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Sustainability and specifically environmental stewardship are emerging as prominent issues in engineering decision-making. Despite this, the United States has neither a national policy on sustainability, nor a national sustainable transportation strategy. In many cases this has resulted in state DOTs basing their environmental practices on requirements set out previously by EPA regulations with little or no additional consideration of environmental effects. A survey conducted as part of this thesis revealed that environmental stewardship is not considered part of current DOT pavement management engineers' job responsibilities, despite having duties such as pavement design and maintenance which can greatly affect the environmental impact of a project. Initial cost and engineering judgment were the most widely considered in decision-making, with LCCA also being considered at least some of the time by most respondents. Environmental impacts, on the other hand, are not often integrated into formal decision making and are more likely to be considered as a "tie breaker" when alternatives have similar costs. The literature review also covered two distinct types of environmental decision support tools: Environmental Rating Tools and Environmental Impact Calculators. Rating Tools gather predominantly environmental impact information in order to award a score to a project. Environmental Calculators are software tools that use material or equipment inputs to estimate the amount of pollutants produced by a project. While a variety of environmental impact tools are currently available they suffer from drawbacks such as incomplete or unclearly defined LCA boundaries, consideration of only one environmental impact, subjectivity, lack of transparency, out-of-date databases, and an inability to perform probabilistic calculations. CO₂e was the only environmental factor considered by nearly all Environmental Calculators reviewed as part of this thesis and was a major focus of the Rating Tools. The thesis proposes the framework for a tool that addresses some of the limitations of available tools and aids decision-makers in incorporating environmental factors into roadway decision-making. The proposed tool would address many of the limitations of previous environmental impact calculators and could be implemented without the need for extensive additional research. The tool would calculate emissions due to material extraction and production, emissions due to construction activities, resource consumptions, and emissions due to work zone delays. Emissions due to work zone delays are not considered by any other currently available tool. The tool would also perform probabilistic calculations and have a database which could be added to and updated by users. Additional products developed as part of this thesis are a review of currently available environmental impact tools and a Microsoft Excel workbook used to demonstrate the intended usage of the tool. It is concluded that the development of such a tool is necessary and feasible. The proposed tool would address limitations of available tools by considering more than one environmental impact, including the previously neglected impact of emissions due to work zone related delay, pairing a user-friendly interface with an editable database, and supporting probabilistic calculations. Recommended future research includes surveying state DOT engineers to determine the barriers delaying implementation of currently available environmental impacts tools. Further benefits could be realized by programming the proposed tool and building a database that reflects the materials, mixes, and construction activities available to a specific locality. / Master of Science

Den textila industrin, en egen värld, är nu under rampljuset som en av de största miljöpåverkande industrierna. Precis som i fallet med många andra industrier så måste textilbranschen intensivt arbeta med att minska sin negativa påverkan på miljön. Slutmålet måste vara att helt balansera uttagen och insättningarna så att man skapar en bransch som blir klimat- och miljöneutral. I denna rapport har en livscykelanalys gjorts på en underställströja från Helly Hansen tillverkad av 99 % polypropylene. Inom denna livscykelanalys har vi noggrant studerat och undersökt fakta för att hitta de processer som har den största påverkan på miljön. Genom att undersöka material, energi- och resursförbrukning har lösningar för andra mindre miljöpåverkande alternativ tagits fram. Helly Hansen är ett företag som aktivt arbetar med att minska sin miljöpåverkan. De är bland annat medlemmar i Bluesign och driver inom denna organisation ett intensivt arbete för miljövänligare produkter, material och processer. Dock finns det ytterligare åtgärder som kan göras för att reducera en produkts miljöpåverkan. Ett exempel är att göra en livscykelanalys för att optimera produktionen. Som läsare av denna rapport är det upp till var och en att bestämma om de lösningarna som presenteras är värda att genomföra eller om livscykeln redan är optimerad utifrån ett miljöperspektiv och nuvarande förutsättningar. he textile industry, a world of its own, has now come under the spotlight for its role as one of the most affecting industries on the environment. It is important to make a change so that the natural balance doesn’t reach its limit and turn for the worse, beyond salvation. This report is a creation and a study of a lifecycle analysis for a Helly Hansen baselayer top made out of 99 % polypropylene. The goal was to identify processes which have primal impacts on the environment and are the cause of the largest emissions. By studying the materials used, energy and resource consumption, easy solutions have been established to lower emissions that are harming our eco-system for example by increasing the greenhouse effect. By controlling the consumption of energy and resources of a product in the textile industry, the environmental impact can be reduced. Helly Hansen is a company that actively works to reduce their carbon footprint by, amongst others, being members of the Bluesign group. However there are further measures that can be taken to reduce the impact on the environment, for example by doing lifecycle analyses to optimize production. It is up to the reader of this report to decide if the solutions for optimization presented are worth the investment given current conditions and the impact on the environment. / Program: Textil produktutveckling med entreprenörs- och affärsinriktning

There is an ongoing debate by people in the industry whether to make native or web applications. These discussions mostly surround issues about development costs, user experience and capabilities. Another aspect of this debate is the fact that mobile devices have varying hardware specifications which is another factor to consider when making this decision. What we want to shed some light on is how performance is affected on the device when using these two different approaches of application development. The use of CPU/RAM and Energy is our primary concern and in our experiment we measure these values on two similar applications where one uses Nested Layouts and the other a WebView. The experiment was made on three different devices with varying specifications. What we found was that Web applications have a bigger impact on overall performance and because of this use more battery. While the debate certainly won't come to a close with results they are conclusive when it comes to the topic of performance and will be of value to developers who are concerned about it.

Aujourd'hui, les systèmes logiciels sont omniprésents. Parfois, les applications doivent fonctionner sur des dispositifs à ressources limitées. Toutefois, les applications nécessitent un support d'exécution pour faire face à de telles limitations. Cette thèse aborde le problème de la programmation pour créer des systèmes "conscient des ressources" supporté par des environnements d'exécution adaptés (MRTEs). En particulier, cette thèse vise à offrir un soutien efficace pour recueillir des données sur la consommation de ressources de calcul (par exemple, CPU, mémoire), ainsi que des mécanismes efficaces pour réserver des ressources pour des applications spécifiques. Dans les solutions existantes, nous trouvons deux inconvénients importants. Les solutions imposent un impact important sur les performances à l'exécution des applications. La création d'outils permettant de gérer finement les ressources pour ces abstractions est encore une tâche complexe. Les résultats de cette thèse forment trois contributions : Un cadre de surveillance des ressources optimiste qui réduit le coût de la collecte des données de consommation de ressources ; une méthodologie pour sélectionner les le support d'exécution des composants au moment du déploiement afin d’exécuter la réservation de ressources ; un langage pour construire des profileurs de mémoire personnalisées qui peuvent être utilisés à la fois au cours du développement des applications, ainsi que dans un environnement de production. / Software systems are more pervasive than ever nowadays. Occasionally, applications run on top of resource-constrained devices where efficient resource management is required ; hence, they must be capable of coping with such limitations. However, applications require support from the run-time environment to properly deal with resource limitations. This thesis addresses the problem of supporting resource-aware programming in execution environments. In particular, it aims at offering efficient support for collecting data about the consumption of computational resources (e.g., CPU, memory), as well as efficient mechanisms to reserve resources for specific applications. In existing solutions we find two important drawbacks. First, they impose performance overhead on the execution of applications. Second, creating resource management tools for these abstractions is still a daunting task. The outcomes of this thesis are three contributions: an optimistic resource monitoring framework that reduces the cost of collecting resource consumption data ; a methodology to select components' bindings at deployment time in order to perform resource reservation ; a language to build customized memory profilers that can be used both during applications' development, and also in a production environment.

Der weltweit steigende Bedarf an Energie und natürlichen Ressourcen, insbesondere an fossilen Brennstoffen und seltenen Metallen, sowie die angestrebte Reduktion des CO2-Ausstoßes führen zu steigenden Preisen für Energie und Rohstoffe. Der Energie- und Ressourcenbedarf muss daher neben der Funktionalität und den Kosten eines technischen Produkts in Planungs- und Entwicklungsprozesse einbezogen werden. Für eine Minimierung des Energie- und Ressourcenbedarfs sind insbesondere die frühen Phasen der Produktentwicklung von großem Interesse, da in diesen Phasen die wesentlichen Eigenschaften eines Produkts für den gesamten Lebenszyklus zu großen Teilen festgelegt werden. Durch die Forderung nach kürzeren Markteinführungszeiten bei gleichzeitigem Anstieg der Komplexität technischer Produkte ist der Einsatz von Softwaresystemen zur Unterstützung der Planungs- und Entwicklungsprozesse unabdingbar. Die Zielstellung der vorliegenden Arbeit ist die Entwicklung und Realisierung von Methoden und Verfahren zur softwaretechnischen Unterstützung ausgewählter Abläufe der Produktentwicklung. Die gewählten Abläufe sind die Ausarbeitung von Anforderungsspezifikationen für technische Produkte, die Priorisierung von Anforderungen sowie die Analyse und Bewertung des Energiebedarfs von Werkzeugmaschinen. Der Schwerpunkt der Methoden und Verfahren liegt einerseits auf der Strukturierung und Koordinierung der Zusammenarbeit von Domänenexperten in den ausgewählten Abläufen der Produktentwicklung und andererseits auf der Erweiterung der Abläufe um Energie- und Ressourcenbetrachtungen. Die softwaretechnische Unterstützung der gewählten Abläufe ermöglicht es, die Komplexität der zu entwickelnden Produkte beherrschbar zu machen und den manuellen Aufwand der Domänenexperten in den Abläufen zu verringern.

Nowadays, our daily live concerns the usage of Information Technology, increasingly. As a result, a huge amount of data has to be processed which is outsourced from local devices to data centers. Due to fluctuating demands these are not fully utilized all the time and consume a significant amount of energy while idling. A common approach to avoid unnecessary idle times is to consolidate running services on a subset of machines and switch off the remaining ones. Unfortunately, the services on a single machine interfere with each other due to the competition for shared resources such as caches after the consolidation, which leads to a degradation of performance. Hence, data centers have to trade off between reducing the energy consumption and certain performance criteria defined in the Service Level Agreement. In order to make the trade off in advance, it is necessary to characterize services and quantify the impact to each other after a potential consolidation. Our approach is to use random variables for characterization, which includes the fluctuations of the resource consumptions. Furthermore, we would like to model the interference of services to provide a probability of exceeding a certain performance criterion.

Skiing and snowboarding are popular recreation activities in New Zealand, as well as constituting important components of the winter tourism product. The 2001 snow season witnessed record visitor numbers. Skier days have increased by more than 10% compared with the previous year to 1.254 million. The traditionally “nature related” activity of skiing, however has increasingly often been discussed in the light of excessive resource consumption and pollution of alpine environments. Since no research on resource efficient management of ski fields has been undertaken in New Zealand, this study examined environmental awareness and actions of ski field managers, resource consumption benchmarks (water and energy use, solid waste production), along with resource use related visitor behaviour. Two separate surveys were undertaken to collect relevant information from ski field managers and ski field visitors. While a census of managers across New Zealand was conducted with a mail-back questionnaire (all 27 ski fields were contacted, response rate 44%), the visitor survey was undertaken on-site at six selected ski fields in Canterbury, South Island (total responses: N=259). Analysis of the survey results showed that managers generally acted to protect the environment and resources, however, at different levels for the various indicators measured. Energy use and air pollution were rarely perceived to be environmentally important. Accordingly, only few actions were undertaken to reduce energy use. This is surprising, since energy consumption proved to be a major feature of ski field management. Given the additionally large amounts of water consumed (mainly for snowmaking) and solid waste produced on the mountain, skiing has to be classified as a resource intensive activity. Resource consumption is intensified further, when the impacts associated with tourists being transported to, and from, the mountain are considered. Energy use for “ski trip transport” within New Zealand is two times larger (180 MJ) than energy use associated with ski field infrastructure use (90 MJ) on a per skier day basis. There are several options to improve the environmental performance of ski fields, ranging from modernising equipment, optimising snowmaking and providing efficient transport alternatives. Additionally, increased cooperation between ski field managers, local governments and research institutes could potentially result in environmentally smarter operational practices. Internationally, New Zealand’s ski areas compare relatively well, mainly because of limited on-mountain entertainment and accommodation development, which keeps resource consumption and pollution low compared with European and North American ski fields. However, this research also indicated that New Zealand’s ski field visitors increasingly demand facilities and services similar to those overseas, which in turn may result in larger environmental impacts. New Zealand is generally believed to be a green and nature-related destination and its ski areas still blend well into the natural environment. Hence, there is some potential for the New Zealand ski industry to develop a unique product in such a way that it is both, sustainable and distinguishable from other international markets.

Um Erkenntnisse aus großen Mengen wissenschaftlicher Rohdaten zu gewinnen, sind komplexe Datenanalysen erforderlich. Scientific Workflows sind ein Ansatz zur Umsetzung solcher Datenanalysen. Um Skalierbarkeit zu erreichen, setzen die meisten Workflow-Management-Systeme auf bereits existierende Lösungen zur Verwaltung verteilter Ressourcen, etwa Batch-Scheduling-Systeme. Die Abschätzung der Ressourcen, die zur Ausführung einzelner Arbeitsschritte benötigt werden, wird dabei immer noch an die Nutzer:innen delegiert. Dies schränkt die Leistung und Benutzerfreundlichkeit von Workflow-Management-Systemen ein, da den Nutzer:innen oft die Zeit, das Fachwissen oder die Anreize fehlen, den Ressourcenverbrauch genau abzuschätzen. Diese Arbeit untersucht, wie die Ressourcennutzung während der Ausführung von Workflows automatisch erlernt werden kann. Im Gegensatz zu früheren Arbeiten werden Scheduling und Vorhersage von Ressourcenverbrauch in einem engeren Zusammenhang betrachtet. Dies bringt verschiedene Herausforderungen mit sich, wie die Quantifizierung der Auswirkungen von Vorhersagefehlern auf die Systemleistung. Die wichtigsten Beiträge dieser Arbeit sind: 1. Eine Literaturübersicht aktueller Ansätze zur Vorhersage von Spitzenspeicherverbrauch mittels maschinellen Lernens im Kontext von Batch-Scheduling-Systemen. 2. Ein Scheduling-Verfahren, das statistische Methoden verwendet, um vorherzusagen, welche Scheduling-Entscheidungen verbessert werden können. 3. Ein Ansatz zur Nutzung von zur Laufzeit gemessenem Spitzenspeicherverbrauch in Vorhersagemodellen, die die fortwährende Optimierung der Ressourcenallokation erlauben. Umfangreiche Simulationsexperimente geben Einblicke in Schlüsseleigenschaften von Scheduling-Heuristiken und Vorhersagemodellen. 4. Ein Vorhersagemodell, das die asymmetrischen Kosten überschätzten und unterschätzten Speicherverbrauchs berücksichtigt, sowie die Folgekosten von Vorhersagefehlern einbezieht. / Scientific experiments produce data at unprecedented volumes and resolutions. For the extraction of insights from large sets of raw data, complex analysis workflows are necessary. Scientific workflows enable such data analyses at scale. To achieve scalability, most workflow management systems are designed as an additional layer on top of distributed resource managers, such as batch schedulers or distributed data processing frameworks. However, like distributed resource managers, they do not automatically determine the amount of resources required for executing individual tasks in a workflow. The status quo is that workflow management systems delegate the challenge of estimating resource usage to the user. This limits the performance and ease-of-use of scientific workflow management systems, as users often lack the time, expertise, or incentives to estimate resource usage accurately. This thesis is an investigation of how to learn and predict resource usage during workflow execution. In contrast to prior work, an integrated perspective on prediction and scheduling is taken, which introduces various challenges, such as quantifying the effects of prediction errors on system performance. The main contributions are: 1. A survey of peak memory usage prediction in batch processing environments. It provides an overview of prior machine learning approaches, commonly used features, evaluation metrics, and data sets. 2. A static workflow scheduling method that uses statistical methods to predict which scheduling decisions can be improved. 3. A feedback-based approach to scheduling and predictive resource allocation, which is extensively evaluated using simulation. The results provide insights into the desirable characteristics of scheduling heuristics and prediction models. 4. A prediction model that reduces memory wastage. The design takes into account the asymmetric costs of overestimation and underestimation, as well as follow up costs of prediction errors.

Der weltweit steigende Bedarf an Energie und natürlichen Ressourcen, insbesondere an fossilen Brennstoffen und seltenen Metallen, sowie die angestrebte Reduktion des CO2-Ausstoßes führen zu steigenden Preisen für Energie und Rohstoffe. Der Energie- und Ressourcenbedarf muss daher neben der Funktionalität und den Kosten eines technischen Produkts in Planungs- und Entwicklungsprozesse einbezogen werden. Für eine Minimierung des Energie- und Ressourcenbedarfs sind insbesondere die frühen Phasen der Produktentwicklung von großem Interesse, da in diesen Phasen die wesentlichen Eigenschaften eines Produkts für den gesamten Lebenszyklus zu großen Teilen festgelegt werden. Durch die Forderung nach kürzeren Markteinführungszeiten bei gleichzeitigem Anstieg der Komplexität technischer Produkte ist der Einsatz von Softwaresystemen zur Unterstützung der Planungs- und Entwicklungsprozesse unabdingbar. Die Zielstellung der vorliegenden Arbeit ist die Entwicklung und Realisierung von Methoden und Verfahren zur softwaretechnischen Unterstützung ausgewählter Abläufe der Produktentwicklung. Die gewählten Abläufe sind die Ausarbeitung von Anforderungsspezifikationen für technische Produkte, die Priorisierung von Anforderungen sowie die Analyse und Bewertung des Energiebedarfs von Werkzeugmaschinen. Der Schwerpunkt der Methoden und Verfahren liegt einerseits auf der Strukturierung und Koordinierung der Zusammenarbeit von Domänenexperten in den ausgewählten Abläufen der Produktentwicklung und andererseits auf der Erweiterung der Abläufe um Energie- und Ressourcenbetrachtungen. Die softwaretechnische Unterstützung der gewählten Abläufe ermöglicht es, die Komplexität der zu entwickelnden Produkte beherrschbar zu machen und den manuellen Aufwand der Domänenexperten in den Abläufen zu verringern.