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Special Issue "Fog/Edge Computing-Based Smart Sensing System"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: 20 February 2020

Special Issue Editors

Guest Editor
Prof. Tian Wang

College of Computer Science and Technology, Huaqiao University, China
Website | E-Mail
Interests: sensor networks; sensor-cloud; fog computing
Guest Editor
Prof. Geyong Min

High Performance Computing and Networking (HPCN) Research Group, the University of Exeter, UK
Website | E-Mail
Interests: next-generation Internet; sensor networks; cloud computing; big data
Guest Editor
Prof. Md Zakirul Alam Bhuiyan

Computer and Information Sciences at Fordham University, NY, USA
Website | E-Mail
Interests: sensor networks; cyber physical system

Special Issue Information

Dear Colleagues,

The Fourth International Symposium on Sensor-Cloud Systems (SCS 2019, http://www.spaccs.org/SCS2019/) will be held in Atlanta, America, July 14-17, 2019, in conjunction with "The 12th International Conference on Security, Privacy, and Anonymity in Computation, Communication, and Storage (SpaCCS 2019)". Moreover, the 7th International Conference on Smart Cities and Informatization (iSCI 2019) will be held in Guangzhou, China, November 12-15, 2019.

This Special Issue is cooperating with SCS 2019 and iSCI 2019. Authors of outstanding papers related to sensors presented at these conferences are invited to submit extended versions of their work to the Special Issue for publication.

Wireless sensor networks (WSNs) and cloud computing have received tremendous attention from both academia and industry, as they now own numerous exciting applications in the Internet of Things and smart cities, which can fundamentally change the way people interact with the physical world.

However, there are still challenges that need to be addressed in order to accelerate the development of these integrated systems. First, current techniques of cloud computing cannot satisfy real-time requirements. The cloud cannot respond to sensors’ emergency requests. Second, communication from sensors to the cloud is a big problem, because sensors are with low bandwidth and low energy supplies. Third, as sensors are weak in processing and communication abilities, it is difficult for the cloud to guarantee the stability of the connection or even tolerate errors in that data. Finally, when sensors upload data to cloud for storage, the best way to ensure the data security and privacy in the cloud environment is unclear.

Compared with cloud computing, fog/edge computing is a promising technique for sensor–cloud systems. Fog/edge computing is proposed to enable computing directly at the edge of networks, delivering applications and services especially for IoT or smart cities. These fog devices, called fog nodes, have some local computation and storage capacity, wide geo-distribution-like sensors, and support for mobility. They can be industrial controllers, switches, routers, embedded servers, and video surveillance cameras, and they can be deployed anywhere with network connections. Serving as a link between sensor networks and the cloud, the fog can process and store data near where they are produced and then manage and control sensors at a short distance. In this way, fog/edge computing can extend cloud computing and cover its shortage in smart sensing system.

Prof. Tian Wang
Prof. Geyong Min
Prof. Md Zakirul Alam Bhuiyan
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 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. Sensors is an international peer-reviewed open access semimonthly 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

  • concepts, theory, standardization and modelling, and methodologies for sensor-cloud systems
  • fog computing framework for sensor-cloud system
  • fog computing for data collection of sensor-cloud systems
  • fog computing for real-time computing of sensor-cloud systems
  • fog computing for communications of sensor-cloud systems
  • fog computing for reliabilities of sensor-cloud systems
  • fog computing for data security of sensor-cloud systems
  • fog computing for privacy of sensor-cloud systems
  • fog computing for energy efficiency of sensor-cloud systems
  • fog computing for trust and reputation evaluation of sensor-cloud systems
  • fog computing for data Integrity of sensor-cloud systems
  • fog based applications for sensor-cloud systems
  • mobile fog computing for sensor-cloud systems
  • mobile fog elements for sensor-cloud systems

Published Papers (3 papers)

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Research

Open AccessArticle CMTN-SP: A Novel Coverage-Control Algorithm for Moving-Target Nodes Based on Sensing Probability Model in Sensor Networks
Sensors 2019, 19(2), 257; https://doi.org/10.3390/s19020257
Received: 4 December 2018 / Revised: 26 December 2018 / Accepted: 7 January 2019 / Published: 10 January 2019
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Abstract
The non-consecutive coverage problem for the target nodes in Sensor Networks could lead to the coverage blind area and a large amount of redundant data, which causes the bottleneck phenomenon for the communication link. A novel Coverage Control Algorithm for Moving Target Nodes [...] Read more.
The non-consecutive coverage problem for the target nodes in Sensor Networks could lead to the coverage blind area and a large amount of redundant data, which causes the bottleneck phenomenon for the communication link. A novel Coverage Control Algorithm for Moving Target Nodes Based on Sensing Probability Model (CMTN-SP) is proposed in this work. Firstly, according to the probability theory, we derive the calculation method for the expectation of the coverage quality with multiple joint nodes, which aims to reduce the coverage blind area and improving network coverage rate. Secondly, we employ the dynamic transferring mechanism of the nodes to re-optimize the deployment of the nodes, which alleviates the rapid exhaustion of the proper network energy. Finally, it is verified via the results of the simulation that the network coverage quality could not only be improved by the proposed algorithm, but the proposed algorithm could also effectively curb the rapid exhaustion of the node energy. Full article
(This article belongs to the Special Issue Fog/Edge Computing-Based Smart Sensing System)
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Open AccessArticle Answering the Min-Cost Quality-Aware Query on Multi-Sources in Sensor-Cloud Systems
Sensors 2018, 18(12), 4486; https://doi.org/10.3390/s18124486
Received: 4 November 2018 / Revised: 10 December 2018 / Accepted: 11 December 2018 / Published: 18 December 2018
Cited by 3 | PDF Full-text (1115 KB) | HTML Full-text | XML Full-text
Abstract
In sensor-based systems, the data of an object is often provided by multiple sources. Since the data quality of these sources might be different, when querying the observations, it is necessary to carefully select the sources to make sure that high quality data [...] Read more.
In sensor-based systems, the data of an object is often provided by multiple sources. Since the data quality of these sources might be different, when querying the observations, it is necessary to carefully select the sources to make sure that high quality data is accessed. A solution is to perform a quality evaluation in the cloud and select a set of high-quality, low-cost data sources (i.e., sensors or small sensor networks) that can answer queries. This paper studies the problem of min-cost quality-aware query which aims to find high quality results from multi-sources with the minimized cost. The measurement of the query results is provided, and two methods for answering min-cost quality-aware query are proposed. How to get a reasonable parameter setting is also discussed. Experiments on real-life data verify that the proposed techniques are efficient and effective. Full article
(This article belongs to the Special Issue Fog/Edge Computing-Based Smart Sensing System)
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Open AccessArticle Data Fusion Using Improved Support Degree Function in Aquaculture Wireless Sensor Networks
Sensors 2018, 18(11), 3851; https://doi.org/10.3390/s18113851
Received: 12 October 2018 / Revised: 4 November 2018 / Accepted: 6 November 2018 / Published: 9 November 2018
Cited by 1 | PDF Full-text (2534 KB) | HTML Full-text | XML Full-text
Abstract
For monitoring the aquaculture parameters in pond with wireless sensor networks (WSN), high accuracy of fault detection and high precision of error correction are essential. However, collecting accurate data from WSN to server or cloud is a bottleneck because of the data faults [...] Read more.
For monitoring the aquaculture parameters in pond with wireless sensor networks (WSN), high accuracy of fault detection and high precision of error correction are essential. However, collecting accurate data from WSN to server or cloud is a bottleneck because of the data faults of WSN, especially in aquaculture applications, limits their further development. When the data fault occurs, data fusion mechanism can help to obtain corrected data to replace abnormal one. In this paper, we propose a data fusion method using a novel function that is Dynamic Time Warping time series strategy improved support degree (DTWS-ISD) for enhancing data quality, which employs a Dynamic Time Warping (DTW) time series segmentation strategy to the improved support degree (ISD) function. We use the DTW distance to replace Euclidean distance, which can explore the continuity and fuzziness of data streams, and the time series segmentation strategy is adopted to reduce the computation dimension of DTW algorithm. Unlike Gauss support function, ISD function obtains mutual support degree of sensors without the exponent calculation. Several experiments were finished to evaluate the accuracy and efficiency of DTWS-ISD with different performance metrics. The experimental results demonstrated that DTWS-ISD achieved better fusion precision than three existing functions in a real-world WSN water quality monitoring application. Full article
(This article belongs to the Special Issue Fog/Edge Computing-Based Smart Sensing System)
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