دانلود مقاله ISI انگلیسی شماره 47024
عنوان فارسی مقاله

معماری جامد برای مدیریت زمان واقعی داده های معنایی بزرگ

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
47024 2015 18 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
The Solid  architecture for real-time management of big semantic data ☆
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Future Generation Computer Systems, Volume 47, June 2015, Pages 62–79

کلمات کلیدی
معماری طبقه - داده های معنایی بزرگ - بهنگام -
پیش نمایش مقاله
پیش نمایش مقاله معماری جامد برای مدیریت زمان واقعی داده های معنایی بزرگ

چکیده انگلیسی

Big Data management has become a critical task in many application systems, which usually rely on heavyweight batch processes to manage such large amounts of data. However, batch architectures are not an adequate choice for designing real-time systems in which data updates and reads must be satisfied with very low latency. Thus, gathering and consuming high volumes of data at high velocities is an emerging challenge which we specifically address in the scope of innovative scenarios based on semantic data (RDF) management. The Linked Open Data initiative or emergent projects in the Internet of Things are examples of such scenarios. This paper describes a new architecture (referred to as Solid) which separates the complexities of Big Semantic Data storage and indexing from real-time data acquisition and consumption. This decision relies on the use of two optimized datastores which respectively store historical (big) data and run-time data. It ensures efficient volume management and high processing velocity, but adds the need of coordinating both datastores. Solid  proposes a 3-tiered architecture in which each responsibility is specifically addressed. Besides its theoretical description, we also propose and evaluate a Solid  prototype built on top of binary RDF and state-of-the-art triplestores. Our experimental numbers report that Solid  achieves large savings in data storage (it uses up to 55 times less space than the compared triplestores), while provides efficient SPARQL resolution over the Big Semantic Data (in the order of 10–20 ms for the studied queries). These experiments also show that Solid  ensures low-latency operations because data effectively managed in real-time remain small, so do not suffer Big Data issues.

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