Performability Modeling of Distributed Systems and Its Formal Methods Representation

2021 ◽  
pp. 704-727
Author(s):  
Razib Hayat Khan
Keyword(s):  
Complex System ◽  
Quantitative Analysis ◽  
Functional Properties ◽  
Distributed System ◽  
System Performance ◽  
Early Stage ◽  
Behavioral Changes ◽  
Design Development ◽  
Modeling Framework ◽  
System Components

A distributed system is a complex system. Developing complex systems is a demanding task when attempting to achieve functional and non-functional properties such as synchronization, communication, fault tolerance. These properties impose immense complexities on the design, development, and implementation of the system that incur massive effort and cost. Therefore, it is vital to ensure that the system must satisfy the functional and non-functional properties. Once a distributed system is developed, it is very difficult and demanding to conduct any modification in its architecture. As a result, the quantitative analysis of a complex distributed system at the early stage of the development process is always an essential and intricate endeavor. To meet the above challenge, this chapter introduces an extensive framework for performability evaluation of a distributed system. The goal of the performability modeling framework is to consider the behavioral change of the system components due to failures. This reveals how such behavioral changes affect the system performance.

Performability Modeling of Distributed Systems and Its Formal Methods Representation

2020 ◽  
pp. 203-233
Author(s):  
Razib Hayat Khan
Keyword(s):  
Complex System ◽  
Quantitative Analysis ◽  
Functional Properties ◽  
Distributed System ◽  
System Performance ◽  
Early Stage ◽  
Behavioral Changes ◽  
Design Development ◽  
Modeling Framework ◽  
System Components

A distributed system is a complex system. Developing complex systems is a demanding task when attempting to achieve functional and non-functional properties such as synchronization, communication, fault tolerance. These properties impose immense complexities on the design, development, and implementation of the system that incur massive effort and cost. Therefore, it is vital to ensure that the system must satisfy the functional and non-functional properties. Once a distributed system is developed, it is very difficult and demanding to conduct any modification in its architecture. As a result, the quantitative analysis of a complex distributed system at the early stage of the development process is always an essential and intricate endeavor. To meet the above challenge, this chapter introduces an extensive framework for performability evaluation of a distributed system. The goal of the performability modeling framework is to consider the behavioral change of the system components due to failures. This reveals how such behavioral changes affect the system performance.

Utilizing UML, cTLA, and SRN

2015 ◽  
pp. 23-50
Author(s):  
Razib Hayat Khan
Keyword(s):  
Distributed System ◽  
Model Transformation ◽  
Performance Modeling ◽  
Early Stage ◽  
System Development ◽  
Transformation Process ◽  
Modeling Framework ◽  
Functional Description ◽  
Transformation Rules ◽  
Uml Specification

To meet the challenge of conducting quantitative analysis at the early stage of the system development process, this chapter introduces an extensive framework for performance modeling of a distributed system. The goal of the performance modeling framework is the assessment of the non-functional properties of the distributed system at an early stage based on the system's functional description and deployment mapping of service components over an execution environment. System's functional description with deployment mapping has been specified using UML. To analyze the correctness of the UML specification style, we have used temporal logic, specifically cTLA, to formalize the UML model. We have shown in detail how UML models are formalized by a set of cTLA processes and production rules. To conduct the performance evaluation of a distributed system, the UML model is transformed into analytic model SRN. We have specified an automated model transformation process to generate SRN model from UML, which is performed in an efficient and scalable way by the use of model transformation rules.

Tailoring Design Development and Ideation in Catering To Industry Demands

2017 ◽  
Vol 14 (1) ◽  
pp. 67
Author(s):  
Fadila Mohd Yusof ◽  
Azmir Mamat Nawi ◽  
Azhari Md Hashim ◽  
Ahmad Fazlan Ahmad Zamri ◽  
Abu Hanifa Ab Hamid ◽  
...  
Keyword(s):  
Teaching And Learning ◽  
Industrial Design ◽  
Protocol Analysis ◽  
Early Stage ◽  
Idea Generation ◽  
Learning Processes ◽  
Design Stage ◽  
Design Development ◽  
Conceptual Design Phase ◽  
Industry Practice

Design development is one of the processes in the teaching and learning of industrial design. This process is important during the early stage of ideas before continuing to the next design stage. This study was conducted to investigate the comparison between  academic  syllabus  and  industry  practices  whether  these  processes  are  highly dependent on the idea generation and interaction related to the designer or to the student itself. The data were gathered through an observation of industry practice during conceptual design phase, teaching and learning process in academic through Video Protocol Analysis (VPA) method and interviews with industry practitioners via structured and unstructured questionnaires. The data were analysed by using NVivo software in order to formulate the results. The findings may possibly contribute to the teaching and learning processes especially in the improvement of industrial design syllabus in order to meet the industry demands. Keywords: design development, industrial design, industry demands

scholarly journals Complex System Governance as a Framework for Asset Management

2021 ◽  
Vol 13 (15) ◽  
pp. 8502
Author(s):  
Polinpapilinho F. Katina ◽  
James C. Pyne ◽  
Charles B. Keating ◽  
Dragan Komljenovic
Keyword(s):  
Complex System ◽  
Performance Improvement ◽  
Asset Management ◽  
System Performance ◽  
Future Research ◽  
Complex Organizations ◽  
Potential Relationship ◽  
Structured Approach

Complex system governance (CSG) is an emerging field encompassing a framework for system performance improvement through the purposeful design, execution, and evolution of essential metasystem functions. The goal of this study was to understand how the domain of asset management (AsM) can leverage the capabilities of CSG. AsM emerged from engineering as a structured approach to organizing complex organizations to realize the value of assets while balancing performance, risks, costs, and other opportunities. However, there remains a scarcity of literature discussing the potential relationship between AsM and CSG. To initiate the closure of this gap, this research reviews the basics of AsM and the methods associated with realizing the value of assets. Then, the basics of CSG are provided along with how CSG might be leveraged to support AsM. We conclude the research with the implications for AsM and suggested future research.

Predicting Graceful Extensibility of Human-Machine Systems: A New Analysis Method for Evaluating Extensibility Plots to Anticipate Distributed System Performance

2020 ◽  
Vol 64 (1) ◽  
pp. 313-318
Author(s):  
Dane A. Morey ◽  
Jesse M. Marquisee ◽  
Ryan C. Gifford ◽  
Morgan C. Fitzgerald ◽  
Michael F. Rayo
Keyword(s):  
Artificial Intelligence ◽  
Distributed System ◽  
System Performance ◽  
Healthcare Setting ◽  
Evaluation Methods ◽  
Performance Data ◽  
Analysis Method ◽  
Machine System ◽  
Machine Systems

With all of the research and investment dedicated to artificial intelligence and other automation technologies, there is a paucity of evaluation methods for how these technologies integrate into effective joint human-machine teams. Current evaluation methods, which largely were designed to measure performance of discrete representative tasks, provide little information about how the system will perform when operating outside the bounds of the evaluation. We are exploring a method of generating Extensibility Plots, which predicts the ability of the human-machine system to respond to classes of challenges at intensities both within and outside of what was tested. In this paper we test and explore the method, using performance data collected from a healthcare setting in which a machine and nurse jointly detect signs of patient decompensation. We explore the validity and usefulness of these curves to predict the graceful extensibility of the system.

scholarly journals EEG Fractal Analysis Reflects Brain Impairment after Stroke

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 592
Author(s):  
Maria Rubega ◽  
Emanuela Formaggio ◽  
Franco Molteni ◽  
Eleonora Guanziroli ◽  
Roberto Di Marco ◽  
...  
Keyword(s):  
Early Stage ◽  
Brain Activity ◽  
Phase 1 ◽  
Behavioral Changes ◽  
Stroke Survivors ◽  
Eeg Signals ◽  
Novel Treatments ◽  
Fractal Measures ◽  
Underlying Mechanisms ◽  
Random Fluctuations

Stroke is the commonest cause of disability. Novel treatments require an improved understanding of the underlying mechanisms of recovery. Fractal approaches have demonstrated that a single metric can describe the complexity of seemingly random fluctuations of physiological signals. We hypothesize that fractal algorithms applied to electroencephalographic (EEG) signals may track brain impairment after stroke. Sixteen stroke survivors were studied in the hyperacute (<48 h) and in the acute phase (∼1 week after stroke), and 35 stroke survivors during the early subacute phase (from 8 days to 32 days and after ∼2 months after stroke): We compared resting-state EEG fractal changes using fractal measures (i.e., Higuchi Index, Tortuosity) with 11 healthy controls. Both Higuchi index and Tortuosity values were significantly lower after a stroke throughout the acute and early subacute stage compared to healthy subjects, reflecting a brain activity which is significantly less complex. These indices may be promising metrics to track behavioral changes in the very early stage after stroke. Our findings might contribute to the neurorehabilitation quest in identifying reliable biomarkers for a better tailoring of rehabilitation pathways.

scholarly journals Blockchain Applications in Agribusiness: A Systematic Review

2021 ◽  
Vol 13 (4) ◽  
pp. 95
Author(s):  
Geneci da Silva Ribeiro Rocha ◽  
Letícia de Oliveira ◽  
Edson Talamini
Keyword(s):  
Complex System ◽  
Systematic Review ◽  
Web Of Science ◽  
Scientific Literature ◽  
Early Stage ◽  
Technological Development ◽  
Economic Sectors ◽  
Future Studies ◽  
Blockchain Technology ◽  
Near Future

Blockchain is a technology that can be applied in different sectors to solve various problems. As a complex system, agribusiness presents many possibilities to take advantage of blockchain technology. The main goal of this paper is to identify the purposes for which blockchain has been applied in the agribusiness sector, for which a PRISMA-based systematic review was carried out. The scientific literature corpus was accessed and selected from Elsevier’s Scopus and ISI of Knowledge’s Web of Science (WoS) platforms, using the PRISMA protocol procedures. Seventy-one articles were selected for analysis. Blockchain application in agribusiness is a novel topic, with the first publication dating from 2016. The technological development prevails more than blockchain applications since it has been addressed mainly in the Computer Sciences and Engineering. Blockchain applications for agribusiness management of financial, energy, logistical, environmental, agricultural, livestock, and industrial purposes have been reported in the literature. The findings suggest that blockchain brings many benefits when used in agribusiness supply chains. We concluded that the research on blockchain applications in agribusiness is only at an early stage, as many prototypes are being developed and tested in the laboratory. In the near future, blockchain will be increasingly applied across all economic sectors, including agribusiness, promoting greater reliability and agility in information with a reduced cost. Several gaps for future studies were observed, with significant value for science, industry, and society.

scholarly journals Complexity Analysis of Escher’s Art

Entropy ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. 553 ◽  
Author(s):  
António M. Lopes ◽  
J. A. Tenreiro Machado
Keyword(s):  
Complex System ◽  
Quantitative Analysis ◽  
Complexity Analysis ◽  
Quantitative Characterization ◽  
Cultural Economic ◽  
Scaling Technique ◽  
Artistic Production ◽  
Formidable Challenge ◽  
Visualization Techniques

Art is the output of a complex system based on the human spirit and driven by several inputs that embed social, cultural, economic and technological aspects of a given epoch. A solid quantitative analysis of art poses considerable difficulties and reaching assertive conclusions is a formidable challenge. In this paper, we adopt complexity indices, dimensionality-reduction and visualization techniques for studying the evolution of Escher’s art. Grayscale versions of 457 artworks are analyzed by means of complexity indices and represented using the multidimensional scaling technique. The results are correlated with the distinct periods of Escher’s artistic production. The time evolution of the complexity and the emergent patterns demonstrate the effectiveness of the approach for a quantitative characterization of art.

scholarly journals Nonwearable Sensor-Based In-Home Assessment of Subtle Daily Behavioral Changes as a Candidate Biomarker for Mild Cognitive Impairment

2021 ◽  
Vol 12 (1) ◽  
pp. 11
Author(s):  
Takao Yamasaki ◽  
Shuzo Kumagai
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Early Stage ◽  
Digital Technologies ◽  
Assessment Methods ◽  
Behavioral Changes ◽  
Behavioral Patterns ◽  
Traditional Assessment ◽  
Traditional Performance ◽  
Traditional Assessments

Patients show subtle changes in daily behavioral patterns, revealed by traditional assessments (e.g., performance- or questionnaire-based assessments) even in the early stage of Alzheimer’s disease (AD; i.e., the mild cognitive impairment (MCI) stage). An increase in studies on the assessment of daily behavioral changes in patients with MCI and AD using digital technologies (e.g., wearable and nonwearable sensor-based assessment) has been noted in recent years. In addition, more objective, quantitative, and realistic evidence of altered daily behavioral patterns in patients with MCI and AD has been provided by digital technologies rather than traditional assessments. Therefore, this study hypothesized that the assessment of daily behavioral changes with digital technologies can replace or assist traditional assessment methods for early MCI and AD detection. In this review, we focused on research using nonwearable sensor-based in-home assessment. Previous studies on the assessment of behavioral changes in MCI and AD using traditional performance- or questionnaire-based assessments are first described. Next, an overview of previous studies on the assessment of behavioral changes in MCI and AD using nonwearable sensor-based in-home assessment is provided. Finally, the usefulness and problems of nonwearable sensor-based in-home assessment for early MCI and AD detection are discussed. In conclusion, this review stresses that subtle changes in daily behavioral patterns detected by nonwearable sensor-based in-home assessment can be early MCI and AD biomarkers.

scholarly journals Biased Information Passing Between Subsystems Over Time in Complex System Design

2015 ◽  
Vol 138 (1) ◽  
Author(s):  
Jesse Austin-Breneman ◽  
Bo Yang Yu ◽  
Maria C. Yang
Keyword(s):  
Complex System ◽  
System Design ◽  
Large Scale ◽  
Early Stage ◽  
Systems Design ◽  
System Level ◽  
Worst Case ◽  
Early Stage Design ◽  
Complex System Design ◽  
Biased Information

During the early stage design of large-scale engineering systems, design teams are challenged to balance a complex set of considerations. The established structured approaches for optimizing complex system designs offer strategies for achieving optimal solutions, but in practice suboptimal system-level results are often reached due to factors such as satisficing, ill-defined problems, or other project constraints. Twelve subsystem and system-level practitioners at a large aerospace organization were interviewed to understand the ways in which they integrate subsystems in their own work. Responses showed subsystem team members often presented conservative, worst-case scenarios to other subsystems when negotiating a tradeoff as a way of hedging against their own future needs. This practice of biased information passing, referred to informally by the practitioners as adding “margins,” is modeled in this paper with a series of optimization simulations. Three “bias” conditions were tested: no bias, a constant bias, and a bias which decreases with time. Results from the simulations show that biased information passing negatively affects both the number of iterations needed and the Pareto optimality of system-level solutions. Results are also compared to the interview responses and highlight several themes with respect to complex system design practice.

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