Matching Items (6)

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Tenga: A Case Study on Building Web Applications

Description

Tenga is an e-commerce demo web application for students studying Distributed Software Development and Software Integration and Engineering at Arizona State University (ASU). The application, written in C#, aims to

Tenga is an e-commerce demo web application for students studying Distributed Software Development and Software Integration and Engineering at Arizona State University (ASU). The application, written in C#, aims to empower students to understand how complex systems are build. Complementing the two courses taught at ASU, it seeks to demonstrate how the concepts taught in the two classes can be applied to the real world. In addition to the practical software development process, Tenga also bring in the topics that students are inexperienced with such as recommendation systems and ranking algorithms. Tenga is going to be used in classrooms to help students to learn fundamental issues in Web software development and software integration and to understand tools and skill sets required to built a web application.

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Created

Date Created
  • 2016-05

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GeoSparkSim: A Scalable Microscopic Road Network Traffic Simulator Based on Apache Spark

Description

Researchers and practitioners have widely studied road network traffic data in different areas such as urban planning, traffic prediction and spatial-temporal databases. For instance, researchers use such data to evaluate

Researchers and practitioners have widely studied road network traffic data in different areas such as urban planning, traffic prediction and spatial-temporal databases. For instance, researchers use such data to evaluate the impact of road network changes. Unfortunately, collecting large-scale high-quality urban traffic data requires tremendous efforts because participating vehicles must install Global Positioning System(GPS) receivers and administrators must continuously monitor these devices. There have been some urban traffic simulators trying to generate such data with different features. However, they suffer from two critical issues (1) Scalability: most of them only offer single-machine solution which is not adequate to produce large-scale data. Some simulators can generate traffic in parallel but do not well balance the load among machines in a cluster. (2) Granularity: many simulators do not consider microscopic traffic situations including traffic lights, lane changing, car following. This paper proposed GeoSparkSim, a scalable traffic simulator which extends Apache Spark to generate large-scale road network traffic datasets with microscopic traffic simulation. The proposed system seamlessly integrates with a Spark-based spatial data management system, GeoSpark, to deliver a holistic approach that allows data scientists to simulate, analyze and visualize large-scale urban traffic data. To implement microscopic traffic models, GeoSparkSim employs a simulation-aware vehicle partitioning method to partition vehicles among different machines such that each machine has a balanced workload. The experimental analysis shows that GeoSparkSim can simulate the movements of 200 thousand cars over an extensive road network (250 thousand road junctions and 300 thousand road segments).

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Created

Date Created
  • 2019

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Performance and scaling analysis of a hypocycloid wiseman engine

Description

The slider-crank mechanism is popularly used in internal combustion engines to convert the reciprocating motion of the piston into a rotary motion. This research discusses an alternate mechanism proposed by

The slider-crank mechanism is popularly used in internal combustion engines to convert the reciprocating motion of the piston into a rotary motion. This research discusses an alternate mechanism proposed by the Wiseman Technology Inc. which involves replacing the crankshaft with a hypocycloid gear assembly. The unique hypocycloid gear arrangement allows the piston and the connecting rod to move in a straight line, creating a perfect sinusoidal motion. To analyze the performance advantages of the Wiseman mechanism, engine simulation software was used. The Wiseman engine with the hypocycloid piston motion was modeled in the software and the engine's simulated output results were compared to those with a conventional engine of the same size. The software was also used to analyze the multi-fuel capabilities of the Wiseman engine using a contra piston. The engine's performance was studied while operating on diesel, ethanol and gasoline fuel. Further, a scaling analysis on the future Wiseman engine prototypes was carried out to understand how the performance of the engine is affected by increasing the output power and cylinder displacement. It was found that the existing Wiseman engine produced about 7% less power at peak speeds compared to the slider-crank engine of the same size. It also produced lower torque and was about 6% less fuel efficient than the slider-crank engine. These results were concurrent with the dynamometer tests performed in the past. The 4 stroke diesel variant of the same Wiseman engine performed better than the 2 stroke gasoline version as well as the slider-crank engine in all aspects. The Wiseman engine using contra piston showed poor fuel efficiency while operating on E85 fuel. But it produced higher torque and about 1.4% more power than while running on gasoline. While analyzing the effects of the engine size on the Wiseman prototypes, it was found that the engines performed better in terms of power, torque, fuel efficiency and cylinder BMEP as their displacements increased. The 30 horsepower (HP) prototype, while operating on E85, produced the most optimum results in all aspects and the diesel variant of the same engine proved to be the most fuel efficient.

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Created

Date Created
  • 2014

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Scalable register file architecture for CGRA accelerators

Description

Coarse-grained Reconfigurable Arrays (CGRAs) are promising accelerators capable

of accelerating even non-parallel loops and loops with low trip-counts. One challenge

in compiling for CGRAs is to manage both recurring and nonrecurring variables

Coarse-grained Reconfigurable Arrays (CGRAs) are promising accelerators capable

of accelerating even non-parallel loops and loops with low trip-counts. One challenge

in compiling for CGRAs is to manage both recurring and nonrecurring variables in

the register file (RF) of the CGRA. Although prior works have managed recurring

variables via rotating RF, they access the nonrecurring variables through either a

global RF or from a constant memory. The former does not scale well, and the latter

degrades the mapping quality. This work proposes a hardware-software codesign

approach in order to manage all the variables in a local nonrotating RF. Hardware

provides modulo addition based indexing mechanism to enable correct addressing

of recurring variables in a nonrotating RF. The compiler determines the number of

registers required for each recurring variable and configures the boundary between the

registers used for recurring and nonrecurring variables. The compiler also pre-loads

the read-only variables and constants into the local registers in the prologue of the

schedule. Synthesis and place-and-route results of the previous and the proposed RF

design show that proposed solution achieves 17% better cycle time. Experiments of

mapping several important and performance-critical loops collected from MiBench

show proposed approach improves performance (through better mapping) by 18%,

compared to using constant memory.

Contributors

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Created

Date Created
  • 2016

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Analysis and Management of Security State for Large-Scale Data Center Networks

Description

With the increasing complexity of computing systems and the rise in the number of risks and vulnerabilities, it is necessary to provide a scalable security situation awareness tool to assist

With the increasing complexity of computing systems and the rise in the number of risks and vulnerabilities, it is necessary to provide a scalable security situation awareness tool to assist the system administrator in protecting the critical assets, as well as managing the security state of the system. There are many methods to provide security states' analysis and management. For instance, by using a Firewall to manage the security state, and/or a graphical analysis tools such as attack graphs for analysis.

Attack Graphs are powerful graphical security analysis tools as they provide a visual representation of all possible attack scenarios that an attacker may take to exploit system vulnerabilities. The attack graph's scalability, however, is a major concern for enumerating all possible attack scenarios as it is considered an NP-complete problem. There have been many research work trying to come up with a scalable solution for the attack graph. Nevertheless, non-practical attack graph based solutions have been used in practice for realtime security analysis.

In this thesis, a new framework, namely 3S (Scalable Security Sates) analysis framework is proposed, which present a new approach of utilizing Software-Defined Networking (SDN)-based distributed firewall capabilities and the concept of stateful data plane to construct scalable attack graphs in near-realtime, which is a practical approach to use attack graph for realtime security decisions. The goal of the proposed work is to control reachability information between different datacenter segments to reduce the dependencies among vulnerabilities and restrict the attack graph analysis in a relative small scope. The proposed framework is based on SDN's programmable capabilities to adjust the distributed firewall policies dynamically according to security situations during the running time. It apply white-list-based security policies to limit the attacker's capability from moving or exploiting different segments by only allowing uni-directional vulnerability dependency links between segments. Specifically, several test cases will be presented with various attack scenarios and analyze how distributed firewall and stateful SDN data plan can significantly reduce the security states construction and analysis. The proposed approach proved to achieve a percentage of improvement over 61% in comparison with prior modules were SDN and distributed firewall are not in use.

Contributors

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Created

Date Created
  • 2018

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Tile-based methods for online choropleth mapping: a scalability evaluation

Description

Choropleth maps are a common form of online cartographic visualization. They reveal patterns in spatial distributions of a variable by associating colors with data values measured at areal units. Although

Choropleth maps are a common form of online cartographic visualization. They reveal patterns in spatial distributions of a variable by associating colors with data values measured at areal units. Although this capability of pattern revelation has popularized the use of choropleth maps, existing methods for their online delivery are limited in supporting dynamic map generation from large areal data. This limitation has become increasingly problematic in online choropleth mapping as access to small area statistics, such as high-resolution census data and real-time aggregates of geospatial data streams, has never been easier due to advances in geospatial web technologies. The current literature shows that the challenge of large areal data can be mitigated through tiled maps where pre-processed map data are hierarchically partitioned into tiny rectangular images or map chunks for efficient data transmission. Various approaches have emerged lately to enable this tile-based choropleth mapping, yet little empirical evidence exists on their ability to handle spatial data with large numbers of areal units, thus complicating technical decision making in the development of online choropleth mapping applications. To fill this knowledge gap, this dissertation study conducts a scalability evaluation of three tile-based methods discussed in the literature: raster, scalable vector graphics (SVG), and HTML5 Canvas. For the evaluation, the study develops two test applications, generates map tiles from five different boundaries of the United States, and measures the response times of the applications under multiple test operations. While specific to the experimental setups of the study, the evaluation results show that the raster method scales better across various types of user interaction than the other methods. Empirical evidence also points to the superior scalability of Canvas to SVG in dynamic rendering of vector tiles, but not necessarily for partial updates of the tiles. These findings indicate that the raster method is better suited for dynamic choropleth rendering from large areal data, while Canvas would be more suitable than SVG when such rendering frequently involves complete updates of vector shapes.

Contributors

Agent

Created

Date Created
  • 2013