Adaptation-Aware Architecture Modeling and Analysis of Energy Efficiency for Software Systems

This thesis presents an approach for the design time analysis of energy efficiency for static and self-adaptive software systems. The quality characteristics of a software system, such as performance and operating costs, strongly depend upon its architecture. Software architecture is a high-level view on software artifacts that reflects essential quality characteristics of a system under design. Design decisions made on an architectural level have a decisive impact on the quality of a system. Revising architectural design decisions late into development requires significant effort. Architectural analyses allow software architects to reason about the impact of design decisions on quality, based on an architectural description of the system. An essential quality goal is the reduction of cost while maintaining other quality goals. Power consumption accounts for a significant part of the Total Cost of Ownership (TCO) of data centers. In 2010, data centers contributed 1.3% of the world-wide power consumption. However, reasoning on the energy efficiency of software systems is excluded from the systematic analysis of software architectures at design time. Energy efficiency can only be evaluated once the system is deployed and operational. One approach to reduce power consumption or cost is the introduction of self-adaptivity to a software system. Self-adaptive software systems execute adaptations to provision costly resources dependent on user load. The execution of reconfigurations can increase energy efficiency and reduce cost. If performed improperly, however, the additional resources required to execute a reconfiguration may exceed their positive effect. Existing architecture-level energy analysis approaches offer limited accuracy or only consider a limited set of system features, e.g., the used communication style. Predictive approaches from the embedded systems and Cloud Computing domain operate on an abstraction that is not suited for architectural analysis. The execution of adaptations can consume additional resources. The additional consumption can reduce performance and energy efficiency. Design time quality analyses for self-adaptive software systems ignore this transient effect of adaptations. This thesis makes the following contributions to enable the systematic consideration of energy efficiency in the architectural design of self-adaptive software systems: First, it presents a modeling language that captures power consumption characteristics on an architectural abstraction level. Second, it introduces an energy efficiency analysis approach that uses instances of our power consumption modeling language in combination with existing performance analyses for architecture models. The developed analysis supports reasoning on energy efficiency for static and self-adaptive software systems. Third, to ease the specification of power consumption characteristics, we provide a method for extracting power models for server environments. The method encompasses an automated profiling of servers based on a set of restrictions defined by the user. A model training framework extracts a set of power models specified in our modeling language from the resulting profile. The method ranks the trained power models based on their predicted accuracy. Lastly, this thesis introduces a systematic modeling and analysis approach for considering transient effects in design time quality analyses. The approach explicitly models inter-dependencies between reconfigurations, performance and power consumption. We provide a formalization of the execution semantics of the model. Additionally, we discuss how our approach can be integrated with existing quality analyses of self-adaptive software systems. We validated the accuracy, applicability, and appropriateness of our approach in a variety of case studies. The first two case studies investigated the accuracy and appropriateness of our modeling and analysis approach. The first study evaluated the impact of design decisions on the energy efficiency of a media hosting application. The energy consumption predictions achieved an absolute error lower than 5.5% across different user loads. Our approach predicted the relative impact of the design decision on energy efficiency with an error of less than 18.94%. The second case study used two variants of the Spring-based community case study system PetClinic. The case study complements the accuracy and appropriateness evaluation of our modeling and analysis approach. We were able to predict the energy consumption of both variants with an absolute error of no more than 2.38%. In contrast to the first case study, we derived all models automatically, using our power model extraction framework, as well as an extraction framework for performance models. The third case study applied our model-based prediction to evaluate the effect of different self-adaptation algorithms on energy efficiency. It involved scientific workloads executed in a virtualized environment. Our approach predicted the energy consumption with an error below 7.1%, even though we used coarse grained measurement data of low accuracy to train the input models. The fourth case study evaluated the appropriateness and accuracy of the automated model extraction method using a set of Big Data and enterprise workloads. Our method produced power models with prediction errors below 5.9%. A secondary study evaluated the accuracy of extracted power models for different Virtual Machine (VM) migration scenarios. The results of the fifth case study showed that our approach for modeling transient effects improved the prediction accuracy for a horizontally scaling application. Leveraging the improved accuracy, we were able to identify design deficiencies of the application that otherwise would have remained unnoticed

Computing large market equilibria using abstractions

Computing market equilibria is an important practical problem for market design (e.g. fair division, item allocation). However, computing equilibria requires large amounts of information (e.g. all valuations for all buyers for all items) and compute power. We consider ameliorating these issues by applying a method used for solving complex games: constructing a coarsened abstraction of a given market, solving for the equilibrium in the abstraction, and lifting the prices and allocations back to the original market. We show how to bound important quantities such as regret, envy, Nash social welfare, Pareto optimality, and maximin share when the abstracted prices and allocations are used in place of the real equilibrium. We then study two abstraction methods of interest for practitioners: 1) filling in unknown valuations using techniques from matrix completion, 2) reducing the problem size by aggregating groups of buyers/items into smaller numbers of representative buyers/items and solving for equilibrium in this coarsened market. We find that in real data allocations/prices that are relatively close to equilibria can be computed from even very coarse abstractions

Ein Beitrag zur Validierung von Antriebssystemen mit Bezug auf kupplungs- und motorinduzierte Schwingungen

Die vorliegende Arbeit beschreibt die Entwicklung einer neuartigen Prüfstandsumgebung zur Validierung von Antriebssystemen mit physischen Kupplungs- und Dämpfersystemen, die eine detaillierte Simulation der restlichen Antriebssystemkomponenten ermöglicht. Über eine schnelle Kommunikation und hochdynamische Prüfstandsantriebe kann der Einfluss von Kupplungs- und Dämpfersystemen auf Schwingungsphänomene im gesamten Antriebssystem realistisch abgebildet werden

Adaptation-Aware Architecture Modeling and Analysis of Energy Efficiency for Software Systems

This work presents an approach for the architecture analysis of energy efficiency for static and self-adaptive software systems. It introduces a modeling language that captures consumption characteristics on an architectural level. The outlined analysis predicts the energy efficiency of systems described with this language. Lastly, this work introduces an approach for considering transient effects in design time architecture analyses

Pacing Equilibrium in First-Price Auction Markets

In the isolated auction of a single item, second price often dominates first price in properties of theoretical interest. But, single items are rarely sold in true isolation, so considering the broader context is critical when adopting a pricing strategy. In this paper, we study a model centrally relevant to Internet advertising and show that when items (ad impressions) are individually auctioned within the context of a larger system that is managing budgets, theory offers surprising endorsement for using a first price auction to sell each individual item. In particular, first price auctions offer theoretical guarantees of equilibrium uniqueness, monotonicity, and other desirable properties, as well as efficient computability as the solution to the well-studied Eisenberg-Gale convex program. We also use simulations to demonstrate that a bidder's incentive to deviate vanishes in thick markets

ResourceApp – Entwicklung eines mobilen Systems zur Erfassung und Erschließung von Ressourceneffizienzpotenzialen beim Rückbau von Infrastruktur und Produkten

Der Anteil an Bau- und Abbruchabfällen beträgt mit rund 200 Mio. t mehr als 50 % der jährlich anfallenden Abfälle in Deutschland [Statistik Portal 2015]. Dabei sind Rückbau- und Abbruchprojekte durch einen großen Zeit- und Kostendruck gekennzeichnet. Bei der heute üblichen Erfassung von Rückbauobjekten durch Begehung werden die verbauten, oft wert- haltigen Materialien grob geschätzt, was zu einer großen Abweichung zur tatsächlichen Mate- rialzusammensetzung führen kann. Dennoch dienen diese Schätzwerte zurzeit als Grundlage für das Angebot und die Projekt- und Verwertungsplanung der Rückbauunternehmer. Im Projekt ResourceApp wurde ein Demonstrator entwickelt, der erstmals die mobile, drei- dimensionale (3D) und semantische Erfassung von Gebäuden und Bauteilen und eine an- schließende Umbau- oder Rückbauplanung in Echtzeit ermöglicht. Das System besteht aus einem Sensor und Software-Modulen auf einem Laptop, die die Da- tenverarbeitung der Sensordaten erlauben, um das Rohstoffpotenzial eines Gebäudes zu be- stimmen und dessen Rückbau zu planen. Für das Gebäudeaudit wird der Innenraum erfasst und in 3D rekonstruiert sowie dessen Inventar bestimmt. Notwendige Rückbaumaßnahmen zur Wiedergewinnung der Rohstoffe werden ermittelt und geplant und daraus die Rückge- winnungskosten der Materialien bestimmt. Im Fall des Praxistests, des Krankenhauses von Bad Pyrmont, wurde das Gebäude mit dem Sensor aufgenommen, automatisiert inventarisiert und nach der Begehung rückgebaut. In der Praxis war es möglich, große Bauteile (Wände, Decken, Böden, Türen, Fenster) mit der App zu erkennen. Aufgrund schwieriger Raumgeometrien (kleine, verwinkelte und langgestreckte gleichförmige Räume), die die Aufnahme mit dem Kinect-Sensor erschwerten, konnten aber ca. 20 % der großen Bauteile nicht erkannt werden. Zudem konnte ein Großteil der zu erken- nenden Anschlüsse (wie Steckdosen), die Rückschlüsse auf die technische Gebäudeausstattung und somit auf die werthaltigen Rohstoffe des Gebäudes geben sollten, nicht erkannt werden. Hier besteht weiterer erheblicher Forschungsbedarf, da die eingesetzten Sensoren eine noch nicht ausreichende Auflösung aufweisen. Koordiniert wurde das Projekt ResourceApp vom Fraunhofer-Institut für Chemische Tech- nologie ICT. Weitere Partner waren das Fraunhofer-Institut für Graphische Datenverarbei- tung IGD, das Institut für Industriebetriebslehre und Industrielle Produktion IIP des Karlsru- her Instituts für Technologie KIT, die Abbruch- bzw. Sanierungsunternehmen Werner Otto GmbH und COSAWA Sanierung GmbH sowie das Umwelt-Beratungsbüro GPB Arke

Biomass distribution among tropical tree species grown under\ud differing regional climates

In the Neotropics, there is a growing interest in establishing plantations of native tree species for commerce, local consumption, and to replant on abandoned agricultural lands. Although numerous trial plantations have been established, comparative information on the performance of native trees under different regional environments is generally lacking. In this study, we evaluated the accumulation and partitioning of above-ground biomass in 16 native and two exotic tree species growing in replicated species selection trials in Panama under humid and dry regional environments. Seven of the 18 species accumulated greater total biomass at the humid site than at the dry site over a two-year period. Species specific biomass partitioning among leaves, branches and trunks was observed. However, awide range of total biomass found among species (from 1.06 kg for Dipteryx panamensis to 29.84 kg for Acacia mangium at Soberania) justified the used of an Aitchison log ratio transformation to adjust for size. When biomass partitioning was adjusted for size, a majority of these differences proved to be a result of the ability of the tree to support biomass components rather than the result of differences in the regional environments at the two sites. These findings were confirmed by comparative ANCOVAs on Aitchison-transformed and non-Aitchison-transformed variables. In these comparisons, basal diameter, height and diameter at breast height were robust predictors of biomass for the pooled data from both sites, but Aitchison-transformed\ud variables had little predictive power