Cloud Computing presents a novel way for businesses to procure their IT needs. Its elasticity and on-demand provisioning enables a shift from capital expenditures to operating expenses, giving businesses the technological agility they need to respond to an ever-changing marketplace. The rapid adoption of Cloud Computing, however, poses a unique challenge to Cloud providers—their already very large electricity bill and carbon footprint will get larger as they expand; managing both costs is therefore essential to their growth. This thesis squarely addresses the above challenge. Recognizing the presence of Cloud data centers in multiple locations and the differences in electricity price and emission intensity among these locations and over time, we develop an optimization framework that couples workload distribution with time-varying signals on electricity price and emission intensity for financial and environmental benefits. The framework is comprised of an optimization model, an aggregate cost function, and 6 scheduling heuristics. To evaluate cost savings, we run simulations with 5 data centers located across North America over a period of 81 days. We use historical data on electricity price, emission intensity, and workload collected from market operators and research data archives. We find that our framework can produce substantial cost savings, especially when workloads are distributed both geographically and temporally—up to 53.35% on electricity cost, or 29.13% on carbon cost, or 51.44% on electricity cost and 13.14% on carbon cost simultaneously.

The aim of the study: to determine and compare the low frequency fatigue of the legs’ muscles of 12–13 years old boys during the isometric and eccentric-concentric physical exercises. The objectives of the study: 1. To determine the exertion of low frequency fatigue during isometric exercises in boys. 2. To determine the exertion of low frequency fatigue during eccentric-concentric exercises in boys. 3. To compare the exertion of low frequency fatigue among isometric and eccentric-concentric exercises in boys. Subjects. Healthy boys (n = 6) aged 12–13 (12,4 ± 0,6) who do not participate in sports regularly but attend the classes of physical education twice a week. The rest period between the studies was three weeks. The tension was set up at 50 % MVS level. After that the values of the contractions and relaxations of the muscles were registered as follows: 1. The strength of muscle contraction caused by a single electric stimulus (Pt); 2. The strength of muscle contraction (P) caused by the following regiments of electrostimulation: 7 Hz (P7), 10 Hz (P10), 15 Hz (P15), 20 Hz (P20), and 100 Hz (P100) (the duration of the stimulation – 1 s, and the rest intervals between stimulations – 5 s); 3. Maximal voluntary strength (MVS) of muscle contractions (three trials every 3 minutes); 4. The workout (10 minutes of slow pedaling on the ergometer: the heart rate contractions from 110 to 130 times per minute); 5. Isometric workload: 18 times, each lasts 15 s, 40 % MVS contraction... [to full text]

The concept of home care nursing workload has not been widely studied and no evidence was found that an analysis of the concept had been undertaken. Consequently, there was a knowledge gap regarding the definition and attributes for the concept of home care nursing workload as it is currently experienced. To address that gap, a descriptive, three-phase, mixed methods (quantitative and qualitative) study was conducted. In Phase One, Rodgers’ (2000) evolutionary method was used to analyze the concept of home care nursing workload based on the empirical literature. Phase Two was situated within the naturalistic inquiry paradigm and involved observation of ten home care registered nurses during their visits to 61 patients. In Phase three a questionnaire was administered to validate the draft definition and attributes for the concept of home care nursing workload. It was completed by 88 home care nursing experts from clinical practice, education, management and research. Qualitative findings were analyzed using inductive content analysis. Quantitative data were analyzed descriptively using SPSS. Data triangulation was used extensively within and between the study phases. Of 14 attributes in the phase three draft concept definition, respondents assigned the highest level of relevance to the attribute of cognitive effort and the lowest to physical effort. The final definition contained 20 attributes and includes the following excerpt: “Home care nursing workload is the totality of the cognitive, emotional and physical effort home care nurses expend to meet the expectations of all stakeholders in providing holistic, outcome directed and patient/family focused care within the context of a short or long-term therapeutic relationship.” Respondents reported high levels of agreement with the accuracy and completeness of the definition and the majority indicated the definition would be useful or very useful in their day-to-day work. The comprehensive concept exemplar that emerged from the study includes each of the identified attributes. The study findings provided evidence of the complexity and challenge inherent in quantitatively measuring home care nursing workload. Accordingly, implications of the findings are shared for the management and monitoring of workload and associated outcomes, as well as for nursing practice, education and research.

The concept of home care nursing workload has not been widely studied and no evidence was found that an analysis of the concept had been undertaken. Consequently, there was a knowledge gap regarding the definition and attributes for the concept of home care nursing workload as it is currently experienced. To address that gap, a descriptive, three-phase, mixed methods (quantitative and qualitative) study was conducted. In Phase One, Rodgers’ (2000) evolutionary method was used to analyze the concept of home care nursing workload based on the empirical literature. Phase Two was situated within the naturalistic inquiry paradigm and involved observation of ten home care registered nurses during their visits to 61 patients. In Phase three a questionnaire was administered to validate the draft definition and attributes for the concept of home care nursing workload. It was completed by 88 home care nursing experts from clinical practice, education, management and research. Qualitative findings were analyzed using inductive content analysis. Quantitative data were analyzed descriptively using SPSS. Data triangulation was used extensively within and between the study phases. Of 14 attributes in the phase three draft concept definition, respondents assigned the highest level of relevance to the attribute of cognitive effort and the lowest to physical effort. The final definition contained 20 attributes and includes the following excerpt: “Home care nursing workload is the totality of the cognitive, emotional and physical effort home care nurses expend to meet the expectations of all stakeholders in providing holistic, outcome directed and patient/family focused care within the context of a short or long-term therapeutic relationship.” Respondents reported high levels of agreement with the accuracy and completeness of the definition and the majority indicated the definition would be useful or very useful in their day-to-day work. The comprehensive concept exemplar that emerged from the study includes each of the identified attributes. The study findings provided evidence of the complexity and challenge inherent in quantitatively measuring home care nursing workload. Accordingly, implications of the findings are shared for the management and monitoring of workload and associated outcomes, as well as for nursing practice, education and research.

Cloud Computing presents a novel way for businesses to procure their IT needs. Its elasticity and on-demand provisioning enables a shift from capital expenditures to operating expenses, giving businesses the technological agility they need to respond to an ever-changing marketplace. The rapid adoption of Cloud Computing, however, poses a unique challenge to Cloud providers—their already very large electricity bill and carbon footprint will get larger as they expand; managing both costs is therefore essential to their growth. This thesis squarely addresses the above challenge. Recognizing the presence of Cloud data centers in multiple locations and the differences in electricity price and emission intensity among these locations and over time, we develop an optimization framework that couples workload distribution with time-varying signals on electricity price and emission intensity for financial and environmental benefits. The framework is comprised of an optimization model, an aggregate cost function, and 6 scheduling heuristics. To evaluate cost savings, we run simulations with 5 data centers located across North America over a period of 81 days. We use historical data on electricity price, emission intensity, and workload collected from market operators and research data archives. We find that our framework can produce substantial cost savings, especially when workloads are distributed both geographically and temporally—up to 53.35% on electricity cost, or 29.13% on carbon cost, or 51.44% on electricity cost and 13.14% on carbon cost simultaneously.

Thesis (M.A. (Social Work)) -- University of Limpopo, 2017 / The aim of the study was to explore the factors that contribute to occupational stress among the fire-fighters employed by the Polokwane Local Municipality, Capricorn District of Limpopo. The study focused on the following variables: working relationships, work load, nature of work, deadlines pressure and work-home balance. The nature of the study is qualitative. The study data was collected from July to September 2015. The researcher interviewed fire-fighters in Polokwane Local Municipality. An in-depth semi-structured interview was utilised as the data collection method. The instrument used in the study was a semi structured interview schedule. Data was thematically analysed. The study findings showed that working relationships, work-load, nature of work, deadline pressure and work-home balance contributed to occupational stress. The study also found that occupational stress had negative effects on both the fire-fighters and their organisation

No description available.

Autonomic management is important in storage systems and the space of autonomics in storage systems is vast. Such autonomic management systems can employ a variety of techniques depending upon the specific problem. In this thesis, we first take an algorithmic approach towards reliability enhancement and then we use learning along with a reactive framework to facilitate storage optimization for applications. We study how the reliability of non-repairable systems can be improved through automatic reconfiguration of their XOR-coded structure. To this regard we propose to increase the fault tolerance of non-repairable systems by reorganizing the system, after a failure is detected, to a new XOR-code with a better fault tolerance. As errors can manifest during reorganization due to whole reads of multiple submodules, our framework takes them in to account and models such errors as based on access intensity (ie.BER-biterrorrate). We present and evaluate the reliability of an example storage system with and without reorganization. Motivated by the critical need for automating various aspects of data management in virtualized data centers, we study the specific problem of automatically implementing Virtual Machine (VM) migration in a dynamic environment according to some pre-set policies. This is a problem that requires automated identification of various workloads and their execution environments running inside virtual machines in a non-intrusive manner. To this end we propose AuM (for Autonomous Manager) that has the capability to learn workloads by aggregating variety of information obtained from network traces of storage protocols. We use state of the art Machine Learning tools, namely Multiple Kernel learning ,to aggregate information and show that AuM is indeed very accurate in identifying work loads, their execution environments and is also successful in following user set policies very closely for the VM migration tasks. Storage infrastructure in large-scale cloud data center environments must support applications with diverse, time-varying data access patterns while observing the quality of service. To meet service level requirements in such heterogeneous application phases, storage management needs to be phase-aware and adaptive ,i.e. ,identify specific storage access patterns of applications as they occur and customize their handling accordingly. We build LoadIQ, an online application phase detector for networked (file and block) storage systems. In a live deployment , LoadIQ analyzes traces and emits phase labels learnt online. Such labels could be used to generate alerts or to trigger phase-specific system tuning.

This doctoral thesis focuses on the modification of ACC to include actual driver workload in the context of automatic headway change. ACC is a driver assistance system that automatically maintains a preliminary defined speed and permits a driver to perform manual headway changes. As drivers show worse (brake) reaction times under high workload situations, the system increases headway accordingly. Driver workload is estimated based on physiological data. Here, we investigate the possibilities of such a system, assuming that physiological sensors can be implemented in future vehicles. The thesis consists of three parts: In the first part, the theoretical background is described and a suitable theoretical model is developed; in the second part, experiments are described, and in the last part, results are discussed. Altogether four experiments support this thesis: 1. The first experiment investigates the foundational relationships between physiology, brake reaction time and workload level. The study employs a simulator setting and results show that physiological data, such as heart rate and skin conductance, permit the identification of different workload levels. These findings validate the results of other studies showing that workload leads to an increase in reaction time. These results could only be validated between the extremes “no-workload” and “high workload” situations. 2. The second experiment simulates an ideal workload-adaptive cruise control (WACC) system. In a simulator setting, system acceptance and awareness are studied, with a view toward future implementation in a real car. The results show better acceptance of WACC in comparison with ACC when subjects receive additional information about the new system. This is because subjects do not perceive changes in distance under high workload conditions. 3. The third experiment focuses on acceptance of the simulated system in on-road conditions. In this study, WACC is integrated in the car and is operated using a MATLAB model. The experiment shows that more subjects notice changes in distance in the on-road condition. In general WACC is preferred over ACC; it is especially these subjects who do not notice changes in distance, who value WACC more than ACC. With the aim of implementing an operational WACC that is capable of adjusting distance according to changes in physiological data, a workload algorithm is developed. 4. The fourth experiment validates the workload algorithm. Results of the algorithm are compared with recordings of the activated workload task and detection rate is calculated. The detection of workload periods was feasible in nearly every case and detection rate was favorable, especially if one considers lags due to design-related latency periods. The experiments presented here indicate that workload is detectable in physiological data and that it influences brake reaction time. Further, we provide evidence pointing to the technical possibility of implementing WACC as well as positive acceptance. The results have been published as an article and are part of this thesis. Also, some parts of the thesis are published as a book chapter (see footnotes). Another publication is in preparation, coauthored by diploma thesis students, who are supervised by the author (consult footnotes). This dissertation is composed, in part, of these publications. References to page numbers of the diploma theses are given to ensure correspondence. The author escorted the topic WACC from the beginning to the end. Sometimes students were involved and intensively supervised, from a thematic as well as a personnel guidance perspective. The author planned the whole project and executed studies and calculations. His psychology insights were not only limited to the discipline of psychology but were furthermore, with the help of students, interdisciplinarily expanded to the subject of informatics. Every study and every result which is presented within this work, was conducted or achieved by the author or (if students supported him) was discussed with the author in weekly discussions (and often several times a day). In these discussions the author provided new ideas and corrections if necessary. Apart from that, the author looked after the fulfillment of the central theme, implemented his psychological knowledge on a daily basis and provided his expertise to complement interdisciplinary point of views. He discussed the central theme as well as details with external partners like the MIT AgeLab as well as professors of the European Union from the adaption project (a project aimed at educating future researchers which includes involvement of highly important commercial and educational partners) and beyond. In this time he also visited conferences and accumulated knowledge which led to the successful achievements of the main objective and he was relevant in reaching the common goals of the adaption project. Furthermore he presented the results of the scientific work on a conference, workshops and in written publications. Within BMW Group Research and Technology, he identified important department- and project- partners and combined the knowledge to a result which benefits science and economy. / In dieser Dissertation wird eine Abwandlung des Active Cruise Control (ACC) untersucht, das zusätzlich die Belastung (Workload) des Fahrers als Parameter betrachtet, um den Abstand zum Vordermann automatisiert zu verändern. Bei diesem ACC handelt es sich um ein Fahrerassistenzsystem, das automatisiert die eingestellte Geschwindigkeit hält und eine manuelle (durch den Nutzer ausgelöste) Abstandsveränderung zum Vordermann ermöglicht. Da sich die Bremsreaktionszeit von Fahrern in hohen Belastungssituationen verschlechtert, soll das entwickelte Workload-adaptive Cruise Control (WACC) in Situationen hoher Belastung den Abstand zum Vordermann automatisiert erhöhen. Die Belastung des Fahrers soll durch physiologische Daten ermittelt werden. Die vorliegende Arbeit untersucht die Möglichkeit eines solchen Systems unter der Annahme, dass in Zukunft geeignete physiologische Sensoren ins Auto eingebaut werden können. Die Arbeit besteht aus drei Teilen: • Im ersten Teil wird der theoretische Hintergrund beschrieben und ein passendes theoretisches Modell entwickelt. • Im zweiten Teil werden die durchgeführten Experimente beschrieben. • Im dritten Teil werden die Ergebnisse diskutiert. Insgesamt wurden im Rahmen dieser Arbeit vier Experimente durchgeführt: Das erste Experiment beschäftigte sich mit den grundlegenden Zusammenhängen zwischen Physiologie, Bremsreaktionszeit und Belastungslevel. Wie die Ergebnisse der im Simulator durchgeführten Studie zeigen, können mit physiologischen Daten wie Herzrate, Herzratenvariabilität und Hautleitfähigkeit unterschiedliche Workloadlevel identifiziert werden. Darüber hinaus wurden die Ergebnisse anderer Studien bestätigt, die belegen, dass Workload die Bremsreaktionszeit erhöht, wobei dies nur im Kontrast zwischen den Extrembereichen „kein Workload“ und „hoher Workload“ nachweisbar ist. Das zweite Experiment diente der Simulierung eines perfekten WACC. Im Simulator wurden Akzeptanz und Systemwahrnehmung getestet, um vor der Implementierung in ein Realfahrzeug weitere Erkenntnisse zu gewinnen. Im Vergleich zum ACC wurde das WACC von den Probanden besser akzeptiert, nachdem sie zusätzliche Informationen zum neuen System erhalten hatten. Der wesentliche Grund dafür ist, dass die Probanden ohne Informationen die Abstandsveränderung bei hohem Workload nicht realisieren. Das dritte Experiment fokussierte auf die Akzeptanz des simulierten Systems unter Realbedingungen. Das WACC wurde in das Auto integriert und durch ein MATLAB Modell gesteuert. Als Ergebnis zeigte sich, dass unter Realbedingungen mehr Probanden die Abstandsveränderung realisieren als im Simulator. Generell wird das WACC präferiert – vor allem jene Probanden, die die Abstandsveränderung nicht realisieren, bewerten das WACC besser als das ACC. Mit den in diesem Teilexperiment erhobenen Daten wurde ein Algorithmus zur Workloaderkennung entwickelt. Auf dieser Basis konnte im letzten Experiment ein Realsystem implementiert werden, das aufgrund physiologischer Daten den Abstand verändert. Das vierte Experiment beschäftigte sich mit der Validierung des Algorithmus zur Workloaderkennung. Die Ergebnisse des Algorithmus wurden mit der aufgezeichneten Aktivierung des Workloadtasks verglichen und eine Detektionsrate ermittelt. Die Detektion der Workloadperioden gelingt in fast allen Fällen und die Detektionsrate ist vielversprechend, gerade wenn man Verzögerungen berücksichtigt, die wegen der Latenzzeit körperlicher Reaktionen nicht verbesserungsfähig sind. In den vorliegenden Experimenten konnte gezeigt werden, dass Workload über die Physiologie messbar ist und sich auf die Bremsreaktionszeit auswirkt. Darüber hinaus wurde gezeigt, dass ein WACC technisch machbar ist und die Ergebnisse lassen außerdem auf eine hohe Akzeptanz schließen. Die Forschungsergebnisse wurden in einem Artikel publiziert, der auch in dieser Dissertation zu finden ist. Teile der vorliegenden Arbeit wurden außerdem als Buchkapitel veröffentlicht (siehe Fußnoten), eine weitere Publikation mit den vom Autor umfassend betreuten Diplomanden ist in Ausarbeitung. Um die Nachvollziehbarkeit zu gewährleisten, wurde auf die Seitenzahlen der entsprechenden Diplomarbeiten verwiesen. Als Autor dieser Dissertation habe ich das Thema WACC von Anfang bis Ende selbst erarbeitet bzw. wurden Studenten eingesetzt und angeleitet, wo es sinnvoll erschien. Neben der fachlichen wie personellen Führung der Studenten umfassten meine Aufgaben die Planung des Gesamtprojekts, das Durchführen der Studien und die Berechnung von Kennzahlen – sowohl in meinem eigenen psychologischen Fachgebiet als auch interdisziplinär mit Hilfe von Experten aus der Informatik. Jedes Ergebnis, das in dieser Arbeit präsentiert wird, wurde entweder von mir selbst erzielt oder – sofern ich dabei von Studenten unterstützt wurde – mit mir in wöchentlichen (oft auch mehrmals täglich stattfindenden Meetings) besprochen. Wichtig war mir als Autor, einen durchgängigen Weg zur Entwicklung eines WACC zu wahren, mein psychologisches Fachwissen täglich anzuwenden und in interdisziplinären Aufgaben und Diskussionen meine Perspektive einzubringen. Besonders wichtig war dabei die Diskussion des Gesamtprojekts und der Details mit externen Partnern wie dem MIT AgeLab oder Professoren aus der Europäischen Union im Rahmen des Adaptation Projekts (ein von der EU gefördertes Projekt zur Ausbildung von Forschern, unter Einbindung wirtschaftlich und wissenschaftlich hochrangiger Partner). Durch die Präsentation der Ergebnisse auf Konferenzen, in Workshops und Publikationen konnte ich einen Beitrag dazu leisten, um die Adaptation-Ziele zu erreichen. Innerhalb der BMW Group Forschung und Technik habe ich darauf geachtet, relevante Schnittstellen- und Projektpartner zu identifizieren und das erlangte Wissen zu einem Ergebnis zu verbinden, das Wissenschaft und Wirtschaft gleichermaßen nützt.

Server consolidation is currently widely employed in order to improve the energy efficiency of data centers. While being a promising technique, server consolidation may lead to resource interference between applications and thus, reduced performance of applications. Current approaches to account for possible resource interference are not well suited to respect the variation in the workloads for the applications. As a consequence, these approaches cannot prevent resource interference if workload for applications vary. It is assumed that having models for the resource utilization and power consumption of applications as functions of the workload to the applications can improve decision making and help to prevent resource interference in scenarios with varying workload. This thesis aims to develop such models for selected applications. To produce varying workload that resembles statistical properties of real-world workload a workload generator is developed in a first step. Usually, the measurement data for such models origins from different sensors and equipment, all producing data at different frequencies. In order to account for these different frequencies, in a second step this thesis particularly investigates the feasibility to employ quantile functions as model inputs. Complementary, since conventional goodness-of-fit tests are not appropriate for this approach, an alternative to assess the estimation error is presented. / Serverkonsolidierung wird derzeit weithin zur Verbesserung der Energieeffizienz von Rechenzentren eingesetzt. Während diese Technik vielversprechende Ergebnisse zeitigt, kann sie zu Ressourceninterferenz und somit zu verringerter Performanz von Anwendungen führen. Derzeitige Ansätze, um dieses Problem zu adressieren, sind nicht gut für Szenarien geeignet, in denen die Workload für die Anwendungen variiert. Als Konsequenz daraus folgt, dass diese Ansätze Ressourceninterferenz in solchen Szenarien nicht verhindern können. Es wird angenommen, dass Modelle für Anwendungen, die deren Ressourenauslastung und die Leistungsaufnahme als Funktion der Workload beschreiben, die Entscheidungsfindung bei der Konsolidierung verbessern und Ressourceninterferenz verhindern können. Diese Arbeit zielt darauf ab, solche Modelle für ausgewählte Anwendungen zu entwickeln. Um variierende Workload zu erzeugen, welche den statistischen Eigenschaften realer Workload folgt, wird zunächst ein Workload-Generator entwickelt. Gewöhnlicherweise stammen Messdaten für die Modelle aus verschienenen Sensoren und Messgeräten, welche jeweils mit unterschiedlichen Frequenzen Daten erzeugen. Um diesen verschiedenen Frequenzen Rechnung zu tragen, untersucht diese Arbeit insbesondere die Möglichkeit, Quantilfunktionen als Eingabeparameter für die Modelle zu verwenden. Da konventionelle Anpassungsgütetests bei diesem Ansatz ungeeignet sind, wird ergänzend eine Alternative vorgestellt, um den durch die Modellierung entstehenden Schätzfehler zu bemessen.