Today, mobile devices such as smart phones and tablets have become ubiquitous and are used everywhere. Millions of software applications can be purchased and installed on these devices, customizing them to personal interests and needs. However, the frequent use of mobile devices has let a new problem become omnipresent: their limited operation time, due to their limited energy capacities. Although energy consumption can be considered as being a hardware problem, the amount of energy required by today’s mobile devices highly depends on their current workloads, being highly influenced by the software running on them. Thus, although only hardware modules are consuming energy, operating systems, middleware services, and mobile applications highly influence the energy consumption of mobile devices, depending on how efficient they use and control hardware modules. Nevertheless, most of today’s mobile applications totally ignore their influence on the devices’ energy consumption, leading to energy wastes, shorter operation times, and thus, frustrated application users. A major reason for this energy-unawareness is the lack for appropriate tooling for the development of energy-aware mobile applications. As many mobile applications are today behaving energy-unaware and various mobile applications providing similar services exist, mobile application users aim to optimize their devices by installing applications being known as energy-saving or energy-aware; meaning that they consume less energy while providing the same services as their competitors. However, scarce information on the applications’ energy usage is available and, thus, users are forced to install and try many applications manually, before finding the applications fulfilling their personal functional, non-functional, and energy requirements. This thesis addresses the lack of tooling for the development of energy-aware mobile applications and the lack of comparability of mobile applications in terms of energy-awareness with the following two contributions: First, it proposes JouleUnit, an energy profiling and testing framework using unit-tests for the execution of application workloads while profiling their energy consumption in parallel. By extending a well-known testing concept and providing tooling integrated into the development environment Eclipse, JouleUnit requires a low learning curve for the integration into existing development and testing processes. Second, for the comparability of mobile applications in terms of energy efficiency, this thesis proposes an energy benchmarking and labeling service. Mobile applications belonging to the same usage domain are energy-profiled while executing a usage-domain specific benchmark in parallel. Thus, their energy consumption for specific use cases can be evaluated and compared afterwards. To abstract and summarize the profiling results, energy labels are derived that summarize the applications’ energy consumption over all evaluated use cases as a simple energy grade, ranging from A to G. Besides, users can decide how to weigh specific use cases for the computation of energy grades, as it is likely that different users use the same applications differently. The energy labeling service has been implemented for Android applications and evaluated for three different usage domains (being web browsers, email clients, and live wallpapers), showing that different mobile applications indeed differ in their energy consumption for the same services and, thus, their comparison is both possible and sensible. To the best of my knowledge, this is the first approach providing mobile application users comparable energy consumption information on mobile applications without installing and testing them on their own mobile devices.

This research analyzes cyclists' route decision by considering attributes of road safety and security from GPS records of a mobile application in Bogotá. The dataset comprises 3016 georeferenced routes of cyclists registered in the Biko mobile application during February 2018. This database was complemented with accident and thefts records from public entities, a descriptive statistical univariate analysis (RStudio), a Multiple Correspondence Analysis -MCA- (Stata), with multivariate statistical approach, and geographic component (QGIS and ArcGIS). The methods allowed obtaining: [i] a procedure for characterizing quantitative variables per km of route traveled; [ii] Categorization of continuous variables for establishing multivariate relationships through MCA -prerequisite for using this method instead of using surveys (Mobility survey 2019 cyclists' section in Bogotá); [iii] cyclists' commuting patterns with identification of main Origin - Destination zones (UTAM in Bogotá), and [iv] possible initial conditions for the public policies approach in Bogotá, with a continuous comparison between case studies in: Colombia, Latin America, Europe, and the United States, in order to be replicable for any city. ... [From: Introduction]

As mobile devices are nowadays used regularly and everywhere, their energy consumption has become a central concern for their users. However, mobile applications often do not consider energy requirements and users have to install and try them to reveal information on their energy behavior. In this paper, we compare mobile applications from two domains and show that applications reveal different energy consumption while providing similar services. We define microbenchmarks for emailing and web browsing and evaluate applications from these domains. We show that non-functional features such as web page caching can but not have to have a positive influence on applications' energy consumption.

Die Dissertation beschäftigt sich mit User Innovation Toolkits für situationsbezogene Dienste. Während User Innovation Toolkits Endnutzern erlauben, mobile Dienste selbst zu gestalten, haben situationsbezogene Dienste die Fähigkeit, sich an die Bedürfnisse des Nutzers und die Nutzungssituation anzupassen. Aufbauend auf einer empirischen Studie konnten drei wesentliche Herausforderungen der mobilen Telekommunikationsbranche identifiziert werden: Erstens, sind die Bedürfnisse von Nutzern mobiler Dienste hochgradig heterogen und ändern sich laufend. Zweitens, mangelt es an Geschäftsmodellen, um von dem wachsenden Markt zu profitieren. Schließlich sind technologische Probleme hinsichtlich adaptierbarer und lernfähiger Informationssysteme zu lösen. Die Untersuchung der theoretischen Grundlagen fokussierte vor allem auf den Transfer von Kundenwissen, der Wissensemergenz und der Situationstheorie und ihrer Anwendungen. Im Rahmen der Aktionsforschung konnte gemeinsam mit Fachexperten ein Ökonomisch sinnvolles generisches Geschäftsmodell für User Innovation Toolkits konzipiert und evaluiert, ein neues Vorgehensmodell zur Anforderungsanalyse generiert und die Informationsarchitektur zur Realisierung situationsbezogener Dienste modelliert werden. Die Synthese stellt den Prototyp eines User Innovation Toolkits für situationsbezogene Dienste dar. (Autorenref.)

Today, mobile devices such as smart phones and tablets have become ubiquitous and are used everywhere. Millions of software applications can be purchased and installed on these devices, customizing them to personal interests and needs. However, the frequent use of mobile devices has let a new problem become omnipresent: their limited operation time, due to their limited energy capacities. Although energy consumption can be considered as being a hardware problem, the amount of energy required by today’s mobile devices highly depends on their current workloads, being highly influenced by the software running on them. Thus, although only hardware modules are consuming energy, operating systems, middleware services, and mobile applications highly influence the energy consumption of mobile devices, depending on how efficient they use and control hardware modules. Nevertheless, most of today’s mobile applications totally ignore their influence on the devices’ energy consumption, leading to energy wastes, shorter operation times, and thus, frustrated application users. A major reason for this energy-unawareness is the lack for appropriate tooling for the development of energy-aware mobile applications. As many mobile applications are today behaving energy-unaware and various mobile applications providing similar services exist, mobile application users aim to optimize their devices by installing applications being known as energy-saving or energy-aware; meaning that they consume less energy while providing the same services as their competitors. However, scarce information on the applications’ energy usage is available and, thus, users are forced to install and try many applications manually, before finding the applications fulfilling their personal functional, non-functional, and energy requirements. This thesis addresses the lack of tooling for the development of energy-aware mobile applications and the lack of comparability of mobile applications in terms of energy-awareness with the following two contributions: First, it proposes JouleUnit, an energy profiling and testing framework using unit-tests for the execution of application workloads while profiling their energy consumption in parallel. By extending a well-known testing concept and providing tooling integrated into the development environment Eclipse, JouleUnit requires a low learning curve for the integration into existing development and testing processes. Second, for the comparability of mobile applications in terms of energy efficiency, this thesis proposes an energy benchmarking and labeling service. Mobile applications belonging to the same usage domain are energy-profiled while executing a usage-domain specific benchmark in parallel. Thus, their energy consumption for specific use cases can be evaluated and compared afterwards. To abstract and summarize the profiling results, energy labels are derived that summarize the applications’ energy consumption over all evaluated use cases as a simple energy grade, ranging from A to G. Besides, users can decide how to weigh specific use cases for the computation of energy grades, as it is likely that different users use the same applications differently. The energy labeling service has been implemented for Android applications and evaluated for three different usage domains (being web browsers, email clients, and live wallpapers), showing that different mobile applications indeed differ in their energy consumption for the same services and, thus, their comparison is both possible and sensible. To the best of my knowledge, this is the first approach providing mobile application users comparable energy consumption information on mobile applications without installing and testing them on their own mobile devices.

Mobile applications are developed to run on fast-evolving platforms, such as Android or iOS. Respective mobile devices are heterogeneous concerning hardware (e.g., sensors, displays, communication interfaces) and software, especially operating system functions. Software vendors cope with platform evolution and various hardware configurations by abstracting from these variable assets. However, they cannot be sure about their assumptions on the inner conformance of all device parts and that the application runs reliably on each of them—in consequence, comprehensive testing is required. Thereby, in testing, variability becomes tedious due to the large number of test cases required to validate behavior on all possible device configurations. In this paper, we provide remedy to this problem by combining model-based testing with variability concepts from Software Product Line engineering. For this purpose, we use feature-based test modeling to generate test cases from variable operational models for individual application configurations and versions. Furthermore, we illustrate our concepts using the commercial mobile application “runtastic” as example application.

As mobile devices are nowadays used regularly and everywhere, their energy consumption has become a central concern for their users. However, mobile applications often do not consider energy requirements and users have to install and try them to reveal information on their energy behavior. In this paper, we compare mobile applications from two domains and show that applications reveal different energy consumption while providing similar services. We define microbenchmarks for emailing and web browsing and evaluate applications from these domains. We show that non-functional features such as web page caching can but not have to have a positive influence on applications' energy consumption.

Mobile applications are developed to run on fast-evolving platforms, such as Android or iOS. Respective mobile devices are heterogeneous concerning hardware (e.g., sensors, displays, communication interfaces) and software, especially operating system functions. Software vendors cope with platform evolution and various hardware configurations by abstracting from these variable assets. However, they cannot be sure about their assumptions on the inner conformance of all device parts and that the application runs reliably on each of them—in consequence, comprehensive testing is required. Thereby, in testing, variability becomes tedious due to the large number of test cases required to validate behavior on all possible device configurations. In this paper, we provide remedy to this problem by combining model-based testing with variability concepts from Software Product Line engineering. For this purpose, we use feature-based test modeling to generate test cases from variable operational models for individual application configurations and versions. Furthermore, we illustrate our concepts using the commercial mobile application “runtastic” as example application.

Automation of mobile construction and agricultural equipment has gained wide acceptance based on increases in productivity, safety, and precision; while also helping upskill operators. On construction equipment, after-market automation of earthmoving crawler dozers and graders has driven a conversion of machines to electro-hydraulic (EH) implement control and integration into digital worksites. Unlike the aforementioned machines, conversion of the excavator into a semi or fully autonomous machine presents significant challenges due to kinematics, variable loads, non-linear multi-function of implements, safety, and robustness. The present work demonstrates the retrofit of a pilot-operated 21-ton excavator and development of automated controls to address these challenges. The operator pilot joysticks and existing hydraulic system were retained, while adding capability for autonomous functionality with integrated hardware, controls, and kinematic solvers within a production viable environment. Autonomous features for path planning, multi-function actuator velocity control, EH controls, and safety were developed to prove the value of precise and low latency control hardware for EH excavator operation.

Gegenwärtige Infrastrukturen für verteilte Dienste und Anwendungen, insbesondere das Internet, entwickeln sich zunehmend zu mobilen verteilten Systemen. Durch die Integration drahtloser Netze, mobiler bzw. dedizierter Endgeräte und nicht zuletzt durch die Mobilität der Benutzer steigt die Heterogenität und Dynamik der Systeme hinsichtlich der eingesetzten Endgeräte, Kommunikationstechnologien sowie Benutzeranforderungen und Anwendungssituationen. Diese Eigenschaften sind mobilen Systemen inhärent und bleiben trotz der fortschreitenden Entwicklung der Technologien bestehen. Daraus resultieren spezifische Anforderungen an Anwendungen und Dienste, denen insbesondere die Softwareentwicklung Rechnung tragen muss. In der vorliegenden Arbeit wird die Adaptivität von Softwaresystemen als wesentlicher Lösungsansatz für mobile verteilte Infrastrukturen thematisiert. Dazu werden wesentliche Mechanismen zur Adaption sowie der Überschneidungsbereich von Adaptionsmechanismen, "Context-Awareness" und Softwareentwicklung untersucht. Ziel ist es, Erkenntnisse über Basismechanismen und Grundprinzipien der Adaption zu gewinnen und diese zur systematischen Entwicklung adaptiver Anwendungen auszunutzen. Aus der Analyse des State-of-the-Art werden als erstes wichtiges Ergebnis der Arbeit wesentliche Basismechanismen zur Adaption identifiziert, umfassend klassifiziert und hinsichtlich eines Einsatzes in mobilen verteilten Infrastrukturen bewertet. Auf dieser Grundlage wird ein Meta-Modell zur systematischen Entwicklung adaptiver Anwendungen erarbeitet. Dieses erlaubt die Beschreibung adaptiver Anwendungen durch die Komposition von Basismechanismen zur Struktur- und Parameteradaption. Die Steuerung der Adaption durch Kontext und Meta-Informationen kann explizit beschrieben werden. Das Meta-Modell kann Entwickler beim Entwurf adaptiver Anwendungen unterstützen, stellt aber auch einen Ausgangspunkt für deren Analyse und Validierung sowie zur Kodegenerierung dar. Durch die explizite Beschreibung der verwendeten Adaptionsmechanismen und deren Abhängigkeiten von Kontext können Anwendungsmodelle außerdem zur Dokumentation verwendet werden. Im Rahmen der Validierung konnte die Integrierbarkeit der Basismechanismen und die flexible Anwendbarkeit des Modells zur systematischen Entwicklung adaptiver Anwendungen nachgewiesen werden.