements in computing power, numerical solutions have become more popular for upscaling. In order to tackle complex fluid flow and transport problems, the working principles and limitations of these methods are emphasized. Still, a large gap exists between the approach algorithms and real-world applications. To bridge the gap, an integrated upscaling framework is needed to incorporate in the current upscaling algorithms, uncertainty quantification techniques, data sciences, and artificial intelligence to acquire laboratory and field-scale measurements and validate the upscaled models and parameters with multi-scale observations in future geo-energy research.© 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)This work was jointly supported by the National Key Research and Development Program of China (No. 2018YFC1800900 ), National Natural Science Foundation of China (No: 41972249 , 41772253 , 51774136 ), the Program for Jilin University (JLU) Science and Technology Innovative Research Team (No. 2019TD-35 ), Graduate Innovation Fund of Jilin University (No: 101832020CX240 ), Natural Science Foundation of Hebei Province of China ( D2017508099 ), and the Program of Education Department of Hebei Province ( QN219320 ). Additional funding was provided by the Engineering Research Center of Geothermal Resources Development Technology and Equipment , Ministry of Education, China.fi=vertaisarvioitu|en=peerReviewed

Phosphorus adsorption and desorption characteristics and its response to soil properties of black soil under long-term different fertilization

editorial reviewedObjective: Fertilizer is generally added to agricultural soil to meet the needs of crop production, but long-term over fertilization changes soil phosphorus (P) pool and soil properties. This study evaluated the characteristics change of P adsorption and desorption and its response to soil properties under long-term fertilization, to do a favor to provide theoretical basis of rational fertilizer application and improve the P availability of black soil. Method: Four treatments, including no fertilizer (CK), urea and potash sulphate (NK), urea, super-calcium phosphate and potash sulphate (NPK), and NPK plus pig manure (NPKM), were investigated in a 21-year (1989-2010) long-term fertilization experiment at Gongzhuling (Jilin Province) of China. The crop of cropping system was maize. Soil samples were collected in 1990, 2000 and 2010 at 0-20 cm depth to analyze soil properties and to measure soil P adsorption and desorption characteristics. Langmuir equation was used to fit the P adsorption curve, and then the maximum adsorption capacity (Qmax), adsorption constant (K), buffering capacity of soil P (MBC), and P sorption saturation (DPS) were calculated according to Langmuir equation. Result: There was a good fitness between the P adsorption curve and Langmuir equation (R2=0.93-0.99, P<0.01). There existed difference for P adsorption and desorption characteristic under the four treatments. Over time, compared with initial year, for CK and NK treatments, the Qmax value increased by 1.83 and 1.61 times, MBC value increased by 0.80% and 49.40%, DPS value decreased by 92.04% and 87.50%, Readily Desorbable Phosphorus (RDP) value decreased by 20.00% and 82.83%, respectively; for NPK treatment, Qmax and DPS value increased by 81.87% and 79.56%, MBC and RDP value decreased by 79.37% and 48.57%, respectively, while under NPKM treatment, the Qmax and MBC value decreased by 33.35% and 78.52%, DPS and RDP values increased by 11.36 and 1.48 times, respectively. After 21 years experiments, compared with CK and NPK treatments, the Qmax and MBC value of NPKM treatment decreased by 64.66% and 49.52%, 81.87% and 79.56%, respectively; the DPS and RDP value of NPKM treatment increased by 110 and 3.81 times, 4.36 times and 78.57%, respectively. Compared with other treatments, the Total-P, Olsen-P, soil organic matter (SOM) and CaCO3 contents increased and SSA decreased significantly, but the pH, free Fe2O3 and Al2O3 value kept unchanged under NPKM treatment. RDA test showed that SOM and Total-P were the main factors that explained 49.5% and 18.7% of the total variation (P<0.05) which caused the difference of P adsorption desorption characteristic parameters among four treatments. Conclusion: Long-term combination of NPK fertilizers with manures could significantly increase SOM and P accumulation contents, decrease the soil adsorption capacity and increase desorption capacity, and improve P availability in soil, but it significantly increased the DPS value, easily thereby caused the risk of phosphorus loss. Therefore, various management practices and inorganic and organic P fertilizer input amounts should be considered to reduce P losses from this area

Acoustic scale from the angular power spectra of SDSS-III DR8 photometric luminous galaxies

We measure the acoustic scale from the angular power spectra of the Sloan Digital Sky Survey III (SDSS-III) Data Release 8 imaging catalog that includes 872,921 galaxies over ~ 10,000 deg^2 between 0.45<z<0.65. The extensive spectroscopic training set of the Baryon Oscillation Spectroscopic Survey (BOSS) luminous galaxies allows precise estimates of the true redshift distributions of galaxies in our imaging catalog. Utilizing the redshift distribution information, we build templates and fit to the power spectra of the data, which are measured in our companion paper, Ho et al. 2011, to derive the location of Baryon acoustic oscillations (BAO) while marginalizing over many free parameters to exclude nearly all of the non-BAO signal. We derive the ratio of the angular diameter distance to the sound horizon scale D_A/r_s= 9.212 + 0.416 -0.404 at z=0.54, and therefore, D_A= 1411+- 65 Mpc at z=0.54; the result is fairly independent of assumptions on the underlying cosmology. Our measurement of angular diameter distance D_A is 1.4 \sigma higher than what is expected for the concordance LCDM (Komatsu et al. 2011), in accordance to the trend of other spectroscopic BAO measurements for z >~ 0.35. We report constraints on cosmological parameters from our measurement in combination with the WMAP7 data and the previous spectroscopic BAO measurements of SDSS (Percival et al. 2010) and WiggleZ (Blake et al. 2011). We refer to our companion papers (Ho et al. 2011; de Putter et al. 2011) for investigations on information of the full power spectrum.Comment: 16 pages, 14 figures, 3 tables, submitted to Ap

Cycle-based trading & portfolio management system

This research project aims to apply machine learning techniques in the area of financial investment. By adopting data-driven objective methods, some common human biases known to prevent investors from making rational decisions could be reasonably avoided. The strategy is built upon cyclical movements in the stock market, which is mainly induced by business cycles. Thus, the target horizon is mid to long term. By selecting stocks at their troughs and investing capitals during the rising phases, capitals could be utilized more efficiently to preserve values and generate returns. To predict the inflection points in stock prices, Takagi-Sugeno-Kang fuzzy neural network is adopted due to its accuracy. To improve its performance, Evolutionary Algorithms (EA) are applied to fine tune the model’s parameters. In addition, angular coding scheme is used to conquer the problem of limited search space associated with the designing of TSK Fuzzy Rule-Based System with EAs. After the longer term inflection signal is given, entry/exit points are confirmed by shorter-term signals such as MACD, which reflects more recent market changes. Maximum reward reinforcement learning is also incorporated to estimate the potential rising amplitude in order to avoid entering into unprofitable trades while taking into account transaction costs. The cycle-based stock selection approach is combined into the design of a portfolio management system based on Markowitz Portfolio Theory. The system constructs portfolios with the objective of maximizing return while maintaining overall risk at a predefined target level. Rebalancing is scheduled according to the Larry Swedroe 5/25 rules, which enables prompt response to significant market changes. The proposed cycled-based strategy achieves average annual return of around 14%. Compared to the benchmark (S&P) annual return of 9% during the same back-test period, the system makes a significant improvement.Bachelor of Engineering (Computer Science