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Real-time design patterns for the verification of safety-critical embedded systems in model-based approach
The development of safety-critical real-time embedded systems (RTESs) is a difficult task. Indeed, in addition to functional requirements, these...
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Early anomaly detection in time series: a hierarchical approach for predicting critical health episodes
The early detection of anomalous events in time series data is essential in many domains of application. In this paper we deal with critical health...
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Applications of Real-Time Database Systems
This chapter explores the wide range of applications where real-time databases play a crucial role in managing and processing time-sensitive data. It...
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Refined Limit Theorems for the Critical Continuous-Time Markov Branching Systems
We consider a critical homogeneous-continuous-time Markov branching system, i.e. the average value of the branching rate is zero. Our basic...
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Customized Slicing for Industrial Applications
Wireless networks are required to provide mobile ultra-reliable and low-latency services for applications in vertical industries, promoting the...
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Robust-PAC time-critical workflow offloading in edge-to-cloud continuum among heterogeneous resources
Edge-to-cloud continuum connects and extends the calculation from edge side via network to cloud platforms, where diverse workflows go back and...
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Evaluating virtualization for fog monitoring of real-time applications in mixed-criticality systems
Technological advances in embedded systems and the advent of fog computing led to improved quality of service of applications of cyber-physical...
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ArkGPU: enabling applications’ high-goodput co-location execution on multitasking GPUs
With the development of deep learning, hardware accelerators represented by GPUs have been used to accelerate the execution of deep learning...
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An Edge Cloud Based Coordination Platform for Multi-user AR Applications
Augmented Reality (AR) applications can reshape our society enabling novel ways of interactions and immersive experiences in many fields. However,...
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Integration of Synergetic IoT Applications with Heterogeneous Format Data for Interoperability Using IBM ACE
Data interoperability is a crucial requirement in IoT to improve services and enhance business opportunities and innovation. Integrating synergetic...
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Mobi-Sense: mobility-aware sensor-fog paradigm for mission-critical applications using network coding and steganography
Mission-critical applications refer to the real-time applications, which require fast and secure service provisioning, such as defense sector and...
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AppChainer: investigating the chainability among payloads in android applications
Statistics show that more than 80 applications are installed on each android smartphone. Vulnerability research on Android applications is of...
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FT-EALU: fault-tolerant arithmetic and logic unit for critical embedded and real-time systems
This paper presents a fault-tolerant ALU (“FT-EALU”) based on time redundancy and reward/punishment-based learning approaches for real-time embedded...
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Securing Laravel Applications
In the previous chapter, we delved into the crucial realm of advanced third-party integrations in Laravel, expanding the functionalities of our...
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Scaling Laravel Applications
In the previous chapter, we delved into the essential aspects of performance monitoring and debugging in Laravel, ensuring the efficiency and...
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AMAS: Adaptive auto-scaling for edge computing applications
Edge computing offers a promising approach to building on-demand computing infrastructure, leveraging clusters of small, commodity-scale,...
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An online ensemble method for auto-scaling NFV-based applications in the edge
The synergy of edge computing and Machine Learning (ML) holds immense potential for revolutionizing Internet of Things (IoT) applications,...
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Securing Augmented Reality Applications
Augmented Reality (AR) applications are becoming increasingly popular and are being used in various fields, including education, entertainment, and...
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Chebyshev approximation technique: analysis and applications
In many situations, exact solutions to complex problems may be challenging or impossible to obtain, making approximation techniques necessary for...
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Machine and deep learning for longitudinal biomedical data: a review of methods and applications
Exploiting existing longitudinal data cohorts can bring enormous benefits to the medical field, as many diseases have a complex and multi-factorial...
