Real-Time Data Services for the Internet of Things

A special issue of Big Data and Cognitive Computing (ISSN 2504-2289).

Deadline for manuscript submissions: closed (31 December 2018) | Viewed by 332

Special Issue Editors


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Guest Editor
Department of Computer Science, State University of New York at Binghamton, Binghamton, NY 13902, USA
Interests: Internet of Things; cyber-physical systems; real-time embedded systems

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Guest Editor
Computer Science and Engineering Department, University of Connecticut, Storrs, CT 06269, USA
Interests: industrial Internet-of-Things; Cyber-Physical Systems; embedded sensing and control systems; real-time data analytics; wireless networks

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) interconnects embedded sensors, actuators, robots, vehicles, homes, buildings, factories, electric grids, and humans to support numerous important applications, including cognitive assistance, health care, smart homes and buildings, intelligent transportation, smart grids, and industry 4.0, with tremendous societal and economic impacts. By 2020, there will be tens of billions of connected things expected to generate trillion dollar revenues according to Cisco and Gartner. To realize the IoT vision, it is required to collect, exchange, store, analyze, and visualize high volume of data in real-time to detect, predict, and react to important events, such as abnormal health conditions of vulnerable populations, traffic delays and incidents, road hazards, demand-supply analysis and prediction for electric grids, and malfunctioning industrial robots, in a timely fashion. Achieving this goal, however, is challenging due to stringent timing constraints and big/fast real-time data streams. Enabling technologies to be explored include novel networking infrastructures and protocols, real-time data stream management and analytics (in things, within networks, at network edges, and in cloud), consumer and industry case studies, and security/privacy, which can handle and support IoT heterogeneity, scalability, and interoperability. This Special Issue calls for original research articles, case studies, and applications that advance technologies for real-time data services for IoT.

Prof. Dr. Kyoung-Don Kang
Prof. Dr. Song Han
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Big Data and Cognitive Computing is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Real-time networking for IoT
  • Edge or Cloud Computing for Real-Time Data Analysis
  • Scalable and interoperable real-time middleware for IoT
  • Real-time data processing systems for stream data management, complex event processing, etc.
  • Real-time data analytics via online machine learning
  • Time series analysis for stream data
  • Context analysis and event detection
  • Data cleaning, alignment, quality management, and visualization
  • Security and privacy
  • Emerging applications and case studies

Published Papers

There is no accepted submissions to this special issue at this moment.
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