Self-Adaptation in Industry: A Survey

Computing systems form the backbone of many areas in our society, from manufacturing to traffic control, healthcare, and financial systems. When software plays a vital role in the design, construction, and operation, these systems are referred as software-intensive systems. Self-adaptation equips a software-intensive system with a feedback loop that either automates tasks that otherwise need to be performed by human operators or deals with uncertain conditions. Such feedback loops have found their way to a variety of practical applications; typical examples are an elastic cloud to adapt computing resources and automated server management to respond quickly to business needs. To gain insight into the motivations for applying self-adaptation in practice, the problems solved using self-adaptation and how these problems are solved, and the difficulties and risks that industry faces in adopting self-adaptation, we performed a large-scale survey. We received 184 valid responses from practitioners spread over 21 countries. Based on the analysis of the survey data, we provide an empirically grounded overview of state-of-the-practice in the application of self-adaptation. From that, we derive insights for researchers to check their current research with industrial needs, and for practitioners to compare their current practice in applying self-adaptation. These insights also provide opportunities for the application of self-adaptation in practice and pave the way for future industry-research collaborations.Comment: 43 page

The CitySPIN Platform: A CPSS Environment for City-Wide Infrastructures

Cyber-physical Social System (CPSS) are complex systems that span the boundaries of the cyber, physical and social spheres. They play an important role in a variety of domains ranging from industry to smart city applications. As such, these systems necessarily need to take into account, combine and make sense of heterogeneous data sources from legacy systems, from the physical layer and also the social groups that are part of/use the system. The collection, cleansing and integration of these data sources represents a major effort not only during the operation of the system, but also during its engineering and design. Indeed, while ongoing efforts are concerned primarily with the operation of such systems, limited focus has been put on supporting the engineering phase of CPSS. To address this shortcoming, within the CitySPIN project we aim to create a platform that supports stakeholders involved in the design of these systems especially in terms of support for data management. To that end, we develop methods and techniques based on Semantic Web and Linked Data technologies for the acquisition and integration of heterogeneous data from disparate structured, semi-structured and unstructured sources, including open data and social data. In this paper we present the overall system architecturewith a core focus on data acquisition and integration.We demon-strate our approach through a prototypical implementation of an adaptive planning use case for public transportation scheduling

Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks

Rising rural body-mass index is the main driver of the global obesity epidemic in adults

Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities(.)(1,2) This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity(3-6). Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017-and more than 80% in some low- and middle-income regions-was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing-and in some countries reversal-of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.Peer reviewe

An Architecture Framework for Collective Intelligence Systems

© 2015 IEEE. Collective intelligence systems (CIS), such as wikis, social networks and content sharing platforms, have dramatically improved knowledge creation and sharing at society level. There is a trend to exploit the stigmergic mechanisms of CIS also at organization/corporate level. However, despite the wide adoption of CIS, there is a lack of consolidated systematic knowledge of the architectural principles and practices that underlie CIS. Software architects lack guidance to design CIS for the application context of individual organizations. To address these challenges, we contribute with an architecture framework for CIS, aligned with ISO/IEC/IEEE 42010. The CIS-AF framework provides guidance for architects to describe key CIS elements and systematically model a CIS that is well-suited for an organization's context and goals. The framework is grounded in an in-depth analysis of existing CIS, workshops and interviews with key stakeholders, and experiences from developing a prototypical CIS. We evaluated the architecture framework in two cases in industry setting where CIS have been designed and implemented using the framework. Results show that the framework effectively supports stakeholders with providing a shared vocabulary of CIS concepts, guiding them to systematically apply the stigmergic principles of CIS, and supporting them with kick starting CIS in their organizations.status: publishe

An Architecture Framework for Collective Intelligence Systems

Collective intelligence systems (CIS), such as wikis, social networks and content sharing platforms, have dramatically improved knowledge creation and sharing at society level. There is a trend to exploit the stigmergic mechanisms of CIS also at organization/corporate level. However, despite the wide adoption of CIS, there is a lack of consolidated systematic knowledge of the architectural principles and practices that underlie CIS. Software architects lack guidance to design CIS for the application context of individual organizations. To address these challenges, we contribute with an architecture framework for CIS, aligned with ISO/IEC/IEEE 42010. The CIS-AF framework provides guidance for architects to describe key CIS elements and systematically model a CIS that is well-suited for an organization's context and goals. The framework is grounded in an in-depth analysis of existing CIS, workshops and interviews with key stakeholders, and experiences from developing a prototypical CIS. We evaluated the architecture framework in two cases in industry setting where CIS have been designed and implemented using the framework. Results show that the framework effectively supports stakeholders with providing a shared vocabulary of CIS concepts, guiding them to systematically apply the stigmergic principles of CIS, and supporting them with kick starting CIS in their organizations

Patterns for Self-Adaptation in Cyber-Physical Systems

© Springer International Publishing AG 2017. Engineering Cyber-Physical Systems (CPS) is challenging, as these systems have to handle uncertainty and change during operation. A typical approach to deal with uncertainty is enhancing the system with self-adaptation capabilities. However, realizing self-adaptation in CPS, and consequently also in Cyber-Physical Production Systems (CPPS) as a member of the CPS family, is particularly challenging due to the specific characteristics of these systems, including the seamless integration of computational and physical components, the inherent heterogeneity and large-scale of such systems, and their open-endedness. In this chapter we survey CPS studies that apply the promising design strategy of combining different self-adaptation mechanisms across the technology stack of the system. Based on the survey results, we derive recurring adaptation patterns that structure and consolidate design knowledge. The patterns offer problem-solution pairs to engineers for the design of future CPS and CPPS with self-adaptation capabilities. Finally, the chapter outlines the potential of collective intelligence systems for CPPS and their engineering based on the survey results.status: accepte

Preliminary Results of a Survey on the Use of Self-Adaptation in Industry

Self-Adaptation equips a software system with a feedback loop that automates tasks that otherwise need to be performed by operators. Such feedback loops have found their way to a variety of practical applications, one typical example is an elastic cloud. Yet, the state of the practice in self-Adaptation is currently not clear. To get insights into the use of self-Adaptation in practice, we are running a largescale survey with industry. This paper reports preliminary results based on survey data that we obtained from 113 practitioners spread over 16 countries, 62 of them work with concrete self-Adaptive systems. We highlight the main insights obtained so far: motivations for self-Adaptation, concrete use cases, and difficulties encountered when applying self-Adaptation in practice. We conclude the paper with outlining our plans for the remainder of the study