Qos Based Optimization Of Runtime Management Of Sensing Cloud Applications
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QoS-Based Optimization of Runtime Management of Sensing Cloud Applications by Gotin, Manuel Pdf
IoT applications perceive and interact with the environment via smart devices and cloud services. When operating such applications one is faced with the challenge of configuring the smart devices and the cloud services in a manner, which achieves a high data quality at low operational costs. This work supports IoT operators with IoT collection strategies and cost optimization functions for data qualities, which are influenced by the interplay of smart device and cloud service configurations.
A Reference Structure for Modular Model-based Analyses by Koch, Sandro Giovanni Pdf
In this work, the authors analysed the co-dependency between models and analyses, particularly the structure and interdependence of artefacts and the feature-based decomposition and composition of model-based analyses. Their goal is to improve the maintainability of model-based analyses. They have investigated the co-dependency of Domain-specific Modelling Languages (DSMLs) and model-based analyses regarding evolvability, understandability, and reusability.
Evaluating Architectural Safeguards for Uncertain AI Black-Box Components by Scheerer, Max Pdf
Although tremendous progress has been made in Artificial Intelligence (AI), it entails new challenges. The growing complexity of learning tasks requires more complex AI components, which increasingly exhibit unreliable behaviour. In this book, we present a model-driven approach to model architectural safeguards for AI components and analyse their effect on the overall system reliability.
Consistent View-Based Management of Variability in Space and Time by Ananieva, Sofia Pdf
Developing variable systems faces many challenges. Dependencies between interrelated artifacts within a product variant, such as code or diagrams, across product variants and across their revisions quickly lead to inconsistencies during evolution. This work provides a unification of common concepts and operations for variability management, identifies variability-related inconsistencies and presents an approach for view-based consistency preservation of variable systems.
Architecture-based Evolution of Dependable Software-intensive Systems by Heinrich, Robert Pdf
This cumulative habilitation thesis, proposes concepts for (i) modelling and analysing dependability based on architectural models of software-intensive systems early in development, (ii) decomposition and composition of modelling languages and analysis techniques to enable more flexibility in evolution, and (iii) bridging the divergent levels of abstraction between data of the operation phase, architectural models and source code of the development phase.
Architectural Data Flow Analysis for Detecting Violations of Confidentiality Requirements by Seifermann, Stephan Pdf
Software vendors must consider confidentiality especially while creating software architectures because decisions made here are hard to change later. Our approach represents and analyzes data flows in software architectures. Systems specify data flows and confidentiality requirements specify limitations of data flows. Software architects use detected violations of these limitations to improve the system. We demonstrate how to integrate our approach into existing development processes.
Architectural Alignment of Access Control Requirements Extracted from Business Processes by Pilipchuk, Roman Pdf
Business processes and information systems evolve constantly and affect each other in non-trivial ways. Aligning security requirements between both is a challenging task. This work presents an automated approach to extract access control requirements from business processes with the purpose of transforming them into a) access permissions for role-based access control and b) architectural data flow constraints to identify violations of access control in enterprise application architectures.
Software Engineering Aspects of Continuous Development and New Paradigms of Software Production and Deployment by Jean-Michel Bruel,Manuel Mazzara,Bertrand Meyer Pdf
This book constitutes revised selected papers of the Second International Workshop on Software Engineering Aspects of Continuous Development and New Paradigms of Software Production and Deployment, DEVOPS 2019, held at the Château de Villebrumier, France, in May 2019. The 15 papers presented in this volume were carefully reviewed and selected from 19 submissions. They cover a wide range of problems arising from DevOps and related approaches: current tools, rapid development-deployment processes, modeling frameworks, anomaly detection in software releases, DevDataOps, microservices, and related topics.
Temporal QOS Management in Scientific Cloud Workflow Systems by Xiao Liu,Jinjun Chen,Yun Yang Pdf
Cloud computing can provide virtually unlimited scalable high performance computing resources. Cloud workflows often underlie many large scale data/computation intensive e-science applications such as earthquake modelling, weather forecasting and astrophysics. During application modelling, these sophisticated processes are redesigned as cloud workflows, and at runtime, the models are executed by employing the supercomputing and data sharing ability of the underlying cloud computing infrastructures. Temporal QOS Management in Scientific Cloud Workflow Systems focuses on real world scientific applications which often must be completed by satisfying a set of temporal constraints such as milestones and deadlines. Meanwhile, activity duration, as a measurement of system performance, often needs to be monitored and controlled. This book demonstrates how to guarantee on-time completion of most, if not all, workflow applications. Offering a comprehensive framework to support the lifecycle of time-constrained workflow applications, this book will enhance the overall performance and usability of scientific cloud workflow systems. Explains how to reduce the cost to detect and handle temporal violations while delivering high quality of service (QoS) Offers new concepts, innovative strategies and algorithms to support large-scale sophisticated applications in the cloud Improves the overall performance and usability of cloud workflow systems
Crowdsourcing of Sensor Cloud Services by Azadeh Ghari Neiat,Athman Bouguettaya Pdf
This book develops a crowdsourced sensor-cloud service composition framework taking into account spatio-temporal aspects. This book also unfolds new horizons to service-oriented computing towards the direction of crowdsourced sensor data based applications, in the broader context of Internet of Things (IoT). It is a massive challenge for the IoT research field how to effectively and efficiently capture, manage and deliver sensed data as user-desired services. The outcome of this research will contribute to solving this very important question, by designing a novel service framework and a set of unique service selection and composition frameworks. Delivering a novel service framework to manage crowdsourced sensor data provides high-level abstraction (i.e., sensor-cloud service) to model crowdsourced sensor data from functional and non-functional perspectives, seamlessly turning the raw data into “ready to go” services. A creative indexing model is developed to capture and manage the spatio-temporal dynamism of crowdsourced service providers. Delivering novel frameworks to compose crowdsourced sensor-cloud services is vital. These frameworks focuses on spatio-temporal composition of crowdsourced sensor-cloud services, which is a new territory for existing service oriented computing research. A creative failure-proof model is also designed to prevent composition failure caused by fluctuating QoS. Delivering an incentive model to drive the coverage of crowdsourced service providers is also vital. A new spatio-temporal incentive model targets changing coverage of the crowdsourced providers to achieve demanded coverage of crowdsourced sensor-cloud services within a region. The outcome of this research is expected to potentially create a sensor services crowdsourcing market and new commercial opportunities focusing on crowdsourced data based applications. The crowdsourced community based approach adds significant value to journey planning and map services thus creating a competitive edge for a technologically-minded companies incentivizing new start-ups, thus enabling higher market innovation. This book primarily targets researchers and practitioners, who conduct research work in service oriented computing, Internet of Things (IoT), smart city and spatio-temporal travel planning, as well as advanced-level students studying this field. Small and Medium Entrepreneurs, who invest in crowdsourced IoT services and journey planning infrastructures, will also want to purchase this book.
Cloud Computing and Services Science by Markus Helfert,Donald Ferguson,Victor Méndez Muñoz,Jorge Cardoso Pdf
This book constitutes extended, revised and selected papers from the 6th International Conference on Cloud Computing and Services Science, CLOSER 2016, held in Rome, Italy, in April 2016. The 16 papers presented in this volume were carefully reviewed and selected from a total of 123 submissions. The volume also contains two invited papers. CLOSER 2016 focused on the emerging area of cloud computing, inspired by recent advances related to infrastructures, operations, and service availability through global networks. It also studied the influence of service science in this area.
Service Level Management in Emerging Environments by Anonim Pdf
Networks are now embedded in daily life thanks to smaller, faster, inexpensive components that are more powerful and increasingly connected. Parallel to this quantitative explosion of communication networks, technology has become more complex. This development comes with challenges related to management and control, and it has become necessary to manage the service level demands of the client to which the service provider commits. Different approaches to managing one or more service level components in different emerging environments are explored, such as: the Internet of Things, the Cloud, smart grids, e-health, mesh networking, D2D (Device to Device), smart cities and even green networking. This book therefore allows for a better understanding of the important challenges and issues relating to Quality of Service (QoS) management, security and mobility in these types of environment.
Handbook of Dynamic Data Driven Applications Systems by Frederica Darema,Erik P. Blasch,Sai Ravela,Alex J. Aved Pdf
This Second Volume in the series Handbook of Dynamic Data Driven Applications Systems (DDDAS) expands the scope of the methods and the application areas presented in the first Volume and aims to provide additional and extended content of the increasing set of science and engineering advances for new capabilities enabled through DDDAS. The methods and examples of breakthroughs presented in the book series capture the DDDAS paradigm and its scientific and technological impact and benefits. The DDDAS paradigm and the ensuing DDDAS-based frameworks for systems’ analysis and design have been shown to engender new and advanced capabilities for understanding, analysis, and management of engineered, natural, and societal systems (“applications systems”), and for the commensurate wide set of scientific and engineering fields and applications, as well as foundational areas. The DDDAS book series aims to be a reference source of many of the important research and development efforts conducted under the rubric of DDDAS, and to also inspire the broader communities of researchers and developers about the potential in their respective areas of interest, of the application and the exploitation of the DDDAS paradigm and the ensuing frameworks, through the examples and case studies presented, either within their own field or other fields of study. As in the first volume, the chapters in this book reflect research work conducted over the years starting in the 1990’s to the present. Here, the theory and application content are considered for: Foundational Methods Materials Systems Structural Systems Energy Systems Environmental Systems: Domain Assessment & Adverse Conditions/Wildfires Surveillance Systems Space Awareness Systems Healthcare Systems Decision Support Systems Cyber Security Systems Design of Computer Systems The readers of this book series will benefit from DDDAS theory advances such as object estimation, information fusion, and sensor management. The increased interest in Artificial Intelligence (AI), Machine Learning and Neural Networks (NN) provides opportunities for DDDAS-based methods to show the key role DDDAS plays in enabling AI capabilities; address challenges that ML-alone does not, and also show how ML in combination with DDDAS-based methods can deliver the advanced capabilities sought; likewise, infusion of DDDAS-like approaches in NN-methods strengthens such methods. Moreover, the “DDDAS-based Digital Twin” or “Dynamic Digital Twin”, goes beyond the traditional DT notion where the model and the physical system are viewed side-by-side in a static way, to a paradigm where the model dynamically interacts with the physical system through its instrumentation, (per the DDDAS feed-back control loop between model and instrumentation).
QoS Prediction in Cloud and Service Computing by Yilei Zhang,Michael R. Lyu Pdf
This book offers a systematic and practical overview of Quality of Service prediction in cloud and service computing. Intended to thoroughly prepare the reader for research in cloud performance, the book first identifies common problems in QoS prediction and proposes three QoS prediction models to address them. Then it demonstrates the benefits of QoS prediction in two QoS-aware research areas. Lastly, it collects large-scale real-world temporal QoS data and publicly releases the datasets, making it a valuable resource for the research community. The book will appeal to professionals involved in cloud computing and graduate students working on QoS-related problems.
Handbook of Dynamic Data Driven Applications Systems by Erik P. Blasch,Frederica Darema,Sai Ravela,Alex J. Aved Pdf
The Handbook of Dynamic Data Driven Applications Systems establishes an authoritative reference of DDDAS, pioneered by Dr. Darema and the co-authors for researchers and practitioners developing DDDAS technologies. Beginning with general concepts and history of the paradigm, the text provides 32 chapters by leading experts in ten application areas to enable an accurate understanding, analysis, and control of complex systems; be they natural, engineered, or societal: The authors explain how DDDAS unifies the computational and instrumentation aspects of an application system, extends the notion of Smart Computing to span from the high-end to the real-time data acquisition and control, and manages Big Data exploitation with high-dimensional model coordination. The Dynamically Data Driven Applications Systems (DDDAS) paradigm inspired research regarding the prediction of severe storms. Specifically, the DDDAS concept allows atmospheric observing systems, computer forecast models, and cyberinfrastructure to dynamically configure themselves in optimal ways in direct response to current or anticipated weather conditions. In so doing, all resources are used in an optimal manner to maximize the quality and timeliness of information they provide. Kelvin Droegemeier, Regents’ Professor of Meteorology at the University of Oklahoma; former Director of the White House Office of Science and Technology Policy We may well be entering the golden age of data science, as society in general has come to appreciate the possibilities for organizational strategies that harness massive streams of data. The challenges and opportunities are even greater when the data or the underlying system are dynamic - and DDDAS is the time-tested paradigm for realizing this potential. Sangtae Kim, Distinguished Professor of Mechanical Engineering and Distinguished Professor of Chemical Engineering at Purdue University
