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Applications of Simulation for Engineering Intelligent IoT Systems
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Applications of Simulation for Engineering Intelligent IoT Systems

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

Deadline for manuscript submissions: closed (15 February 2023) | Viewed by 6039

Special Issue Editors

Dr. Fabian Lorig

E-Mail Website
Guest Editor
Internet of Things and People Research Center, Department of Computer Science and Media Technology, Malmö University, 20506 Malmö, Sweden
Interests: agent-based modeling; computer simulation; Internet of Things; artificial intelligence; logistics; transportation
Dr. Fahed Alkhabbas

E-Mail Website
Guest Editor
Internet of Things and People Research Center, Department of Computer Science and Media Technology, Malmö University, 20506 Malmö, Sweden
Interests: software engineering; Internet of Things; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Dr. Muhammad Aamir Cheema

E-Mail Website
Guest Editor
Faculty of Information Technology, Monash University, Wellington Rd., Clayton, VIC 3800, Australia
Interests: spatial databases; location data management and analytics; routing and scheduling in road networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The integration of the Internet of Things (IoT) and artificial intelligence technologies have enabled novel types of applications and services, referred to as Intelligent IoT (IIoT) systems, which can be applied in different domains, such as smart cities, building automation, transportation and logistics, healthcare, and crisis management. The paradigm shift towards IIoT systems, however, also implies new challenges for the engineering of such self-adaptive systems. For instance, the environments of the IIoT systems are dynamic and uncertain, as both users and IoT devices can be mobile. Furthermore, IoT devices are resource-constrained with respect to processing and storage capabilities and energy, and the performance of AI models might degrade, e.g., due to model drifts. Therefore, engineering IIoT systems to cope with such dynamic and uncertain environments requires conducting a trade-off analysis between multiple (and sometimes conflicting) quality attributes. 

Computer simulation, for instance, is a well-suited method for investigating uncertainty as it allows for conducting what-if analyses, i.e., to study the behavior of a system under different circumstances. Hence, simulation is commonly used when engineering IoT systems as it enables engineers to efficiently investigate different aspects of IoT systems in an artificial environment. However, simulations are often limited in terms of the quality aspects. Many existing IoT simulators focus on the assessment of functional requirements, e.g., bandwidth, energy consumption, or latency. Yet, the design of intelligent self-adaptation strategies in IIoT systems also requires the investigation of non-functional requirements, such as scalability, privacy, or security. To this end, innovative approaches are required for engineering adaptive IIoT systems.

In this Special Issue, we welcome novel contributions on the following set of topics of interest, including but not limited to:

  • Applications of modeling and simulation for engineering IIoT systems
  • Trade-off analysis at IIoT architectural level considering quality attributes, such as security, performance, scalability, etc.;
  • Engineering of IIoT systems in
    • smart buildings, e.g., systems managing energy consumption
    • smart city e.g., systems providing mobility planning and traffic adaptation services in dynamic contexts
    • intelligent and autonomous systems, such as self-driving vehicles
    • crisis management (including monitoring, prevention, response management, or recovery).

Dr. Fabian Lorig
Dr. Fahed Alkhabbas
Prof. Dr. Muhammad Aamir Cheema
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.

Keywords

  • Internet of Things
  • software engineering
  • artificial intelligence
  • computer simulation
  • IoT System and software architectures
  • dynamic and uncertain environments
  • non-functional requirements
  • quality aspects
  • tradeoff analysis
  • crisis management
  • smart citites
  • smart buildings
  • smart mobility

Published Papers (3 papers)

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Research

25 pages, 637 KiB  
Article
A TDD Framework for Automated Monitoring in Internet of Things with Machine Learning
by Victor Takashi Hayashi, Wilson Vicente Ruggiero, Júlio Cezar Estrella, Artino Quintino Filho, Matheus Ancelmo Pita, Reginaldo Arakaki, Cairo Ribeiro, Bruno Trazzi and Romeo Bulla, Jr.
Sensors 2022, 22(23), 9498; https://doi.org/10.3390/s22239498 - 5 Dec 2022
Cited by 1 | Viewed by 1800
Abstract
Robust, fault tolerant, and available systems are fundamental for the adoption of Internet of Things (IoT) in critical domains, such as finance, health, and safety. The IoT infrastructure is often used to collect a large amount of data to meet the business demands [...] Read more.
Robust, fault tolerant, and available systems are fundamental for the adoption of Internet of Things (IoT) in critical domains, such as finance, health, and safety. The IoT infrastructure is often used to collect a large amount of data to meet the business demands of Smart Cities, Industry 4.0, and Smart Home, but there is a opportunity to use these data to intrinsically monitor an IoT system in an autonomous way. A Test Driven Development (TDD) approach for automatic module assessment for ESP32 and ESP8266 IoT development devices based on unsupervised Machine Learning (ML) is proposed to monitor IoT device status. A framework consisting of business drivers, non-functional requirements, engineering view, dynamic system evaluation, and recommendations phases is proposed to be used with the TDD development tool. The proposal is evaluated in academic and smart home study cases with 25 devices, consisting of 15 different firmware versions collected in one week, with a total of over 550,000 IoT status readings. The K-Means algorithm was applied to free memory available, internal temperature, and Wi-Fi level metrics to automatically monitor the IoT devices under development to identify device constraints violation and provide insights for monitoring frequency configuration of different firmware versions. To the best of the authors’ knowledge, it is the first TDD approach for IoT module automatic assessment which uses machine learning based on the real testbed data. The IoT status monitoring and the Python scripts for model training and inference with K-Means algorithm are available under a Creative Commons license. Full article
(This article belongs to the Special Issue Applications of Simulation for Engineering Intelligent IoT Systems)
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14 pages, 6185 KiB  
Article
Performance of Narrow Band Wide Area Networks with Gateway Diversity
by Başak Can, Bora Karaoğlu, Uttam Bhat, Muhammed Faruk Gencel and Thomas Chen
Sensors 2022, 22(22), 8831; https://doi.org/10.3390/s22228831 - 15 Nov 2022
Cited by 5 | Viewed by 1470
Abstract
This paper quantifies the coverage area of Low-Power Wide-Area Networks (LPWAN) for Packet Success Rates (PSR) above 85%, where acceptable Quality of Service (QoS) can be achieved. The network consists of battery-operated end-nodes (ENs) and multiple stationary gateways (GWs). We consider asynchronous communication [...] Read more.
This paper quantifies the coverage area of Low-Power Wide-Area Networks (LPWAN) for Packet Success Rates (PSR) above 85%, where acceptable Quality of Service (QoS) can be achieved. The network consists of battery-operated end-nodes (ENs) and multiple stationary gateways (GWs). We consider asynchronous communication that uses ALOHA-based random channel access. Each transmission from the ENs can be received by multiple GWs. Such spatial diversity results in favorable Signal-to-Noise ratios (SNR). The LoRa modulation is assumed and its specific features, such as IQ inversion, further contribute to decreasing the impact of interference. An increase in the GW density improves network performance, which allows support for a larger density of end-nodes as well as increasing the coverage area. Our simulation results show that a suburban area of up to 1.44 km2 can be covered with five GWs with up to fifty end-nodes with a PSR greater than 86%. Full article
(This article belongs to the Special Issue Applications of Simulation for Engineering Intelligent IoT Systems)
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25 pages, 1688 KiB  
Article
ASSERT: A Blockchain-Based Architectural Approach for Engineering Secure Self-Adaptive IoT Systems
by Fahed Alkhabbas, Mohammed Alsadi, Sadi Alawadi, Feras M. Awaysheh, Victor R. Kebande and Mahyar T. Moghaddam
Sensors 2022, 22(18), 6842; https://doi.org/10.3390/s22186842 - 9 Sep 2022
Cited by 8 | Viewed by 2134
Abstract
Internet of Things (IoT) systems are complex systems that can manage mission-critical, costly operations or the collection, storage, and processing of sensitive data. Therefore, security represents a primary concern that should be considered when engineering IoT systems. Additionally, several challenges need to be [...] Read more.
Internet of Things (IoT) systems are complex systems that can manage mission-critical, costly operations or the collection, storage, and processing of sensitive data. Therefore, security represents a primary concern that should be considered when engineering IoT systems. Additionally, several challenges need to be addressed, including the following ones. IoT systems’ environments are dynamic and uncertain. For instance, IoT devices can be mobile or might run out of batteries, so they can become suddenly unavailable. To cope with such environments, IoT systems can be engineered as goal-driven and self-adaptive systems. A goal-driven IoT system is composed of a dynamic set of IoT devices and services that temporarily connect and cooperate to achieve a specific goal. Several approaches have been proposed to engineer goal-driven and self-adaptive IoT systems. However, none of the existing approaches enable goal-driven IoT systems to automatically detect security threats and autonomously adapt to mitigate them. Toward bridging these gaps, this paper proposes a distributed architectural Approach for engineering goal-driven IoT Systems that can autonomously SElf-adapt to secuRity Threats in their environments (ASSERT). ASSERT exploits techniques and adopts notions, such as agents, federated learning, feedback loops, and blockchain, for maintaining the systems’ security and enhancing the trustworthiness of the adaptations they perform. The results of the experiments that we conducted to validate the approach’s feasibility show that it performs and scales well when detecting security threats, performing autonomous security adaptations to mitigate the threats and enabling systems’ constituents to learn about security threats in their environments collaboratively. Full article
(This article belongs to the Special Issue Applications of Simulation for Engineering Intelligent IoT Systems)
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