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Data analysis using hadoop MapReduce environment

Data analysis using hadoop MapReduce environment

引用

IEEE International Conference on Big Data

作者： PrathyushaRani Merla Yiheng Liang Department of Computer Science Bridgewater State University Bridgewater MA USA

This project deals with analysis of YouTube data using Hadoop MapReduce framework on a cloud platform AWS. Hadoop multi node cluster is setup on private cloud called AWS (Amazon Web Services). Within AWS, I have set up EC2 instances with one name node and 5 data nodes. The video statistics obtained from the API is stored into the HDFS (Hadoop distributed File System) and the data processing is done by the MapReduce system.

关键词： YouTube Data analysis File systems Cloud computing Metadata Big Data distributed databases

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Support automation connectivity system for big data applications

Support automation connectivity system for big data applicat...

引用

International Conference on Inventive Computing and Informatics (ICICI)

作者： S. G. Shaila M S M Prasanna L Niveditha A Vadivel Dept. of Computer Science Engineering Dayananda Sagar University Bangalore SRM University Kattankulathur Tamil Nadu IN

ISBN: (纸本)9781538640326

The business information is stored in different source systems. Accessing specific data from different source systems that contain terabytes of information is tedious. The organization's source systems are complex and hence data extraction could be time consuming and labor-intensive. Not all users are allowed to access the production data due to security limitations and performance issues. Business leads will not be able to make the right decisions if the available raw data is not presented in the right context and the performance cannot be monitored. There is a need to automate the data extraction process targeting the different data sources and the need of Business Intelligence to gather and analyze data, transform it to useful form to gain insight to make decisions. The paper proposes, Support Automation Connectivity approach which addresses these issues using SNPN (Serial and Product Number) Data Extraction system and Store Serve Reporting. Support Automation Connectivity is about tracking the information of the connected Enterprise devices. The intelligent software built into the products sends heartbeat at regular intervals. This helps in supporting the device in terms of failures or software version updates, etc. based on the warranty period. The data is maintained in different cubes. SNPN Data Extraction system allows the business user to analyze the attributes related to connected devices for the given SNPN and report date. This system is triggered by the scheduler at regular intervals to pick up the input files for processing. It performs the data extraction within few seconds even for large data and sends instant notification to the relevant individuals. The file and package execution details can be tracked and appropriate error handling is implemented.

关键词： Data mining Business intelligence Task analysis distributed databases Servers Automation

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iDPL: A scalable and flexible inter-continental testbed for data placement research and experiment

iDPL: A scalable and flexible inter-continental testbed for ...

引用

IEEE Symposium on Computers and Communications (ISCC)

作者： Guang Wei Hailong Yang Zhongzhi Luan Depei Qian Sino-German Joint Software Institute Beihang University Beijing China

In this paper, we propose the China-US international data placement laboratory (iDPL) based on an inter-continental testbed for data placement research. iDPL is able to support various data placement research due to its scalability and flexibility in deploying the experiments in the real network environment. The core design of iDPL leverages reliable workflow management and lightweight I/O protocol to allow complex experiment setup and on-the-fly experiment deployment. It is also extensible to plugin different network profiling tools such as iperf. We expect the powerful measurement capability of iDPL promotes research study on the intelligent data placement policies which adapt to the uncertainty of the wide-area network and guarantee the quality of service (QoS) of the big data applications. As a case study, we setup a set of data placement experiments to measure the end-to-end network performance constantly among several sites between China and US using different data placement tools. The experiments have been running for more than one year, and its measurement data is public available (http://***:8080/). We believe the measurement data is valuable for both network and big data researchers to understand the performance disparity between the raw network and the actual data placement, which provides useful insights to design big data applications with performance awareness. We encourage more researchers to deploy their own data placement experiments on iDPL, expediting the research direction of intelligent data placement with real network environment.

关键词： Tools Synchronization Data visualization Protocols distributed databases Computers Software

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Towards a unified storage and ingestion architecture for stream processing

Towards a unified storage and ingestion architecture for str...

引用

IEEE International Conference on Big Data

作者： Ovidiu-Cristian Marcu Alexandru Costan Gabriel Antoniu María S. Pérez-Hernández Radu Tudoran Stefano Bortoli Bogdan Nicolae Inria Rennes-Bretagne Atlantique France IRISA/INSA Rennes France Universidad Politecnica de Madrid Spain Huawei Germany Research Center

Big Data applications are rapidly moving from a batch-oriented execution model to a streaming execution model in order to extract value from the data in real-time. However, processing live data alone is often not enough: in many cases, such applications need to combine the live data with previously archived data to increase the quality of the extracted insights. Current streaming-oriented runtimes and middlewares are not flexible enough to deal with this trend, as they address ingestion (collection and pre-processing of data streams) and persistent storage (archival of intermediate results) using separate services. This separation often leads to I/O redundancy (e.g., write data twice to disk or transfer data twice over the network) and interference (e.g., I/O bottlenecks when collecting data streams and writing archival data simultaneously). In this position paper, we argue for a unified ingestion and storage architecture for streaming data that addresses the aforementioned challenge. We identify a set of constraints and benefits for such a unified model, while highlighting the important architectural aspects required to implement it in real life. Based on these aspects, we briefly sketch our plan for future work that develops the position defended in this paper.

关键词： Throughput Big Data Data models distributed databases Runtime Routing Scalability

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An Automated Feedback-Based Approach to Support Mobile App Development

An Automated Feedback-Based Approach to Support Mobile App D...

引用

Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

作者： Simon André Scherr Frank Elberzhager Konstantin Holl Fraunhofer IESE Kaiserslautern Germany

The acceptance of mobile applications is highly dependent on the realized set of features and on the quality of the application. Information about their acceptance can be gained quickly by collecting and analyzing user feedback such as explicit textual reviews provided by an application's users or implicitly provided usage data. With an approach based on developing a minimal set of functions in order to realize a minimum viable product (MVP), it is possible to put a product on the market within a short amount of time. Currently, the elicitation, analysis, and processing of user feedback is unfocused and takes too much time and effort to mitigate the poor quality of the application. Hence, we outline an approach named Opti4Apps, which is aimed at tailored quality assurance as part of MVP development and enables and expands the benefits of an MVP by providing a semiautomated feedback elicitation, analysis, and processing framework. This is intended to raise the effectiveness and efficiency of early user feedback consideration during further development in order to assure the quality and acceptance of an app as an MVP. We will present the overall structure as well as the process behind the Opti4Apps framework. As proof-of-concept, we implemented an initial prototype of our idea, focused on textual user feedback.

关键词： Mobile communication Data mining Mobile handsets distributed databases Quality assurance Mobile applications Software

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Fast Parallel Recovery of Many Small In-Memory Objects

Fast Parallel Recovery of Many Small In-Memory Objects

引用

International Conference on Parallel and distributed Systems (ICPADS)

作者： Kevin Beineke Stefan Nothaas Michael Schottner Heinrich-Heine-Universität Dusseldorf Dusseldorf Germany Heinrich-Heine-Universitat Dusseldorf Dusseldorf Nordrhein-Westfalen DE

ISBN: (纸本)9781538632086

Social media networks as well as online graph analytics operate on large-scale graphs with millions of vertices, even billions in some cases. Low-latency access is essential, but caching suffers from the mostly irregular access patterns of the aforementioned application domains. Hence, distributed in-memory systems are proposed keeping all data always in memory. These in-memory systems are typically not optimized for the sheer amounts of small data objects, which demands new concepts regarding the local and global data management as well as for the fault-tolerance mechanisms to mask server failures and power outages. In this paper, we propose a novel backup distribution and parallel recovery approach aiming at fast recovery of servers storing hundreds of millions of small objects. All proposed concepts have been implemented within the open source distributed system DXRAM and have been evaluated in the Microsoft Azure cloud with up to 72 high performance virtual machines in two scale-sets. For evaluation, we used two benchmarks: the Yahoo! Cloud Serving Benchmark and a recovery benchmark. The experiments show that the proposed recovery strategy is able to recover servers with 500,000,000 small data objects in less than 2 seconds and, also, to efficiently mask server failures under heavy load. Furthermore, DXRAM outperforms the state-of-the-art system RAMCloud in additional recovery experiments with large objects (2.4× faster) and even more with small objects (> 9×).

关键词： Servers Random access memory distributed databases Peer-to-peer computing Fault tolerance Fault tolerant systems Power system reliability

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A Load-Balanced Parallel and distributed Sorting Algorithm Implemented with PGX.D

A Load-Balanced Parallel and Distributed Sorting Algorithm I...

引用

IEEE International Symposium on Parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Zahra Khatami Sungpack Hong Jinsoo Lee Siegfried Depner Hassan Chafi J. Ramanujam Hartmut Kaiser Oracle Labs USA Center for Computation and Technology Louisiana State University

Sorting has been one of the most challenging studied problems in different scientific researches. Although many techniques and algorithms have been proposed on the theory of having efficient parallel sorting implementation, however achieving desired performance on different types of the architectures with large number of processors is still a challenging issue. Maximizing parallelism level in applications can be achieved by minimizing overheads due to load imbalance and waiting time due to memory latencies. In this paper, we present a distributed sorting algorithm implemented in PGX. D, a fast distributed graph processing system, which outperforms the Spark's distributed sorting implementation by around 2x-3x by hiding communication latencies and minimizing unnecessary overheads. Furthermore, it shows that the proposed PGX. D sorting method handles dataset containing many duplicated data entries efficiently and always results in keeping balanced workloads for different input data distribution types.

关键词： Sorting Program processors distributed databases Merging Scalability Sparks Algorithm design and analysis

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Elastic Consistent Hashing for distributed Storage Systems

Elastic Consistent Hashing for Distributed Storage Systems

引用

International Symposium on Parallel and distributed Processing (IPDPS)

作者： Wei Xie Yong Chen Department of Computer Science Texas Tech University Lubbock TX

Elastic distributed storage systems have been increasingly studied in recent years because power consumption has become a major problem in data centers. Much progress has been made in improving the agility of resizing small- and large-scale distributed storage systems. However, most of these studies focus on metadata based distributed storage systems. On the other hand, emerging consistent hashing based distributed storage systems are considered to allow better scalability and are highly attractive. We identify challenges in achieving elasticity in consistent hashing based distributed storage. These challenges cannot be easily solved by techniques used in current studies. In this paper, we propose an elastic consistent hashing based distributed storage to solve two problems. First, in order to allow a distributed storage to resize quickly, we modify the data placement algorithm using a primary server design and achieve an equal-work data layout. Second, we propose a selective data re-integration technique to reduce the performance impact when resizing a cluster. Our experimental and trace analysis results confirm that our proposed elastic consistent hashing works effectively and allows significantly better elasticity.

关键词： Servers distributed databases Elasticity Power demand Layout Metadata Scalability

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Civil Aircraft Big Data Platform

Civil Aircraft Big Data Platform

引用

International Conference on Semantic Computing

作者： Sujie Li Yi Yang Lu Yang Haixia Su Guigang Zhang Jian Wang Institute of Automation Chinese Academy of Sciences Beijing China Shanghai Engineering Research Center of Civil Aircraft Health Monitoring Shanghai China

The aviation industry generates massive data every day. By analyzing the aviation big data, aviation manufacturers and airlines can optimize the flight of civil aircraft including risk reducing, operation optimization, and personalized services. Building a platform for storing and analyzing the aviation big data becomes an important task for civil aviation. This paper proposes a civil aircraft big data platform that works on facilitate the development of civil aviation. The platform collects data from multiple types of data sources, including aircrafts, airlines, and maintenance centers. The platform provides decision making support for civil aircrafts including maintenance plan, real-time alarm, health management, fuel saving, and airline schedule. The paper introduces the architecture of the platform and present applications to show how the platform facilitates civil aviation.

关键词： Aircraft Big Data Maintenance engineering Aircraft propulsion Monitoring Aircraft manufacture distributed databases

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Networked H∞ filtering for discrete-time nonlinear singular system with mixed random delays and packet dropouts

Networked H∞ filtering for discrete-time nonlinear singular...

引用

Chinese Control Conference (CCC)

作者： Qiyi Xu Yijun Zhang Shunyuan Xiao School of Automation Nanjing University of Science and Technology Nanjing P. R. China

The H ∞ filtering design problem is studied for a class of networked discrete-time nonlinear singular system. Both mixed random delays and packet dropouts in the communication channels are considered. The mixed time-delays consists of the discrete and distributed delays. And the packet dropout phenomenon occurs in a random way. Three mutually independent Bernoulli distributed random variables are utilized to model the stochastic phenomena. By using the Lyapunov-Kravoskii stability approach, sufficient conditions are presented to guarantee the closed-loop filter error system is regular, causal and stable with a certain H ∞ performance index. And the H ∞ filtering design method is provided. An illustrative example is provided to illustrate the effectiveness of the proposed filter design method.

关键词： Delays Networked control systems Symmetric matrices Stochastic processes Stability analysis distributed databases Random variables

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