Special Issue "Massive Sensory Data Management in WSN, IoT and CPS"

A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708).

Deadline for manuscript submissions: closed (31 October 2019).

Special Issue Editor

Prof. Dr. Abdallah Makhoul
E-Mail Website
Guest Editor
Department of computer science, University of Franche-Comté, Montbéliard, France
Interests: Wireless Sensor Networks & Distributed algorithms & Internet of things & Data management & Machine and deep learning & programmable matter
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Sensors and sensor networks are proliferating in many research domains such as the Internet of Things (IoT) and cyber–physical systems (CPS), and thus in many applications. Usually hundreds or thousands of sensor nodes are randomly deployed to collect environmental data from a region of interest. This makes WSNs one of the big data producers. Therefore, managing this huge amount of collected data is not an easy task, especially for sensors with limited energy and computational resources. This Special Issue aims to solicit recent research in big data management, from data acquisition to analysis, for WSN, IoT and CPS.

Topics of primary interest are centered around sensory data management, including but not limited to:

  • Sensory data acquisition and prediction
  • Sensory data aggregation
  • Multisensory data fusion
  • Sensory data routing and processing
  • Data storage strategies
  • Sensory data mining and machine learning
  • Virtualization technologies and cloud computing for sensory data

Prof. Abdallah Makhoul
Guest Editor

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 papers will be 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. Journal of Sensor and Actuator Networks is an international peer-reviewed open access quarterly 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 1000 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.

Published Papers (1 paper)

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Research

Open AccessArticle
Introducing and Comparing Recent Clustering Methods for Massive Data Management in the Internet of Things
J. Sens. Actuator Netw. 2019, 8(4), 56; https://doi.org/10.3390/jsan8040056 - 09 Dec 2019
Abstract
The use of wireless sensor networks, which are the key ingredient in the growing Internet of Things (IoT), has surged over the past few years with a widening range of applications in the industry, healthcare, agriculture, with a special attention to monitoring and [...] Read more.
The use of wireless sensor networks, which are the key ingredient in the growing Internet of Things (IoT), has surged over the past few years with a widening range of applications in the industry, healthcare, agriculture, with a special attention to monitoring and tracking, often tied with security issues. In some applications, sensors can be deployed in remote, large unpopulated areas, whereas in others, they serve to monitor confined busy spaces. In either case, clustering the sensor network’s nodes into several clusters is of fundamental benefit for obvious scalability reasons, and also for helping to devise maintenance or usage schedules that might greatly improve the network’s lifetime. In the present paper, we survey and compare popular and advanced clustering schemes and provide a detailed analysis of their performance as a function of scale, type of collected data or their heterogeneity, and noise level. The testing is performed on real sensor data provided by the UCI Machine Learning Repository, using various external validation metrics. Full article
(This article belongs to the Special Issue Massive Sensory Data Management in WSN, IoT and CPS)
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