This literature survey provides an overview on the current state of the practice for real-time embedded healthcare monitoring systems. These technologies enable healthcare systems to keep a constant eye on patients, collecting vital health data. They can send alerts and insights to healthcare providers, allowing for faster and better care. Our survey includes an investigation on the rising use of artificial intelligence and deep learning along with the use of intelligent sensors for capturing and analyzing data in real-time health monitoring systems. We also examine the current state of connected embedded health monitoring systems via, e.g. the Internet of Things (IoT). Wireless sensor networks and Tele-Health technologies are also addressed as they are instrumental in enhancing the precision, accessibility, and real-time nature of health data, ensuring that both patients and providers are always connected. Our survey discusses the applications and advantages associated with these technologies, providing valuable insights into their role in enhancing patient care, decision support, and tracking. Additionally, we navigate through the challenges, seeking pathways to mitigate them, and ensuring that the technology is inclusive, secure, and efficient. By examining the latest research and innovations, this survey aims to illuminate the current state of real-time healthcare monitoring and guide future advancements in this critical field.

Model-based engineering (MBE) in industry is on the rise. However, improvements are still needed on the oversight and management of MBE efforts. Frequently, program managers and high level decision makers do not have background in MBE to understand models, the value the models are providing, and if they are successfully achieving their MBE goals. To address these concerns in our previous research we developed a rating scale for models, called Model Assurance Levels (MALs). A MAL level is used to concisely express the assurance the model is providing to the program, as well as, risks associated with the model. However, for MAL level to be effective and meaningful, they need to be consistently determined regardless of who is performing the assessment. Therefore, this paper describes a quantitative and repeatable approach for computing MAL levels for software models.

The past decade has seen explosive growth in the use of small satellites. Within this domain, there has been a growing trend to place more responsibility on the flight software (versus hardware) and an increasing adoption of consumer-grade microprocessors to satisfy this desire for increased processing capability while still minimizing size, weight, and power parameters. These consumer-grade processors, however, are more susceptible to cosmic radiation and the occurrence of single event upsets. In this paper, we examine software-centric checks to detect the occurrence of such upset events in modern microprocessors.

This paper describes a preliminary investigation into the effect of multicore technology on the performance of real-time systems. In particular, it investigates the impact of varying the number of cores on multitasking performance and on different task configurations. Experimental results are presented for a real-time game application executing with several different hardware and software configurations.

Space flight software continues to experience exponential growth as functionality migrates from hardware to software. The resulting complexity of these mission critical systems demands new approaches to software systems engineering in order to effectively manage the development efforts and ensure that reliability is not compromised. Model-based systems/software engineering (MBE) approaches present attractive solutions to address the size and complexity through abstraction and analytical models. However, there are many challenges that must be addressed before MBE approaches can be effectively adopted on a large scale across an entire system. In this paper, we discuss some of the key motivators and challenges based on our experiences with flight software programs employing elements of MBE.

Spaceflight software continues to experience exponential growth as functionality migrates from hardware to software. The resulting complexity of these mission critical systems demands new approaches to software systems engineering in order to effectively manage the development efforts and ensure that reliability is not compromised. Model-based systems /software engineering (MBE) approaches present attractive solutions to address the size and complexity through abstraction and analytical models. However, there are many challenges that must be addressed before MBE approaches can be effectively adopted on a large scale across an entire system. In this position paper, we highlight some of the key challenges based on our experiences with flight software programs employing elements of MBE.

This paper describes an integrated approach for the design and subsequent behavioral analysis of concurrent software designs for embedded systems. The approach integrates software design using the COMET concurrent object-oriented design method, colored Petri net (CPN) modeling, and performance measurement of the target system. The approach combines information from platform-independent and platform-specific models to construct analyses of software architectures for embedded systems. It allows an engineer/analyst to examine behavioral and performance properties of a software architecture design paired with a candidate implementation architecture. Applying the behavioral design patterns in the UML-based design along with corresponding CPN templates, the results from the analyses can be directly mapped back to the original design artifacts. The approach is illustrated using a robot controller case study

In many software development projects, performance requirements are not addressed until after the application is developed or deployed, resulting in costly changes to the software or the acquisition of expensive high-performance hardware. To remedy this, researchers have developed model-driven performance analysis techniques for assessing how well performance requirements are being satisfied early in the software lifecycle. In some cases, companies may not have the expertise to perform such analysis on their software; therefore they have an independent assessor perform the analysis. This paper describes an approach for conducting independent model-driven software performance assessments of UML 2.0 designs and illustrates this approach using a real-time signal generator as a case study

Object-oriented software development practices are being rapidly adopted within increasingly complex systems, including reactive, real-time and concurrent system applications. While data modeling is performed very well under current object-oriented development practices, behavioral modeling necessary to capture critical information in real-time, reactive, and concurrent systems is often lacking. Addressing this deficiency, we offer an approach for modeling and analyzing concurrent object-oriented software designs through the use of behavioral design patterns, allowing us to map stereotyped UML objects to colored Petri net (CPN) representations in the form of reusable templates. The resulting CPNs are then used to model and analyze behavioral properties of the software architecture, applying the results of the analysis to the original software design.

Object-oriented software development practices are being rapidly adopted within increasingly complex systems, including reactive, real-time and concurrent system applications. While data modeling is performed very well under current object-oriented development practices, behavioral modeling necessary to capture critical information in real-time, reactive, and concurrent systems is often lacking. Addressing this deficiency, we offer an approach for modeling and analyzing concurrent object-oriented software designs through the use of behavioral patterns captured through colored Petri nets

This paper provides a series of lessons learned with respect to using performance modeling and analysis techniques on designs of object-oriented software systems. Specifically it focuses on the application of the Unified Modeling Language (UML) profile for schedulability performance, and time (SPT) paired with statistical simulation and coloured Petri nets (CPNs). The experiences captured in this paper are based on observations from an empirical study evaluating these techniques

To address behavioral modeling issues specific to concurrent software architectures, this paper outlines an approach for systematically modeling behavioral patterns found in concurrent software designs by applying colored Petri net (CPN) templates with UML artifacts. In this approach, CPNs are used as an underlying representation of the dynamic object-oriented architecture. These CPNs are then used to provide a simulated functional flow of the architecture and to analyze the concurrent behavior. By applying the results from the CPN analysis to the original UML model, an engineer can enhance the quality of the design and thereby gain additional insight to the behavioral properties of the software design prior to implementation.

This paper describes on-going efforts to integrate Petri nets with software design methods for concurrent and real time systems. Specifically, this paper presents an approach for integrating colored Petri nets with the Ada-based Design Approach for Real-Time Systems (ADARTS/sup SM/) and its sister method, CODARTS (Concurrent Design Approach for Real-Time Systems).