Microservice Transition and its Granularity Problem: A Systematic Mapping Study

Microservices have gained wide recognition and acceptance in software industries as an emerging architectural style for autonomic, scalable, and more reliable computing. The transition to microservices has been highly motivated by the need for better alignment of technical design decisions with improving value potentials of architectures. Despite microservices' popularity, research still lacks disciplined understanding of transition and consensus on the principles and activities underlying "micro-ing" architectures. In this paper, we report on a systematic mapping study that consolidates various views, approaches and activities that commonly assist in the transition to microservices. The study aims to provide a better understanding of the transition; it also contributes a working definition of the transition and technical activities underlying it. We term the transition and technical activities leading to microservice architectures as microservitization. We then shed light on a fundamental problem of microservitization: microservice granularity and reasoning about its adaptation as first-class entities. This study reviews state-of-the-art and -practice related to reasoning about microservice granularity; it reviews modelling approaches, aspects considered, guidelines and processes used to reason about microservice granularity. This study identifies opportunities for future research and development related to reasoning about microservice granularity.Comment: 36 pages including references, 6 figures, and 3 table

Sector concentration in loan portfolios and economic capital

The purpose of this paper is to measure the potential impact of business-sector concentration on economic capital for loan portfolios and to explore a tractable model for its measurement. The empirical part evaluates the increase in economic capital in a multi-factor asset value model for portfolios with increasing sector concentration. The sector composition is based on credit information from the German central credit register. Finding that business sector concentration can substantially increase economic capital, the theoretical part of the paper explores whether this risk can be measured by a tractable model that avoids Monte Carlo simulations. We analyze a simplified version of the analytic value-at-risk approximation developed by Pykhtin (2004), which only requires risk parameters on a sector level. Sensitivity analyses with various input parameters show that the analytic approximation formulae perform well in approximating economic capital for portfolios which are homogeneous on a sector level in terms of PD and exposure size. Furthermore, we explore the robustness of our results for portfolios which are heterogeneous in terms of these two characteristics. We find that low granularity ceteris paribus causes the analytic approximation formulae to underestimate economic capital, whereas heterogeneity in individual PDs causes overestimation. Indicative results imply that in typical credit portfolios, PD heterogeneity will at least compensate for the granularity effect. This suggests that the analytic approximations estimate economic capital reasonably well and/or err on the conservative side. --sector concentration risk,economic capital

Sector Concentration in Loan Portfolios and Economic Capital

The purpose of this paper is to measure the potential impact of business-sector concentration on economic capital for loan portfolios and to explore a tractable model for its measurement. The empirical part evaluates the increase in economic capital in a multi-factor asset value model for portfolios with increasing sector concentration. The sector composition is based on credit information from the German central credit register. Finding that business sector concentration can substantially increase economic capital, the theoretical part of the paper explores whether this risk can be measured by a tractable model that avoids Monte Carlo simulations. We analyze a simplified version of the analytic value-at-risk approximation developed by Pykhtin (2004), which only requires risk parameters on a sector level. Sensitivity analyses with various input parameters show that the analytic approximation formulae perform well in approximating economic capital for portfolios which are homogeneous on a sector level in terms of PD and exposure size. Furthermore, we explore the robustness of our results for portfolios which are heterogeneous in terms of these two characteristics. We find that low granularity ceteris paribus causes the analytic approximation formulae to underestimate economic capital, whereas heterogeneity in individual PDs causes overestimation. Indicative results imply that in typical credit portfolios, PD heterogeneity will at least compensate for the granularity effect. This suggests that the analytic approximations estimate economic capital reasonably well and/or err on the conservative side.sector concentration risk, economic capital

A collection of tools for factory eco-efficiency

co-efficiency is generally defined as doing more with less, aiming to decouple environmental impact from economic and social value creation. This paper presents three tools to guide the implementation of eco-efficiency in factories: (1) definition and patterns of good practices for sustainable manufacturing, (2) a self-assessment tool and maturity grid, and (3) a factory modelling framework

Granular technologies to accelerate decarbonization

Of the 45 energy technologies deemed critical by the International Energy Agency for meeting global climate targets, 38 need to improve substan- tially in cost and performance while accelerating deployment over the next decades.Low-carbon technological solutions vary in scale from solar panels, e-bikes, and smart thermostats to carbon capture and storage, light rail transit, and whole-building retrofits. We make three contributions to long-standing debates on the appropriate scale of technological responses in the energy system. First, we focus on the specific needs of accelerated low-carbon transformation: rapid technology deployment, escaping lock-in, and social legitimacy. Second, we synthesize evidence on energy end-use technologies in homes, transport, and industry, as well as electricity generation and energy supply. Third, we go beyond technical and economic considerations to include innovation, investment, deployment, social, and equity criteria for assessing the relative advantage of alternative technologies as a function of their scale. We suggest numerous potential advantages of more-granular energy technologies for accelerating progress toward climate targets, as well as the conditions on which such progress depends

Mapping the sustainable development goals into the EDINSOST sustainability map of bachelor engineering degrees

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This Research to Practice Work in Progress paper presents the work conducted on the use of the Sustainability Map of Bachelor Engineering Degrees (a tool developed by the EDINSOST project) to analyze how Sustainable Development Goals (SDGs) are developed in each Degree. Over recent years, there has been a growth in the importance of working sustainability based on the SDGs. To identify which learning objective of each SDG corresponds to each learning outcome of the EDINSOST Sustainability Map, a correspondence matrix has been defined. The matrix contains the learning outcomes of the EDINSOST Sustainability Map in its rows, and the 17 SDGs in the columns. The cells of the matrix contain the learning objectives of the SDGs that correspond to each learning outcome of the EDINSOST Sustainability Map. This work in progress presents the first results of the process of mapping the SDGs into the EDINSOST Sustainability Map of Engineering Bachelor Degrees. Early results show that some of the 169 learning objectives are not applicable to Engineering Degrees. Likewise, we have seen that learning objectives have been defined more for policy makers than for engineers, and therefore adaptation is not an easy task. However, the work done has helped us to verify that the EDINSOST Sustainability Map can help in the introduction of the SDGs into the curriculum.Peer ReviewedPostprint (author's final draft

Hierarchical topological clustering learns stock market sectors

The breakdown of financial markets into sectors provides an intuitive classification for groups of companies. The allocation of a company to a sector is an expert task, in which the company is classified by the activity that most closely describes the nature of the company's business. Individual share price movement is dependent upon many factors, but there is an expectation for shares within a market sector to move broadly together. We are interested in discovering if share closing prices do move together, and whether groups of shares that do move together are identifiable in terms of industrial activity. Using TreeGNG, a hierarchical clustering algorithm, on a time series of share closing prices, we have identified groups of companies that cluster into clearly identifiable groups. These clusters compare favourably to a globally accepted sector classification scheme, and in our opinion, our method identifies sector structure clearer than a statistical agglomerative hierarchical clustering metho

Information reuse in dynamic spectrum access

Dynamic spectrum access (DSA), where the permission to use slices of radio spectrum is dynamically shifted (in time an in different geographical areas) across various communications services and applications, has been an area of interest from technical and public policy perspectives over the last decade. The underlying belief is that this will increase spectrum utilization, especially since many spectrum bands are relatively unused, ultimately leading to the creation of new and innovative services that exploit the increase in spectrum availability. Determining whether a slice of spectrum, allocated or licensed to a primary user, is available for use by a secondary user at a certain time and in a certain geographic area is a challenging task. This requires 'context information' which is critical to the operation of DSA. Such context information can be obtained in several ways, with different costs, and different quality/usefulness of the information. In this paper, we describe the challenges in obtaining this context information, the potential for the integration of various sources of context information, and the potential for reuse of such information for related and unrelated purposes such as localization and enforcement of spectrum sharing. Since some of the infrastructure for obtaining finegrained context information is likely to be expensive, the reuse of this infrastructure/information and integration of information from less expensive sources are likely to be essential for the economical and technological viability of DSA. © 2013 IEEE