Improving interoperability in distributed multi-tier software stacks

Distributed multi-tier software stacks organise and deploy software components as a hierarchy of interacting tiers. The components are typically heterogeneous, i.e. each component may be written in a different language and may interoperate using a variety of protocols. Tiered software is modular but leads to a range of interoperability challenges including the following. (1) Interoperating components in multiple languages and paradigms increases developer cognitive load since they must simultaneously reason in multiple languages and paradigms. (2) There must be correct interoperation of components, e.g. adherence to the API or communication protocols between components. (3) Interoperation between different components can lead to diverse modes of failure as each component can fail in unique ways. Many of these challenges are the result of contributing factors like tight coupling or polyglot programmming. This thesis investigates techniques to improve heterogeneous interoperability in distributed multi-tier software stacks. Some common approaches include microservices and tierless languages. Microservices are perceived to offer better reliability than components in multi-tier software stacks through the loose coupling of services. The reliability of microservices is investigated by combining the established properties of dependence and state with reliability. This defines a new three-dimensional space: the Microservices Dependency State Reliability (MDSR) classification with six classes. The feasibility of statically identifying MDSR classes is demonstrated with a prototype analyser that identifies all six classes in Flask microservices web applications. The reliability implications of the different MDSR classes are evaluated by running three case study applications (Hipster-Shop, JPyL & WordPress) against a fault injector. Key results are as follows. (1) All applications fail catastrophically if a critical microservice fails. (2) Applications survive the failure of individual minor microservice(s). (3) The failure of any chain of microservices in JPyL & Hipster is catastrophic. (4) Individual microservices do not necessarily have minor reliability implications. In a tierless language, the compiler generates the code for each component and ensures their correct interoperation. They are mainly used to implement web stacks. However, their use in implementing IoT stacks is less common. This investigation compares interoperation in tiered and tierless IoT stacks through the systematic evaluation of four implementations of the prototype UoG smart campus IoT system: two tierless and two Python-based tiered. Key results of the study are as follows. (1) Tierless languages have the potential to significantly reduce the development effort for IoT systems, requiring 70% less code than the tiered implementations. (2) Tierless languages have the potential to significantly improve the reliability of IoT systems. (3) The first comparison of a tierless codebase for resource-rich sensor nodes and one for resourceconstrained sensor nodes shows that they have very similar functional structure and code sizes - within 7%. Tier elimination is a technique that removes a tier/component by integrating two tiers. Specifically, this thesis investigates the implications of eliminating the Apache web server in a 4-tier web stack: Jupyter Notebook, Apache, Python, Linux (JAPyL) and replacing it with PHP libraries in the frontend webpage to get the 3-tier (JPL). The study reveals the following. (1) The JPL 3-tier web stack requires that the developer uses fewer programming languages and paradigms than JAPyL, i.e two compared with four languages and two compared with three paradigms. (2) JPL requires 42% less code than JAPyL. (3) In JPL, some of the functionalities can be automated due to the decreased abstraction levels at the upper layers of the stack. (4) However, the latency in JPL is two to three times greater than that of JAPyL. So while tier elimination reduces developer effort and semantic friction the tradeoffs are high performance overhead & resource consumption and increasing code complexity

Building Information Modeling (BIM) for existing buildings - literature review and future needs

Abstract not availableRebekka Volk, Julian Stengel, Frank Schultman

Context Aware Middleware Architectures: Survey and Challenges

Abstract: Context aware applications, which can adapt their behaviors to changing environments, are attracting more and more attention. To simplify the complexity of developing applications, context aware middleware, which introduces context awareness into the traditional middleware, is highlighted to provide a homogeneous interface involving generic context management solutions. This paper provides a survey of state-of-the-art context aware middleware architectures proposed during the period from 2009 through 2015. First, a preliminary background, such as the principles of context, context awareness, context modelling, and context reasoning, is provided for a comprehensive understanding of context aware middleware. On this basis, an overview of eleven carefully selected middleware architectures is presented and their main features explained. Then, thorough comparisons and analysis of the presented middleware architectures are performed based on technical parameters including architectural style, context abstraction, context reasoning, scalability, fault tolerance, interoperability, service discovery, storage, security & privacy, context awareness level, and cloud-based big data analytics. The analysis shows that there is actually no context aware middleware architecture that complies with all requirements. Finally, challenges are pointed out as open issues for future work

Preface

DAMSS-2018 is the jubilee 10th international workshop on data analysis methods for software systems, organized in Druskininkai, Lithuania, at the end of the year. The same place and the same time every year. Ten years passed from the first workshop. History of the workshop starts from 2009 with 16 presentations. The idea of such workshop came up at the Institute of Mathematics and Informatics. Lithuanian Academy of Sciences and the Lithuanian Computer Society supported this idea. This idea got approval both in the Lithuanian research community and abroad. The number of this year presentations is 81. The number of registered participants is 113 from 13 countries. In 2010, the Institute of Mathematics and Informatics became a member of Vilnius University, the largest university of Lithuania. In 2017, the institute changes its name into the Institute of Data Science and Digital Technologies. This name reflects recent activities of the institute. The renewed institute has eight research groups: Cognitive Computing, Image and Signal Analysis, Cyber-Social Systems Engineering, Statistics and Probability, Global Optimization, Intelligent Technologies, Education Systems, Blockchain Technologies. The main goal of the workshop is to introduce the research undertaken at Lithuanian and foreign universities in the fields of data science and software engineering. Annual organization of the workshop allows the fast interchanging of new ideas among the research community. Even 11 companies supported the workshop this year. This means that the topics of the workshop are actual for business, too. Topics of the workshop cover big data, bioinformatics, data science, blockchain technologies, deep learning, digital technologies, high-performance computing, visualization methods for multidimensional data, machine learning, medical informatics, ontological engineering, optimization in data science, business rules, and software engineering. Seeking to facilitate relations between science and business, a special session and panel discussion is organized this year about topical business problems that may be solved together with the research community. This book gives an overview of all presentations of DAMSS-2018.DAMSS-2018 is the jubilee 10th international workshop on data analysis methods for software systems, organized in Druskininkai, Lithuania, at the end of the year. The same place and the same time every year. Ten years passed from the first workshop. History of the workshop starts from 2009 with 16 presentations. The idea of such workshop came up at the Institute of Mathematics and Informatics. Lithuanian Academy of Sciences and the Lithuanian Computer Society supported this idea. This idea got approval both in the Lithuanian research community and abroad. The number of this year presentations is 81. The number of registered participants is 113 from 13 countries. In 2010, the Institute of Mathematics and Informatics became a member of Vilnius University, the largest university of Lithuania. In 2017, the institute changes its name into the Institute of Data Science and Digital Technologies. This name reflects recent activities of the institute. The renewed institute has eight research groups: Cognitive Computing, Image and Signal Analysis, Cyber-Social Systems Engineering, Statistics and Probability, Global Optimization, Intelligent Technologies, Education Systems, Blockchain Technologies. The main goal of the workshop is to introduce the research undertaken at Lithuanian and foreign universities in the fields of data science and software engineering. Annual organization of the workshop allows the fast interchanging of new ideas among the research community. Even 11 companies supported the workshop this year. This means that the topics of the workshop are actual for business, too. Topics of the workshop cover big data, bioinformatics, data science, blockchain technologies, deep learning, digital technologies, high-performance computing, visualization methods for multidimensional data, machine learning, medical informatics, ontological engineering, optimization in data science, business rules, and software engineering. Seeking to facilitate relations between science and business, a special session and panel discussion is organized this year about topical business problems that may be solved together with the research community. This book gives an overview of all presentations of DAMSS-2018

Drone Navigation in Polar and Cryospheric Regions

Aerial and underwater drones present a paradigm shift away from the long term use of manned airplanes, helicopters and mini-submarines. This is evident from the number of scientific research articles that focus on research data obtained with drones. For instance, a special edition of the International Journal of Remote Sensing consists of 65 articles focused solely on aerial drone research (Remote Sensing, Vol 38, 2017). A second special edition consists of another 36 aerial drone articles (Remote Sensing, Vol 39, 2018). While less prevalent, underwater drones are also playing an ever increasing role in scientific research and proving to be effective contributors in many contexts (Harris, 2018; Zhou et al 2019). For example, if a typical daily drop camera productivity rate is 700 images per day, underwater drones can already achieve 15,000 images per day (Smale et al 2012). This study predominantly examines the use of aerial drones at high latitudes and in cryospheric regions. The study aims to provide insights into the navigation accuracy of Global Navigation Satellite Systems (GNSSs) use for drones, and the accuracy levels of drone positioning data achieved by GNSS augmentation. Currently, drone use in the global polar and cryospheric community is limited, and there is a scarcity of data on drone GNSS navigation and augmented measurements. The drone use survey in this study attempted to gain insights on general GNSS accuracy and augmented GNSS. The drone survey data obtained is the first representative sample from this close-knit community across the specialisms of climatology, ecology, geology, geomorphology, geophysics and oceanography. The drone survey data revealed that many different combinations of augmentation were used to obtain sub-metre and even sub-decimetre accuracy

Monitoring and Information Alignment in Pursuit of an IoT-Enabled Self-Sustainable Interoperability

To remain competitive with big corporations, small and medium-sized enterprises (SMEs) often need to be more dynamic, adapt to new business situations, react faster, and thereby survive in today‘s global economy. To do so, SMEs normally seek to create consortiums, thus gaining access to new and more opportunities. However, this strategy may also lead to complications. Due to the different sources of enterprise models and semantics, organizations are experiencing difficulties in seamlessly exchanging vital information via electronic means. In their attempt to address this issue, most seek to achieve interoperability by establishing peer-to-peer mappings with different business partners, or by using neutral data standards to regulate communications in optimized networks. Moreover, systems are more and more dynamic, frequently changing to answer new customer‘s requirements, causing new interoperability problems and a reduction of efficiency. Another situation that is constantly changing is the devices used in the enterprises, as the Enterprise Information Systems, devices are used to register internal data, and to be used to monitor several aspects. These devices are constantly changing, following the evolution and growth of the market. So, it is important to monitor these devices and doing a model representation of them. This dissertation proposes a self-sustainable interoperable framework to monitor existing enterprise information systems and their devices, monitor the device/enterprise network for changes and automatically detecting model changes. With this, network harmonization disruptions are detected in a timely way, and possible solutions are suggested to regain the interoperable status, thus enhancing robustness for reaching sustainability of business networks along time

BIM Assisted Design Process Automation for Pre-Engineered Buildings (PEB)

The effective adoption and implementation of Building Information Modeling (BIM) is still challenging for the construction industry. However, studies and reports show a significant increase in the rate of BIM implementation and adoption in mainstream construction activities over the last five years. In contrast, Pre-Engineered Building (PEB) construction, a specialized construction system which provides a very efficient approach for construction of primarily industrial buildings, has not seen the same uptake in BIM implementation and adoption. The thesis reviews the benefits and the main applications of BIM for the PEB industry as well as challenges of its practical implementation. To facilitate the implementation of BIM in the PEB industry, a BIM framework is adapted from Pre-fabrication (Pre-fab) industry and new workflows, process maps, and data-exchange strategies are developed. As the PEB industry traditionally makes significant use of automation in its design and fabrication process, accordingly this work investigates the technical challenges of incorporating automation into the proposed BIM process. Two new BIM concepts, “Planar Concept” and “Floating LOD”, are then developed and implemented as a solution to these challenges. To define the proper input/output criteria for automated BIM design processes, a numerical study was performed to identify an “Optimum LOD”. A software implementation embodying the research outcomes was developed to illustrate the feasibility of the results. Its step-by-step deployment is analyzed and discussed using an example industry PEB design project. Further, the impact of this work is extended by integrating the developed BIM framework and automated design process with wind engineering design activities and tools and procurement systems. The study concludes that the deployment of the proposed BIM framework could significantly address existing issues in project design through to operation processes found in the PEB industry. Also, the results indicate the developed concepts have the potential for supporting the application of automation in the other sectors of the general construction industry. This thesis is written using the Integrated Article format and includes various complementary studies