تحلیل داده بزرگ برای محیط شهری هوشمند مبتنی بر اینترنت اشیا
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تحلیل داده بزرگ برای محیط شهری هوشمند مبتنی بر اینترنت اشیا

عنوان فارسی مقاله: سیستم مدیریت داده شهری: به سوی تحلیل داده بزرگ برای محیط شهری هوشمند مبتنی بر اینترنت اشیا با استفاده از Hadoop سفارشی
عنوان انگلیسی مقاله: Urban data management system: Towards Big Data analytics for Internet of Things based smart urban environment using customized Hadoop
مجله/کنفرانس: سیستم های کامپیوتری نسل آینده-Future Generation Computer Systems
رشته های تحصیلی مرتبط: مهندسی کامپیوتر، مهندسی فناوری اطلاعات
گرایش های تحصیلی مرتبط: هوش مصنوعی، اینترنت و شبکه های گسترده
کلمات کلیدی فارسی: تحلیل داده بزرگ، شهر هوشمند، اینترنت اشیا، Hadoop
کلمات کلیدی انگلیسی: Big Data Analytics, Smart City, Internet of Things, Hadoop
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: Scopus – Master Journals List – JCR
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.future.2019.02.035
دانشگاه: Software Engineering Department, National University of Sciences and Technology Islamabad, Pakistan
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 7.007 در سال 2018
شاخص H_index: 93 در سال 2019
شاخص SJR: 0.835 در سال 2018
شناسه ISSN: 0167-739X
شاخص Quartile (چارک): Q1 در سال 2018
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 19
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
کد محصول: E12081
فهرست انگلیسی مطالب

Abstract


1- Introduction


2- Related work


3- Proposed methodology


4- Data analysis and results


5- Conclusion and future work


References

نمونه متن انگلیسی مقاله

Abstract


The unbroken amplification of a versatile urban setup is challenged by huge Big Data processing. Understanding the voluminous data generated in a smart urban environment for decision making is a challenging task. Big Data analytics is performed to obtain useful insights about the massive data. The existing conventional techniques are not suitable to get a useful insight due to the huge volume of data. Big Data analytics has attracted significant attention in the context of large-scale data computation and processing. This paper presents a Hadoop-based architecture to deal with Big Data loading and processing. The proposed architecture is composed of two different modules, i.e., Big Data loading and Big Data processing. The performance and efficiency of data loading is tested to propose a customized methodology for loading Big Data to a distributed and processing platform, i.e., Hadoop. To examine data ingestion into Hadoop, data loading is performed and compared repeatedly against different decisions. The experimental results are recorded for various attributes along with manual and traditional data loading to highlight the efficiency of our proposed solution. On the other hand, the processing is achieved using YARN cluster management framework with specific customization of dynamic scheduling. In addition, the effectiveness of our proposed solution regarding processing and computation is also highlighted and decorated in the context of throughput.


Introduction


With the passage of time, the technological growth has revolutionized the generation of data [1]. Unlike the landline phones of earlier ages, the availability of smart phones has made our lives smarter. We used to have floppy disks for data storage, however, the same data are now stored at the cloud. A huge amount of data is generated by each action performed using the mobiles phones [2]. The introduction of smart cars in the transportation industry has increased the scale of data generation. These cars have a number of sensors to record every happening event in the context of a vehicle’s functionality. Thus, the volume of data has increased exponentially. Besides, the generated data is not in a structured form [3]. Internet of Things (IoT) plays an essential role in the evolution of data. IoT connects the physical objects with the Internet and makes the objects smarter. IoT is the organization and arrangement of interconnected machines, objects and computing platforms to transmit data over a particular network. IoT has changed the entire digital world and is the main reason behind the evolution of data. It is predicted that there will be 50 billion physical devices integrated in the Internet by 2020 [4].

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