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Context-Rich Interoperable IoT Applications
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Context-Rich Interoperable IoT Applications

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

Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 5551

Special Issue Editors

Prof. Dr. Arkady Zaslavsky

E-Mail Website
Guest Editor
School of Information Technology, Deakin University, Burwood, VIC 3125, Australia
Interests: IoT; context-awareness; smart cities; waste management
Special Issues, Collections and Topics in MDPI journals
Dr. Ali Hassani

E-Mail Website
Guest Editor
School of Info Technology, Deakin University, Burwood, VIC 3125, Australia
Interests: IoT; middleware platforms; software engineering; scalable architecture; query language
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) envisions an ecosystem in which everyday objects are enhanced with sensing, computation, actuation, and communication capabilities. These ‘smart’ devices (i.e., IoT devices) can sense and collect an enormous amount of data about their surroundings. By processing the data produced by IoT devices, it is possible to infer the current context and situation of physical and virtual entities forming our world, and utilising the context data to enhance a wide range of applications in a way that they adapt their behaviour according to the context of their related entities, including themselves. Such applications are known as context-aware IoT applications.

While context-driven intelligence is a fundamental factor for IoT sustainability, growth, interoperability, and acceptance, IoT’s characteristics, such as scalability, big data, heterogeneity, interoperability, and dynamism, will make the development of context-aware IoT applications and services a very challenging task. This Special Issue aims to bring together researchers and application developers working on the intersection of IoT and context awareness, developing next-generation context-rich interoperable IoT applications, algorithms, frameworks, and solutions to support the growth and applicability of IoT. We welcome high-quality research, work in progress, quality review articles, real-world experiments, and deployment use-case papers that address the challenges and gaps in the current state of the art in the areas mentioned above.

Potential research topics of interest include (but are not necessarily limited to) the following:

  • Formal context and situation modelling;
  • Dynamic discovery and annotation of IoT services;
  • Machine learning and deep learning for context and situation reasoning and prediction;
  • Architectures, protocols, frameworks, and applications of context management platform;
  • Cost and quality of context;
  • Privacy and access control for context-aware IoT.

Application use-cases reporting outcomes of real-world case studies that demonstrate context and situation-aware IoT applications and services include, but are not limited to, the following:

  • Smart cities;
  • Intelligent transport systems;
  • Industry 4.0;
  • Digital health.

Prof. Dr. Arkady Zaslavsky
Dr. Ali Hassani
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. 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 2600 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.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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32 pages, 5467 KiB  
Article
Situation-Aware IoT Data Generation towards Performance Evaluation of IoT Middleware Platforms
by Shalmoly Mondal, Prem Prakash Jayaraman, Pari Delir Haghighi, Alireza Hassani and Dimitrios Georgakopoulos
Sensors 2023, 23(1), 7; https://doi.org/10.3390/s23010007 - 20 Dec 2022
Cited by 4 | Viewed by 1964
Abstract
With the increasing growth of IoT applications in various sectors (e.g., manufacturing, healthcare, etc.), we are witnessing a rising demand of IoT middleware platform that host such IoT applications. Hence, there arises a need for new methods to assess the performance of IoT [...] Read more.
With the increasing growth of IoT applications in various sectors (e.g., manufacturing, healthcare, etc.), we are witnessing a rising demand of IoT middleware platform that host such IoT applications. Hence, there arises a need for new methods to assess the performance of IoT middleware platforms hosting IoT applications. While there are well established methods for performance analysis and testing of databases, and some for the Big data domain, such methods are still lacking support for IoT due to the complexity, heterogeneity of IoT application and their data. To overcome these limitations, in this paper, we present a novel situation-aware IoT data generation framework, namely, SA-IoTDG. Given a majority of IoT applications are event or situation driven, we leverage a situation-based approach in SA-IoTDG for generating situation-specific data relevant to the requirements of the IoT applications. SA-IoTDG includes a situation description system, a SySML model to capture IoT application requirements and a novel Markov chain-based approach that supports transition of IoT data generation based on the corresponding situations. The proposed framework will be beneficial for both researchers and IoT application developers to generate IoT data for their application and enable them to perform initial testing before the actual deployment. We demonstrate the proposed framework using a real-world example from IoT traffic monitoring. We conduct experimental evaluations to validate the ability of SA-IoTDG to generate IoT data similar to real-world data as well as enable conducting performance evaluations of IoT applications deployed on different IoT middleware platforms using the generated data. Experimental results present some promising outcomes that validate the efficacy of SA-IoTDG. Learning and lessons learnt from the results of experiments conclude the paper. Full article
(This article belongs to the Special Issue Context-Rich Interoperable IoT Applications)
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30 pages, 3886 KiB  
Article
Requirements, Limitations and Recommendations for Enabling End-to-End Quality of Context-Awareness in IoT Middleware
by Kanaka Sai Jagarlamudi, Arkady Zaslavsky, Seng W. Loke, Alireza Hassani and Alexey Medvedev
Sensors 2022, 22(4), 1632; https://doi.org/10.3390/s22041632 - 19 Feb 2022
Cited by 9 | Viewed by 2927
Abstract
Satisfying a context consumer’s quality of context (QoC) requirements is important to context management platforms (CMPs) in order to have credibility. QoC indicates the contextual information’s quality metrics (e.g., accuracy, timeliness, completeness). The outcomes of these metrics depend on the functional and quality [...] Read more.
Satisfying a context consumer’s quality of context (QoC) requirements is important to context management platforms (CMPs) in order to have credibility. QoC indicates the contextual information’s quality metrics (e.g., accuracy, timeliness, completeness). The outcomes of these metrics depend on the functional and quality characteristics associated with all actors (context consumers (or) context-aware applications, CMPs, and context providers (or) IoT-data providers) in context-aware IoT environments. This survey identifies and studies such characteristics and highlights the limitations in actors’ current functionalities and QoC modelling approaches to obtain adequate QoC and improve context consumers’ quality of experience (QoE). We propose a novel concept system based on our critical analysis; this system addresses the functional limitations in existing QoC modelling approaches. Moreover, we highlight those QoC metrics affected by quality of service (QoS) metrics in CMPs. These recommendations provide CMP developers with a reference system they could incorporate, functionalities and QoS metrics to maintain in order to deliver an adequate QoC. Full article
(This article belongs to the Special Issue Context-Rich Interoperable IoT Applications)
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