Cache Affinity-aware In-memory Caching Management for Hadoop

Department of Computer Science and EngineeringIn this paper, we investigate techniques to effectively manage HDFS in-memory caching for Hadoop. We first revisit the current implementation of Hadoop with HDFS in-memory caching to understand its limitation on the effective usage of in-memory caching. For various representative MapReduce applications, we also evaluate a degree of benefit each application can get from in-memory caching, i.e. cache affinity. We then propose an adaptive cache local scheduling algorithm that adaptively computes how long a MapReduce job waits to be scheduled on a cache local node to be proportional to the percentage of cached input data for the job. In addition, we propose a block goodness aware cache replacement algorithm that determines which block is cached and evicted based on the accessed rate and the cache affinity of applications. Using various workloads consisting of multiple MapReduce applications, we conduct extensive experimental study to demonstrate the effects of the proposed in-memory orchestration techniques. Our experimental results show that our enhanced Hadoop in-memory caching scheme improves the performance of the MapReduce workloads.ope

Hydrological Drought Analysis Based on Copula Theory

Drought has been a more frequent phenomenon of major concern all over the world. From the perspective of water resources management, one of the biggest problems associated with drought analyses is a lack of quantitative estimation for the target drought amount. The objective of this study is to examine the establishing process for the severity-duration-frequency (hereafter referred as “SDF”) curves on climate change. The standardized truncation level that defines hydrological drought was estimated and a bivariate frequency analysis for drought duration and severity was derived. The SDF curves were also estimated. The methodology suggested in this study could be used as elementary data for water resources managements

Assessment of Meteorological Drought in Korea under Climate Change

Drought has become one of the most important elements for water resources planning and management in Korea. The objective of this study is to estimate the spatial distribution of drought and change in the drought characteristics over time due to climate change. For the spatial characterization of drought, the standardized precipitation index (SPI) is calculated from the 45 observatories in Korea and the spatial distribution is also estimated based on the joint probability analysis using the copula method. To analyze the effect of climate change, spatial distribution of drought in the future is analyzed using the SPI time series calculated from Representative Concentration Pathways (RCPs) scenarios and HADGEM3-RA regional climate model. The results show that the Youngsan River and the northwest of Nakdong River basins in Korea have nearly doubled drought amount compared to the present and are most vulnerable to drought in near future (2016 to 2039 years)

Objective Function and Parameter Calibrations of Flood Forecasting Models

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Scrub Typhus Incidence Modeling with Meteorological Factors in South Korea

Since its recurrence in 1986, scrub typhus has been occurring annually and it is considered as one of the most prevalent diseases in Korea. Scrub typhus is a 3rd grade nationally notifiable disease that has greatly increased in Korea since 2000. The objective of this study is to construct a disease incidence model for prediction and quantification of the incidences of scrub typhus. Using data from 2001 to 2010, the incidence Artificial Neural Network (ANN) model, which considers the time-lag between scrub typhus and minimum temperature, precipitation and average wind speed based on the Granger causality and spectral analysis, is constructed and tested for 2011 to 2012. Results show reliable simulation of scrub typhus incidences with selected predictors, and indicate that the seasonality in meteorological data should be considered

5GHz Wideband Channel Model in Apartment Building

This paper reports the empirical 5GHz wideband channel model in apartment building. The channel measurement system is based on the pseudo-noise (PN) correlation method. In measurements, transmitter is fixed at two different positions in a house while receiver moves from the rooms of the house to those of nearby houses in each transmitter position. From measurement results, propagation loss and wideband channel characteristics are analyzed. As a result, we found that the signal reflected to neighboring buildings proffered other clusters. Especially, in cases of the receiver positions where with a big window and large away from the transmitter, this phenomenon is emphasized. And transmitter located at the biased position, could cause the imbalance of received signal level in a single house and the interference to neighboring houses

Bivariate Drought Analysis Using Streamflow Reconstruction with Tree Ring Indices in the Sacramento Basin, California, USA

Long-term streamflow data are vital for analysis of hydrological droughts. Using an artificial neural network (ANN) model and nine tree-ring indices, this study reconstructed the annual streamflow of the Sacramento River for the period from 1560 to 1871. Using the reconstructed streamflow data, the copula method was used for bivariate drought analysis, deriving a hydrological drought return period plot for the Sacramento River basin. Results showed strong correlation among drought characteristics, and the drought with a 20-year return period (17.2 million acre-feet (MAF) per year) in the Sacramento River basin could be considered a critical level of drought for water shortages

Future Climate Data from RCP 4.5 and Occurrence of Malaria in Korea

Since its reappearance at the Military Demarcation Line in 1993, malaria has been occurring annually in Korea. Malaria is regarded as a third grade nationally notifiable disease susceptible to climate change. The objective of this study is to quantify the effect of climatic factors on the occurrence of malaria in Korea and construct a malaria occurrence model for predicting the future trend of malaria under the influence of climate change. Using data from 2001–2011, the effect of time lag between malaria occurrence and mean temperature, relative humidity and total precipitation was investigated using spectral analysis. Also, a principal component regression model was constructed, considering multicollinearity. Future climate data, generated from RCP 4.5 climate change scenario and CNCM3 climate model, was applied to the constructed regression model to simulate future malaria occurrence and analyze the trend of occurrence. Results show an increase in the occurrence of malaria and the shortening of annual time of occurrence in the future

Electrically Robust Single-Crystalline WTe2 Nanobelts for Nanoscale Electrical Interconnects

As the elements of integrated circuits are downsized to the nanoscale, the current Cu-based interconnects are facing limitations due to increased resistivity and decreased current-carrying capacity because of scaling. Here, the bottom-up synthesis of single-crystalline WTe2 nanobelts and low- and high-field electrical characterization of nanoscale interconnect test structures in various ambient conditions are reported. Unlike exfoliated flakes obtained by the top-down approach, the bottom-up growth mode of WTe2 nanobelts allows systemic characterization of the electrical properties of WTe2 single crystals as a function of channel dimensions. Using a 1D heat transport model and a power law, it is determined that the breakdown of WTe2 devices under vacuum and with AlOx capping layer follows an ideal pattern for Joule heating, far from edge scattering. High-field electrical measurements and self-heating modeling demonstrate that the WTe2 nanobelts have a breakdown current density approaching approximate to 100 MA cm(-2), remarkably higher than those of conventional metals and other transition-metal chalcogenides, and sustain the highest electrical power per channel length (approximate to 16.4 W cm(-1)) among the interconnect candidates. The results suggest superior robustness of WTe2 against high-bias sweep and its possible applicability in future nanoelectronics