شیوه های مدیریت داده ها در اینترنت اشیا
ترجمه نشده

شیوه های مدیریت داده ها در اینترنت اشیا

عنوان فارسی مقاله: شیوه های مدیریت داده ها در اینترنت اشیا
عنوان انگلیسی مقاله: Data management techniques for Internet of Things
مجله/کنفرانس: سیستم های مکانیکی و پردازش سیگنال – Mechanical Systems and Signal Processing
رشته های تحصیلی مرتبط: مهندسی فناوری اطلاعات، مهندسی کامپیوتر
گرایش های تحصیلی مرتبط: اینترنت و شبکه های گسترده، هوش مصنوعی
کلمات کلیدی فارسی: مدیریت داده ها، اینترنت اشیا، اپلیکیشن های اینترنت اشیا، کلان داده ها، اینترنت اشیای صنعتی
کلمات کلیدی انگلیسی: Data management, Internet of Things, IoT applications, Big data, Industrial Internet of Things
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: Scopus – Master Journals List – JCR
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.ymssp.2019.106564
دانشگاه: University of Assane Seck, Ziguinchor, Senegal
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2020
ایمپکت فاکتور: 6.032 در سال 2019
شاخص H_index: 134 در سال 2020
شاخص SJR: 1.821 در سال 2019
شناسه ISSN: 0888-3270
شاخص Quartile (چارک): Q1 در سال 2019
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 19
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E14159
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست انگلیسی مطالب

Abstract


1- Introduction


2- Internet of things verticals


3- Background and basic concepts of data management


4- Current proposals of data management systems in IoT


5- Discussion and open issues


6- IoT data requirements for processing and storage


7- Conclusion


Acknowledgements


References

نمونه متن انگلیسی مقاله

Abstract


Internet of Things (IoT) is a network paradigm in which physical, digital, and virtual objects are equipped with identification, detection, networking, and processing functions to communicate with each other and with other devices and services on the Internet in order to perform the users’ required tasks. Many IoT applications are provided to bring comfort and facilitate the human life. In addition, the application of IoT technologies in the automotive industry has given rise to the concept of Industrial Internet of Things (IIoT) which facilitated using of Cyber Physic Systems, in which machines and humans interact. Due to the diversity, heterogeneity, and large volume of data generated by these entities, the use of traditional database management systems is not suitable in general. In the design of IoT data management systems, many distinctive principles should be considered. These different principles allowed the proposal of several approaches for IoT data management. Some middleware or architecture-oriented solutions facilitate the integration of generated data. Other available solutions provide efficient storage and indexing structured and unstructured data as well as the support to the NoSQL language. Thus, this paper identifies the most relevant concepts of data management in IoT, surveys the current solutions proposed for IoT data management, discusses the most promising solutions, and identifies relevant open research issues on the topic providing guidelines for further contributions.


Introduction


In computing science’s history, the Internet had become more present in people’s lives in a very short time than any other technology. It had revolutionized the possibility of people’s communication. Later, Internet involves the possibility of connecting machines, devices, software, and objects [1]. Through the use of the Transmission Control Protocol/Internet Protocol (TCP/IP) architecture, these objects can be connected a network. This allowed communication between them without human intervention. Most recently, a new concept called, Internet of Things (IoT), appears and it is considered the main evolution to the fourth generation of the Internet. IoT does not have a unambiguous and acceptable definition from users of the global community [2]. Only the term is defined by several entities associating academicians, researchers, practitioners, innovators, developers, and businessmen but its initial use was attributed to Kevin Ashton, an expert in digital innovation [3]. One of the best IoT definition considers it a dynamic and global network infrastructure, in which intelligent things (objects), subsystems and individual physical and virtual entities, are identifiable, autonomous, and self-configurable [4,5]. This sort of network has generally a large number of nodes (things) widely distributed on a given area and communicating among themselves in order to interact with environment by exchanging sensed data, while reacting to events and triggering actions to control the physical world. Each network node is considered smart (given by the software that allows autonomous behaviors) with generally very limited resources, especially those of storage, processing and energy. This implies, among other problems, the reliability and validity of data, performance, security, the privacy

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