Adaptive Monitoring of Complex Software Systems using Management Metrics

Software systems supporting networked, transaction-oriented services are large and complex; they comprise a multitude of inter-dependent layers and components, and they implement many dynamic optimization mechanisms. In addition, these systems are subject to workload that is hard to predict. These factors make monitoring these systems as well as performing problem determination challenging and costly. In this thesis we tackle these challenges with the goal of lowering the cost and improving the effectiveness of monitoring and problem determination by reducing the dependence on human operators. Specifically, this thesis presents and demonstrates the effectiveness of an efficient, automated monitoring approach which enables detection of errors and failures, and which assists in localizing faults. Software systems expose various types of monitoring data; this thesis focuses on the use of management metrics to monitor a system's health. We devise a system modeling approach which entails modeling stable, statistical correlations among management metrics; these correlations characterize a system's normal behaviour This approach allows a system model to be built automatically and efficiently using the monitoring data alone. In order to control the monitoring overhead, and yet allow a system's health to be assessed reliably, we design an adaptive monitoring approach. This adaptive capability builds on the flexible nature of our system modeling approach, which allows the set of monitored metrics to be altered at runtime. We develop methods to automatically select management metrics to collect at the minimal monitoring level, without any domain knowledge. In addition, we devise an automated fault localization approach, which leverages the ability of the monitoring system to analyze individual metrics. Using a realistic, multi-tier software system, including different applications based on Java Enterprise Edition and industrial-strength products, we evaluate our system modeling approach. We show that stable metric correlations exist in complex software systems and that many of these correlations can be modeled using simple, efficient techniques. We investigate the effect of the collection of management metrics on system performance. We show that the monitoring overhead can be high and thus needs to be controlled. We employ fault injection experiments to evaluate the effectiveness of our adaptive monitoring and fault localization approach. We demonstrate that our approach is cost-effective, has high fault coverage and, in the majority of the cases studied, provides pertinent diagnosis information. The main contribution of this work is to show how to monitor complex software systems and determine problems in them automatically and efficiently. Our solution approach has wide applicability and the techniques we use are simple and yet effective. Our work suggests that the cost of monitoring software systems is not necessarily a function of their complexity, providing hope that the health of increasingly large and complex systems can be tracked with a limited amount of human resources and without sacrificing much system performance

NEW, MULTI-SCALE APPROACHES TO CHARACTERIZE PATTERNS IN VEGETATION, FUELS, AND WILDFIRE

Pattern and scale are key to understanding ecological processes. My dissertation research aims for novel quantification of vegetation, fuel, and wildfire patterns at multiple scales and to leverage these data for insights into fire processes. Core to this motivation is the 3-dimensional (3-D) characterization of forest properties from light detection and ranging (LiDAR) and structure-from-motion (SfM) photogrammetry. Analytical methods for extracting useable information currently lag the ability to collect such 3-D data. The chapters that follow focus on this limitation blending interests in machine learning and data science, remote sensing, wildland fuels (vegetation), and wildfire. In Chapter 2, forest canopy structure is characterized from multiple landscapes using LiDAR data and a novel data-driven framework to identify and compare structural classes. Motivations for this chapter include the desire to systematically assess forest structure from landscape to global scales and increase the utility of data collected by government agencies for landscape restoration planning. Chapter 3 endeavors to link 3-D canopy fuels attributes to conventional optical remote sensing data with the goal of extending the reach of laser measurements to the entire western US while exploring geographic differences in LiDAR-Landsat relationships. Development of predictive models and resulting datasets increase accuracy and spatial variation over currently used canopy fuel datasets. Chapters 4 and 5 characterize fire and fuel variability using unmanned aerial systems (UAS) and quantify trends in the influence of fuel patterns on fire processes

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped upon decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

Security in Distributed, Grid, Mobile, and Pervasive Computing

This book addresses the increasing demand to guarantee privacy, integrity, and availability of resources in networks and distributed systems. It first reviews security issues and challenges in content distribution networks, describes key agreement protocols based on the Diffie-Hellman key exchange and key management protocols for complex distributed systems like the Internet, and discusses securing design patterns for distributed systems. The next section focuses on security in mobile computing and wireless networks. After a section on grid computing security, the book presents an overview of security solutions for pervasive healthcare systems and surveys wireless sensor network security

Education and Security: Design and Evaluation Tools for Deliberate Disease Risks Mitigation

This thesis addresses the role of education to mitigate the risks of deliberate disease, including biological weapons. Specifically, it aims to analyse how education was constructed as a potential instrument to mitigate specific security risks; if and how education could impact on risks; and how effectiveness of education as a risk mitigation measure could be improved. The research framework combines concepts of security, risk and education within a general constructionist approach. Securitization is used to analyse attempts to construct education as a tool to mitigate specific security risks; risk assessment is used to identify and characterize risk scenarios and potential for risks mitigation; and instructional design and evaluation models are used for the design and evaluation of education. The thesis contends that education has been constructed as a mitigation tool for what were presented as urgent security risks of deliberate disease. Nine attempted securitization moves are identified and assessed. Improved competences identified in four thematic areas, and built with education, can mitigate risks in specific scenarios via impacting factors that primarily influence risk likelihood. The thesis presents several examples of achieved learning objectives, and tools that can be useful to evaluate behavioural and risk impacts, though empirical results on these levels here are still scarce. Design and evaluation tools, illustrated through a large amount of original and pre-existing data from a range of countries and contexts, are presented that can improve effectiveness of education as a deliberate disease risks mitigation measure

A Coaching and/or Education Intervention Targeting Physical Activity and Nutrition Behaviours in Parents with Overweight/obesity and their Children

The purpose of this dissertation is to provide a detailed overview of, findings from, and experiences participating in a 3-month randomized controlled trial (RCT) targeting obesity-related behaviours in parents with overweight/obesity (body mass index [BMI] ≥ 25 kg/m2) and their children (2.5-10 years old, any weight; N = 50 dyads). A concurrent mixed methods study comprised of an RCT and descriptive qualitative design was utilized. Parent-participants received Co-Active Life Coaching (CALC) and webinar-based health education (intervention) or education only (control). To address the dissertation’s purpose, Chapter II provides a detailed methodological account of the program, including rationale and a description of utilized measures. Chapter III depicts a study exploring the impact of the program on the primary outcomes of physical activity (PA) and dietary intake of parents and children, parental motivation to engage in healthy behaviours, and parental perceptions of program improvements. To determine anthropometric impacts, parental BMI and waist circumference were included. Quantitative results were not statistically significant; however, decrease in sodium intake in intervention group parents showed a trend toward significance (p = 0.04) from baseline to 6-month follow-up. Qualitatively, parents in both groups reported increased awareness of health behaviours, diet and PA improvements, and positive program experiences. Some parents felt the webinars were reminders about healthy habits, whereas others felt the information was new and important. Finally, to understand both client and coach perspectives, and what might be needed to maximize this behaviour change approach, Chapter IV presents a qualitative exploration of the experiences of parents and coaches in the intervention group. Parents reported increased accountability for their behaviours, learning how to effectively set goals, working through root causes of their behaviours, and changing their perspectives. Coaches provided information on tools/techniques they most commonly used, insights into working with this population, and advice for future coaches. The findings from this study will allow researchers, coaches, and participants to better understand the foundations for a strong coaching partnership in the context of obesity-related health behaviour changes. Together, these chapters represent the first (to the researchers’ knowledge) CALC and/or health education intervention for parents with overweight/obesity and their children

Collaborative and corroborative semantic web service monitoring

Service Oriented Computing has emerged as a promising computing paradigm for Internet-scale distributed applications built around services as primary building blocks. Such Internet-scale computing relies heavily on the connectivity infrastructure because existing business functionalities could be made accessible through this infrastructure. Furthermore, the services, as building blocks of these Internet-scale applications, may be developed and managed autonomously by enterprises. Different organizations may provide similar functionalities and it therefore becomes a matter of differentiation to support negotiable quality of service characteristics such as response time, cost, throughput, among others. Service consumers consider these non-functional characteristics of the published services when selecting which service to use; so there is an economic aspect to quality of service (QoS). The negotiated QoS characteristics often involve penalties, making it absolutely critical for the service provider to detect and correct any deviations from the agreedupon service behaviour. The need to detect potential failures has resulted in several research activities dedicated to service monitoring, specifically, Semantic Web Service Monitoring. Monitoring entails detecting and signaling whether the participating services behave consistently with the expected functionality and non-functional service properties. Monitoring may further entail enacting corrective mechanisms when there are failures or breaches to agreements by contracted services. Many approaches for both the service-consumer-side and service-provider-side monitoring have been proposed, including the use of dedicated monitoring infrastructure. Contemporary monitoring approaches rely on the service performance data being collected separately by the service provider for service-side monitoring and the consumer for client-side monitoring. As of this writing and according to our knowledge, no monitoring approach had been developed that facilitates the collaborative and corroborative exchange of monitoring information by both the service consumer and the service provider. The exchange of monitoring information is significant because: (1) the service consumer and the service provider may have different perspectives of the same QoS parameter and collaboration can help develop consensus, (2) enables the support for a flexible quality-based pricing model, which is a potential competitive advantage for service providers, (3) it has a built-in self-checking mechanism so that there is no need for costly incentive schemes to encourage honest reporting, (4) there is no need for costly dedicated infrastructure for monitoring by surveillance because service consumer and service provider exchange their context-dependent monitoring information directly. Having made a case for a collaborative and corroborative monitoring approach, this study hypothesizes that collaborative and corroborative monitoring of semantic web services is a viable alternative approach to client-side, service-side and 3rd-party/dedicated monitoring infrastructure. Therefore, the main objective of this study is to investigate, design, develop, and evaluate a collaborative and corroborative monitoring technique for Semantic Web Services. Design Science Research (DSR) methodology is adopted as it is particularly suitable for research studies that, like this study, aim to design an artefact. The significance of this work is underpinned by the critical importance of effective monitoring for the practical application of Service Oriented Computing technologies, specifically the Semantic Web Services. This study is critical because it purports to introduce a novel and practical approach to Semantic Web Service monitoring that is corroborative and collaborative between a service consumer and a service provider. In pursuance of the collaborative and corroborative monitoring, the study developed a Generalized Response Time Metric (GRTM), a consensus-based generalized metric for response time QoS parameter. The study further developed a technology-agnostic Monitoring Information eXchange (MIX) protocol to facilitate the exchange of performance data which is described in terms of the GRTM. The study also found, and demonstrated, that the support for, and implementation of collaborative and corroborative monitoring for Semantic Web Services is technically feasible. This is made possible by implementing a monitoring information exchange mechanism based on the MIX protocol. The proposed solution has been evaluated in terms of its technical feasibility. There were no other implementations of collaborative or corroborative monitoring of Semantic Web Services at the time of the execution of the research and consequently, there was no need for comparative analysis. The study demonstrated the technical feasibility of the proposed collaborative and corroborative monitoring technique for Semantic Web Service. This was achieved through a reference implementation of the MIX protocol. Finally, the study makes three recommendations for consideration as future research work and these are based on the identified limitations of the study. Firstly, developing the correct syntax for the semantic description of the mathematical expressions of all the parameters that characterize the performance of a Semantic Web Service such as latency, response time, throughput, and error-rate. An expressive ontology model for Semantic Web Service performance needs to include the logical expressions of these performance parameters; the study focused only on response time. Secondly, a Semantic Web Service Monitoring tool based on the MIX protocol should be developed further to provide extensible interfaces that software engineers can implement to support MIX functionality. The third recommendation is for software engineers and researchers to explore possible Service Level Agreement (SLA) negotiation strategies and implement these as part of the post-execution processes of the MIX protocol.School of ComputingPh. D. (Computer Science

Congress UPV Proceedings of the 21ST International Conference on Science and Technology Indicators

This is the book of proceedings of the 21st Science and Technology Indicators Conference that took place in València (Spain) from 14th to 16th of September 2016. The conference theme for this year, ‘Peripheries, frontiers and beyond’ aimed to study the development and use of Science, Technology and Innovation indicators in spaces that have not been the focus of current indicator development, for example, in the Global South, or the Social Sciences and Humanities. The exploration to the margins and beyond proposed by the theme has brought to the STI Conference an interesting array of new contributors from a variety of fields and geographies. This year’s conference had a record 382 registered participants from 40 different countries, including 23 European, 9 American, 4 Asia-Pacific, 4 Africa and Near East. About 26% of participants came from outside of Europe. There were also many participants (17%) from organisations outside academia including governments (8%), businesses (5%), foundations (2%) and international organisations (2%). This is particularly important in a field that is practice-oriented. The chapters of the proceedings attest to the breadth of issues discussed. Infrastructure, benchmarking and use of innovation indicators, societal impact and mission oriented-research, mobility and careers, social sciences and the humanities, participation and culture, gender, and altmetrics, among others. We hope that the diversity of this Conference has fostered productive dialogues and synergistic ideas and made a contribution, small as it may be, to the development and use of indicators that, being more inclusive, will foster a more inclusive and fair world