Engineering Commons^™

Metaflow: A Scalable Metadata Lookup Service For Distributed File Systems In Data Centers, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Haiyong Xie

Research Collection School Of Computing and Information Systems

In large-scale distributed file systems, efficient metadata operations are critical since most file operations have to interact with metadata servers first. In existing distributed hash table (DHT) based metadata management systems, the lookup service could be a performance bottleneck due to its significant CPU overhead. Our investigations showed that the lookup service could reduce system throughput by up to 70%, and increase system latency by a factor of up to 8 compared to ideal scenarios. In this paper, we present MetaFlow, a scalable metadata lookup service utilizing software-defined networking (SDN) techniques to distribute lookup workload over network components. MetaFlow tackles …

Data Analytics And Application Developments Based On Synchrophasor Measurements, Jiahui Guo

Doctoral Dissertations

Frequency Monitoring Network (FNET) is an Internet‐based, wide‐area phasor measurement system that collects power system data using Frequency Disturbance Recorders (FDRs) that are installed at the distribution level. These synchrophasor measurements enable the monitoring of bulk power systems, and provides wide‐area situational awareness and disturbance analysis for understanding power system disturbances and system operations. Various data analytics and applications are built based on these valuable measurements.

Real-time situational awareness tools are of critical importance to power system operators. Knowledge of the scope and extent of facilities impacted, as well as the duration of their dependence on backup power, enables emergency …

Energy Consumption Prediction With Big Data: Balancing Prediction Accuracy And Computational Resources, Katarina Grolinger, Miriam Am Capretz, Luke Seewald

Electrical and Computer Engineering Publications

In recent years, advances in sensor technologies and expansion of smart meters have resulted in massive growth of energy data sets. These Big Data have created new opportunities for energy prediction, but at the same time, they impose new challenges for traditional technologies. On the other hand, new approaches for handling and processing these Big Data have emerged, such as MapReduce, Spark, Storm, and Oxdata H2O. This paper explores how findings from machine learning with Big Data can benefit energy consumption prediction. An approach based on local learning with support vector regression (SVR) is presented. Although local learning itself is …

Cepsim: Modelling And Simulation Of Complex Event Processing Systems In Cloud Environments, Wilson A. Higashino, Miriam Am Capretz, Luiz F. Bittencourt

Electrical and Computer Engineering Publications

The emergence of Big Data has had profound impacts on how data are stored and processed. As technologies created to process continuous streams of data with low latency, Complex Event Processing (CEP) and Stream Processing (SP) have often been related to the Big Data velocity dimension and used in this context. Many modern CEP and SP systems leverage cloud environments to provide the low latency and scalability required by Big Data applications, yet validating these systems at the required scale is a research problem per se. Cloud computing simulators have been used as a tool to facilitate reproducible and repeatable …

Application Of Secondary Analyses On Industrial Data Sets, Luis G. Perez

Open Access Theses & Dissertations

Secondary analysis on quantitative data sets is the in-depth analysis of relationships, trends, patterns or behaviors that are not obvious from a superficial examination of data but that can be very germane in the application of that data. The present work presents a framework for investigators to use in applying secondary analysis on big data that correlates to the research topic. The framework can facilitate the illumination of possible data behaviors or patterns that could be useful in arriving at an answer to a question. Behavior of monitored equipment (analyzers, meters, etc.) can easily be depicted and can be used …

A Data Driven Approach To Quantify The Impact Of Crashes, Obaidur Rahman Kazi

Theses and Dissertations--Civil Engineering

The growth of data has begun to transform the transportation research and policy, and open a new window for analyzing the impact of crashes. Currently for the crash impact analysis, researchers tend to rely on reported incident duration, which may not always be accurate. Further, impact of the crashes could linger a much longer time at upstream, even if the records are correct for the crash spot and it is a challenge to quantify the impact of a crash from the complex dynamics of the recurrent and non-recurrent congested condition. Therefore, a difference-in-speed approach is developed in this research to …