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Sensors
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Performance, Reliability and Scalability of IoT Systems
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Performance, Reliability and Scalability of 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 May 2022) | Viewed by 8941

Special Issue Editors

Prof. Andrea Marin

E-Mail Website
Guest Editor
Department of Environmental Sciences, Informatics and Statistics (DAIS), Università Ca' Foscari of Venice, 30172 Venezia Mestre, Italy
Interests: network modeling; performance evaluation; underwater sensor networks; simulation
Special Issues, Collections and Topics in MDPI journals
Prof. Dieter Fiems

E-Mail Website
Guest Editor
Departement of Telecommunications and Information Processing, Ghent University, St-Pietersnieuwstraat 41, 9000 Gent, Belgium
Interests: queueing analysis; wireless networks; epidemics; optical buffers

Special Issue Information

Dear Colleagues,

The development of IoT systems poses serious problems in terms of quality of service (QoS) assurance. The availability of massive amounts of data collected by heterogenous sensors, the need for their analysis, and the demand of quick reactions at the occurrence of certain events make the design of such systems quite challenging. In many cases, these requirements conflict with the need for low-cost and low-power consumption of most of the devices. Furthermore, the scalability of the devised solutions must be considered, since workloads may depend on many unpredictable factors that can generate peaks of resource demands. This can undermine the availability of the services due to saturation of the system’s service capacity.

For these reasons, performance and reliability modeling, analysis, and simulation as well as on-field measurements play crucial roles in the design of IoT systems.

This Special Issue welcomes either methodological, applicative or experimental contributions with respect (but not limited) to the following areas of interest:

  • Performance and scalability of the communication protocols;
  • Reliability of communication systems and of systems in general;
  • Data offloading policies;
  • Quantitative analysis of interactions with fog computing and cloud architectures;
  • Workload characterization in IoT;
  • Design of new energy-aware communication protocols for sensor nodes;
  • Development of models for the early evaluation of IoT system performance and reliability properties.

Prof. Andrea Marin
Prof. Dieter Fiems
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

  • IoT
  • performance evaluation
  • reliability analysis
  • sensor networks
  • fog computing

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Published Papers (3 papers)

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Research

27 pages, 1879 KiB  
Article
FaTEMa: A Framework for Multi-Layer Fault Tolerance in IoT Systems
by Mário Melo and Gibeon Aquino
Sensors 2021, 21(21), 7181; https://doi.org/10.3390/s21217181 - 29 Oct 2021
Cited by 4 | Viewed by 2887
Abstract
Fault tolerance in IoT systems is challenging to overcome due to its complexity, dynamicity, and heterogeneity. IoT systems are typically designed and constructed in layers. Every layer has its requirements and fault tolerance strategies. However, errors in one layer can propagate and cause [...] Read more.
Fault tolerance in IoT systems is challenging to overcome due to its complexity, dynamicity, and heterogeneity. IoT systems are typically designed and constructed in layers. Every layer has its requirements and fault tolerance strategies. However, errors in one layer can propagate and cause effects on others. Thus, it is impractical to consider a centralized fault tolerance approach for an entire system. Consequently, it is vital to consider multiple layers in order to enable collaboration and information exchange when addressing fault tolerance. The purpose of this study is to propose a multi-layer fault tolerance approach, granting interconnection among IoT system layers, allowing information exchange and collaboration in order to attain the property of dependability. Therefore, we define an event-driven framework called FaTEMa (Fault Tolerance Event Manager) that creates a dedicated fault-related communication channel in order to propagate events across the levels of the system. The implemented framework assist with error detection and continued service. Additionally, it offers extension points to support heterogeneous communication protocols and evolve new capabilities. Our empirical results show that introducing FaTEMa provided improvements to the error detection and error resolution time, consequently improving system availability. In addition, the use of Fatema provided a reliability improvement and a reduction in the number of failures produced. Full article
(This article belongs to the Special Issue Performance, Reliability and Scalability of IoT Systems)
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21 pages, 944 KiB  
Article
Optimization-Based Approaches for Minimizing Deployment Costs for Wireless Sensor Networks with Bounded Estimation Errors
by Chiu-Han Hsiao, Frank Yeong-Sung Lin, Hao-Jyun Yang, Yennun Huang, Yu-Fang Chen, Ching-Wen Tu and Si-Yao Zhang
Sensors 2021, 21(21), 7121; https://doi.org/10.3390/s21217121 - 27 Oct 2021
Cited by 1 | Viewed by 2369
Abstract
As wireless sensor networks have become more prevalent, data from sensors in daily life are constantly being recorded. Due to cost or energy consumption considerations, optimization-based approaches are proposed to reduce deployed sensors and yield results within the error tolerance. The correlation-aware method [...] Read more.
As wireless sensor networks have become more prevalent, data from sensors in daily life are constantly being recorded. Due to cost or energy consumption considerations, optimization-based approaches are proposed to reduce deployed sensors and yield results within the error tolerance. The correlation-aware method is also designed in a mathematical model that combines theoretical and practical perspectives. The sensor deployment strategies, including XGBoost, Pearson correlation, and Lagrangian Relaxation (LR), are determined to minimize deployment costs while maintaining estimation errors below a given threshold. Moreover, the results significantly ensure the accuracy of the gathered information while minimizing the cost of deployment and maximizing the lifetime of the WSN. Furthermore, the proposed solution can be readily applied to sensor distribution problems in various fields. Full article
(This article belongs to the Special Issue Performance, Reliability and Scalability of IoT Systems)
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32 pages, 7384 KiB  
Article
Examining the Performance of Fog-Aided, Cloud-Centered IoT in a Real-World Environment
by Mohammed A. Aleisa, Abdullah Abuhussein, Faisal S. Alsubaei and Frederick T. Sheldon
Sensors 2021, 21(21), 6950; https://doi.org/10.3390/s21216950 - 20 Oct 2021
Cited by 4 | Viewed by 2357
Abstract
The fog layer provides substantial benefits in cloud-based IoT applications because it can serve as an aggregation layer and it moves the computation resources nearer to the IoT devices; however, it is important to ensure adequate performance is achieved in such applications, as [...] Read more.
The fog layer provides substantial benefits in cloud-based IoT applications because it can serve as an aggregation layer and it moves the computation resources nearer to the IoT devices; however, it is important to ensure adequate performance is achieved in such applications, as the devices usually communicate frequently and authenticate with the cloud. This can cause performance and availability issues, which can be dangerous in critical applications such as in the healthcare sector. In this paper, we analyze the efficacy of the fog layer in different architectures in a real-world environment by examining performance metrics for the cloud and fog layers using different numbers of IoT devices. We also implement the fog layer using two methods to determine whether different fog implementation frameworks can affect the performance. The results show that including a fog layer with semi-heavyweight computation capability results in higher capital costs, although the in the long run resources, time, and money are saved. This study can serve as a reference for fundamental fog computing concepts. It can also be used to walk practitioners through different implementation frameworks of fog-aided IoT and to show tradeoffs in order to inform when to use each implementation framework based on one’s objectives. Full article
(This article belongs to the Special Issue Performance, Reliability and Scalability of IoT Systems)
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