Leveraging Virtualization for Performance Driven Development

This thesis contains the research component of a software engineering study to create a .NET application performance testing lab, and several guided learning activities intended to teach the fundamentals of how to use it. In arriving upon the research which serves as the groundwork for this project, an introduction to the concepts of software performance, the risks associated with performances, and an approach to mitigating this risks called performance driven development is presented. This introduction is expanded by an overview of how performance is affected from application, network, database and presentation aspects. To address problems associated with performance in .NET web applications, a virtual test lab has been created on the software engineering lab server at Regis University\u27s Academic Research Network (ARNe), and this paper documents the architecture of that test lab. In order to demonstrate how it can be used students, developers or others previously unfamiliar with performance testing, a series of presentations has been composed, and this paper represents the research conducted in composing them. This research includes a basic level understanding of Visual Studio Team System 2008\u27s test tools, and virtualization with VMWare

Analysis and Development of Instrument Software Paradigms: Conception and Implementation of a New Instrument Control and Data Acquisition System, Proven by Material Scientific Applications

During the last 50 years, the quality of analysis methods in many scientific disciplines has been enhanced by electronic applications, automation and data processing. While the features, performance and usability of these processes have been continually enhanced, it is conspicuous that the majority of institutes operate own proprietary software. This situation arises for both historical and financial reasons, plus a wish to retain autonomy fuelled by the requirement for a system that remains compatible with both new and legacy hardware. This thesis reviews the commonly used scientific software systems and their stakeholders and tries to identify generic problems. The demands on instrument systems are summarized by a requirement specification. Based on these requirements, a basic concept is developed that reflects the current state-of-the art in software design and which may provide a blueprint for instrument system architectures. The results are used to create a proof-of-concept implementation. Core to this approach is an application server that comes with a container, which makes use of the Inversion-of-Control pattern to loosely couple and execute components. These do not need to implement fixed interfaces and are thus decoupled from a specific use-case. Components can, for example, be proxies that control and acquire data from legacy hardware, perform calculations, provide a human-machine interface or act as storage. They are dynamically wired to experiments using XML-based Assembly files. Both Assemblies and Components can be published using a central store on a collaboration platform and shared by the community. This increases reusability and allows the use of existing Assemblies with new hardware by simply replacing the hardware proxy modules. Example components have been provided for the access to legacy and new instrument hardware, the storage of results in the NeXus format, data reduction, simulation with McStas, the execution of customizable scans and the visualization of data

Real-Time QoS Monitoring and Anomaly Detection on Microservice-based Applications in Cloud-Edge Infrastructure

Ph. D. Thesis.Microservices have emerged as a new approach for developing and deploying cloud applications that require higher levels of agility, scale, and reliability. A microservicebased cloud application architecture advocates decomposition of monolithic application components into independent software components called \microservices". As the independent microservices can be developed, deployed, and updated independently of each other, it leads to complex run-time performance monitoring and management challenges. The deployment environment for microservices in multi-cloud environments is very complex as there are numerous components running in heterogeneous environments (VM/container) and communicating frequently with each other using REST-based/REST-less APIs. In some cases, multiple components can also be executed inside a VM/container making any failure or anomaly detection very complicated. It is necessary to monitor the performance variation of all the service components to detect any reason for failure. Microservice and container architecture allows to design loose-coupled services and run them in a lightweight runtime environment for more e cient scaling. Thus, containerbased microservice deployment is now the standard model for hosting cloud applications across industries. Despite the strongest scalability characteristic of this model which opens the doors for further optimizations in both application structure and performance, such characteristic adds an additional level of complexity to monitoring application performance. Performance monitoring system can lead to severe application outages if it is not able to successfully and quickly detecting failures and localizing their causes. Machine learning-based techniques have been applied to detect anomalies in microservice-based cloud-based applications. The existing research works used di erent tracking algorithms to search the root cause if anomaly observed behaviour. However, linking the observed failures of an application with their root causes by the use of these techniques is still an open research problem. Osmotic computing is a new IoT application programming paradigm that's driven by the signi cant increase in resource capacity/capability at the network edge, along with support for data transfer protocols that enable such resources to interact more seamlessly with cloud-based services. Much of the di culty in Quality of Service (QoS) and performance monitoring of IoT applications in an osmotic computing environment is due to the massive scale and heterogeneity (IoT + edge + cloud) of computing environments. To handle monitoring and anomaly detection of microservices in cloud and edge datacenters, this thesis presents multilateral research towards monitoring and anomaly detection on microservice-based applications performance in cloud-edge infrastructure. The key contributions of this thesis are as following: • It introduces a novel system, Multi-microservices Multi-virtualization Multicloud monitoring (M3 ) that provides a holistic approach to monitor the performance of microservice-based application stacks deployed across multiple cloud data centers. • A framework forMonitoring, Anomaly Detection and Localization System (MADLS) which utilizes a simpli ed approach that depends on commonly available metrics o ering a simpli ed deployment environment for the developer. • Developing a uni ed monitoring model for cloud-edge that provides an IoT application administrator with detailed QoS information related to microservices deployed across cloud and edge datacenters.Royal Embassy of Saudi Arabia Cultural Bureau in London, government of Saudi Arabi

Rethinking the risk matrix

So far risk has been mostly defined as the expected value of a loss, mathematically PL (being P the probability of an adverse event and L the loss incurred as a consequence of the adverse event). The so called risk matrix follows from such definition. This definition of risk is justified in a long term “managerial” perspective, in which it is conceivable to distribute the effects of an adverse event on a large number of subjects or a large number of recurrences. In other words, this definition is mostly justified on frequentist terms. Moreover, according to this definition, in two extreme situations (high-probability/low-consequence and low-probability/high-consequence), the estimated risk is low. This logic is against the principles of sustainability and continuous improvement, which should impose instead both a continuous search for lower probabilities of adverse events (higher and higher reliability) and a continuous search for lower impact of adverse events (in accordance with the fail-safe principle). In this work a different definition of risk is proposed, which stems from the idea of safeguard: (1Risk)=(1P)(1L). According to this definition, the risk levels can be considered low only when both the probability of the adverse event and the loss are small. Such perspective, in which the calculation of safeguard is privileged to the calculation of risk, would possibly avoid exposing the Society to catastrophic consequences, sometimes due to wrong or oversimplified use of probabilistic models. Therefore, it can be seen as the citizen’s perspective to the definition of risk

Combining SOA and BPM Technologies for Cross-System Process Automation

This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation

Challenges for engineering students working with authentic complex problems

Engineers are important participants in solving societal, environmental and technical problems. However, due to an increasing complexity in relation to these problems new interdisciplinary competences are needed in engineering. Instead of students working with monodisciplinary problems, a situation where students work with authentic complex problems in interdisciplinary teams together with a company may scaffold development of new competences. The question is: What are the challenges for students structuring the work on authentic interdisciplinary problems? This study explores a three-day event where 7 students from Aalborg University (AAU) from four different faculties and one student from University College North Denmark (UCN), (6th-10th semester), worked in two groups at a large Danish company, solving authentic complex problems. The event was structured as a Hackathon where the students for three days worked with problem identification, problem analysis and finalizing with a pitch competition presenting their findings. During the event the students had workshops to support the work and they had the opportunity to use employees from the company as facilitators. It was an extracurricular activity during the summer holiday season. The methodology used for data collection was qualitative both in terms of observations and participants’ reflection reports. The students were observed during the whole event. Findings from this part of a larger study indicated, that students experience inability to transfer and transform project competences from their previous disciplinary experiences to an interdisciplinary setting

Exploring the practical use of a collaborative robot for academic purposes

This article presents a set of experiences related to the setup and exploration of potential educational uses of a collaborative robot (cobot). The basic principles that have guided the work carried out have been three. First and foremost, study of all the functionalities offered by the robot and exploration of its potential academic uses both in subjects focused on industrial robotics and in subjects of related disciplines (automation, communications, computer vision). Second, achieve the total integration of the cobot at the laboratory, seeking not only independent uses of it but also seeking for applications (laboratory practices) in which the cobot interacts with some of the other devices already existing at the laboratory (other industrial robots and a flexible manufacturing system). Third, reuse of some available components and minimization of the number and associated cost of required new components. The experiences, carried out following a project-based learning methodology under the framework of bachelor and master subjects and thesis, have focused on the integration of mechanical, electronic and programming aspects in new design solutions (end effector, cooperative workspace, artificial vision system integration) and case studies (advanced task programming, cybersecure communication, remote access). These experiences have consolidated the students' acquisition of skills in the transition to professional life by having the close collaboration of the university faculty with the experts of the robotics company.Postprint (published version