2015 IEEE First International Conference on Big Data Computing Service and Applications

March 30 2015-April 2 2015

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  • [Front cover]

    Publication Year: 2015, Page(s): C4
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  • [Title page i]

    Publication Year: 2015, Page(s): i
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  • [Title page iii]

    Publication Year: 2015, Page(s): iii
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  • [Copyright notice]

    Publication Year: 2015, Page(s): iv
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  • Table of contents

    Publication Year: 2015, Page(s):v - x
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  • Message from the IEEE BigDataService 2015 General Chairs

    Publication Year: 2015, Page(s): xi
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  • Message from the IEEE BigDataService 2015 Program Chairs

    Publication Year: 2015, Page(s): xii
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  • IEEE BigDataService 2015 Organizing Committee

    Publication Year: 2015, Page(s):xiii - xv
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  • IEEE BigDataService 2015 Program Committee

    Publication Year: 2015, Page(s):xvi - xxi
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  • Sponsors

    Publication Year: 2015, Page(s): xxii
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  • Interest-Based Mining and Modeling of Big Mobile Networks

    Publication Year: 2015, Page(s):1 - 6
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1006 KB) | HTML iconHTML

    Usage of mobile wireless Internet has grown very fast in recent years. This radical change in availability of Internet has led to communication of big amount of data over mobile networks raising new challenges and opportunities for modeling of mobile Internet characteristics. While the traditional approach toward network modeling suggests finding a generic traffic model for the whole network, in t... View full abstract»

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  • A Hybrid Network Architecture for Data Centers

    Publication Year: 2015, Page(s):7 - 13
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (757 KB) | HTML iconHTML

    In recent years, the concept of Big Data (BD) analytics has brought rapid changes to the way enterprises conduct business. Everyday more organizations are getting into the cloud of BD users. Due to an influx of data analytic projects, data centers and cloud-based service providers have experienced massive growth. A growth engulfed with impetuous increase of data and the rapid rise of Internet traf... View full abstract»

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  • Scalable Security Event Aggregation for Situation Analysis

    Publication Year: 2015, Page(s):14 - 23
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1293 KB) | HTML iconHTML

    Cyber-attacks have been evolved in a way to be more sophisticated by employing combinations of attack methodologies with greater impacts. For instance, Advanced Persistent Threats (APTs) employ a set of stealthy hacking processes running over a long period of time, making it much hard to detect. With this trend, the importance of big-data security analytics has taken greater attention since identi... View full abstract»

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  • Big Graph Processing Systems: State-of-the-Art and Open Challenges

    Publication Year: 2015, Page(s):24 - 33
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (386 KB) | HTML iconHTML

    Graph is a fundamental data structure that captures relationships between different data entities. In practice, graphs are widely used for modeling complicated data in different application domains such as social networks, protein networks, transportation networks, bibliographical networks, knowledge bases and many more. Currently, graphs with millions and billions of nodes and edges have become v... View full abstract»

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  • Fast Quantitative Analysis of Stock Trading Points in Dual Period of DMAC

    Publication Year: 2015, Page(s):34 - 43
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1196 KB) | HTML iconHTML

    We propose a novel volatility segmentation approach to detect effective trading points from 2679 stocks of NASDAQ. The buy and sell points are derived from dual periods of DMAC based on daily and weekly periods by estimating the amplitude and interval. The proposed approach is very accurate in that only 373 stocks (out of 2679) in NASDAQ have the average rate of profit of overall buy points higher... View full abstract»

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  • An Optimized Generic Client Service API for Managing Large Datasets within a Data Repository

    Publication Year: 2015, Page(s):44 - 51
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (848 KB) | HTML iconHTML

    Exponential growth in scientific research data demands novel measures for managing the extremely large datasets. In particular, due to advancements in high-resolution microscopy, the nanoscopy scientific research community is producing datasets up to the range of multiple TeraBytes (TB). Systematically acquired datasets of biological specimens are composed of multiple high-resolution images, in th... View full abstract»

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  • Monitoring Noise Pollution Using the Urban Civics Middleware

    Publication Year: 2015, Page(s):52 - 61
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3888 KB) | HTML iconHTML

    Noise pollution is a significant problem in cities due to its various effects on health, but the modeling of noise data and the generation of accurate noise pollution maps suffer from the high cost and restricted scale of sensing performed using static municipal sensors. In this paper, we present our approach for augmenting municipally sensed data using participatory sensing-based information coll... View full abstract»

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  • Performance Characterization of the Servioticy API: An IoT-as-a-Service Data Management Platform

    Publication Year: 2015, Page(s):62 - 71
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1101 KB) | HTML iconHTML

    In the last years, Internet of Things (IoT) and Big Data platforms are clearly converging in terms of technologies, problems and approaches. IoT workloads generate a vast amount of data that needs to be stored and processed, becoming a Big Data problem. IoT devices and sensors generate streams of data across a diversity of locations and protocols that in the end reach a central platform that is us... View full abstract»

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  • Framework Using Bayesian Belief Networks for Utility Effective Management and Operations

    Publication Year: 2015, Page(s):72 - 78
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1014 KB) | HTML iconHTML

    A Networked Society based on the Internet of Things is a significant paradigm shift in the early 21st century. The advanced modern engineered systems, constituent of the networked society, within the areas of Utility, Transport, Telecommunication and Enterprise are becoming increasingly dynamic and complex. These encompass various smart devices components, including both software and hardware such... View full abstract»

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  • Big Data Sensing and Service: A Tutorial

    Publication Year: 2015, Page(s):79 - 88
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1973 KB) | HTML iconHTML

    As the advance of the Internet of Things (IoT), more M2M sensors and devices are connected to the Internet. These sensors and devices generate sensor-based big data and bring new business opportunities and demands for creating and developing sensor-oriented big data infrastructures, platforms and analytics service applications. Big data sensing is becoming a new concept and next technology trend b... View full abstract»

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  • When Good-Enough is Enough: Complex Queries at Fixed Cost

    Publication Year: 2015, Page(s):89 - 98
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (361 KB) | HTML iconHTML

    Collections of time-series data appear in a wide variety of contexts. To gain insight into the underlying phenomenon (that the data represents), one must analyze the time-series data. Analysis can quickly become challenging for very large data (~terabytes or more) sets, and it may be infeasible to scan the entire data-set on each query due to time limits or resource constraints. To avoid this prob... View full abstract»

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  • Web Service-Enabled Spam Filtering with Naïve Bayes Classification

    Publication Year: 2015, Page(s):99 - 104
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (412 KB) | HTML iconHTML

    Electronic mail has nowadays become a convenient and inexpensive way for communication regardless of the distance. However, an increasing volume of unsolicited emails is bringing down the productivity dramatically. There is a need for reliable anti-spam filters to separate such messages from legitimate ones. The Naïve Bayesian classifier is suggested as an effective engine to pick out spam... View full abstract»

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  • BDAP: A Big Data Placement Strategy for Cloud-Based Scientific Workflows

    Publication Year: 2015, Page(s):105 - 114
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (569 KB) | HTML iconHTML

    In this new era of Big Data, there is a growing need to enable scientific workflows to perform computations at a scale far exceeding a single workstation's capabilities. When running such data intensive workflows in the cloud distributed across several physical locations, the execution time and the resource utilization efficiency highly depends on the initial placement and distribution of the inpu... View full abstract»

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  • Do You Feel the Lag of Your Hadoop?

    Publication Year: 2015, Page(s):115 - 119
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (547 KB) | HTML iconHTML

    The configuration of a Hadoop cluster is significantly important to its performance, because an improper configuration can greatly deteriorate the job execution performance. Unfortunately, systematic guidelines on how to configure a Hadoop cluster are still missing. In this paper, we undertake an empirical study on key operations and mechanisms of Hadoop job execution, including the task assignmen... View full abstract»

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  • Secure Scalar Product for Big-Data in MapReduce

    Publication Year: 2015, Page(s):120 - 129
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (412 KB) | HTML iconHTML

    Organizations and individuals nowadays are more and more willing to outsource their data to save storage and management costs, especially with the push of cloud computing which offers both storage and computation scalability. However, the data, once being released to a server, is no longer under its owner's control, and its privacy and security herein become a primary concern. To this end, users u... View full abstract»

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