Systems Simulation and Modelling for IoT Data Processing Applications
A special issue of Multimodal Technologies and Interaction (ISSN 2414-4088).
Deadline for manuscript submissions: closed (30 August 2022) | Viewed by 6780
Special Issue Editors
Interests: medical imaging; healthcare; AI; deep learning
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; medical sensor; image processing; deep learning
Special Issues, Collections and Topics in MDPI journals
Interests: CT; machine learning; deep learning; tumor classification; medical images segmentation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
System simulation and modeling (SSM) focus on solving problems through the use of models and simulations. SSM is used in almost every science and engineering involving a multidisciplinary nature. SSM develops frameworks that are applicable across disciplines and develop benchmark tools that are useful in developing IoT data processing applications. Modeling theories need to be transformed into consistent frameworks, which in turn are implemented into consistent benchmarks. The world is clearly in the era of internet data processing (e.g., Internet of Things). The challenge for IoT data processing systems is balancing operation and cost tradeoffs by optimizing configuration at both the IoT hardware and software layers to accommodate users’ constraints. For example, several internet data processing application developers and researchers can perform tests in a controllable and repeatable manner. Propelled by the need to analyze the performance of different IoT data processing and Industry 4.0 frameworks, researchers have introduced several IoT simulation and modeling benchmarks. Despite the substantial progress achieved, however, the research community still needs a holistic comprehensive simulation and modeling platforms for IoT data processing. This Special Issue aspires to furnish a compendium of high-quality research articles on the following specific areas of interest, including but not limited to:
- Theoretical aspects of modeling and simulation, including formal modeling, model-checking, sensitivity analysis, Monte Carlo methods, variance reduction techniques, experimental design, meta-modeling, methods and algorithms for validation and verification, and selection and comparison procedures;
- Development of discrete event simulation benchmarks to evaluate workloads in heterogeneous state-of-the-art hardware platforms;
- Advances in modeling and simulation tools for performance evaluation, security problems, and scalable IoT data processing environments;
- Cognitive combined discrete and continuous simulations based on both IoT hardware and software;
- Cognitive interactive modeling for internet data processing;
- Methodology and requirements of benchmarking IoT data processing and Industry 4.0;
- Data-driven cognitive computing for industrial IoT;
- Advances in Industry 4.0 frameworks and benchmarks for large-scale data analytics;
- IoT data processing frameworks for industrial predictive analytics.
Dr. J Dinesh Peter
Dr. Yu-Dong Zhang
Dr. Steven L. Fernandes
Guest Editors
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Keywords
- Simulation and modeling
- Internet of Things
- Data processing
- Cognitive computing
- Industry 4.0
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