Дисертації з теми "Workload"

There is an ongoing debate regarding the construct of team workload and a central point in that debate is team workload’s relation to individual workload. This study set out to investigate this relationship. To assess the participants workload a microworld called C3Fire was used to simulate a complex control situation in which teams had to cooperate to complete the task of fighting a forest fire. Twelve teams that consisted of four members in each team were recruited. In the microworld each member of the team took on one out of four separate roles and completed three different scenarios with varying degree of difficulty in C3Fire. After each scenario, a number of questionnaires aimed at gauging different aspects of the teams’ experience in the microworld was administered. The questionnaire in focus of the current study was the DATMA questionnaire, which was used to measure individual workload and team workload. To assert the relationship between the two constructs a multiple linear regression was conducted. The results provided showed that individual workload could be used as a significant predictor for modeling team workload. The study therefore concludes that there is evidence for a relationship in which each team members individual workload could be the parts of the total sum of team workload.

Thesis (M.S.) -- University of Maryland, College Park, 2005.
Thesis research directed by: Dept. of Computer Science. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

The primary contribution of this thesis is the development of a new performance metric, Capacity, which evaluates the performance of Chip Heterogeneous Multiprocessors (CHMs) that process multiple heterogeneous channels. Performance metrics are required in order to evaluate any system, including computer systems. A lack of appropriate metrics can lead to ambiguous or incorrect results, something discovered while developing the secondary contribution of this thesis, that of workload modes for CHMs â or Workload Specific Processors (WSPs). For many decades, computer architects and designers have focused on techniques that reduce latency and increase throughput. The change in modern computer systems built around CHMs that process multi-channel communications in the service of single users calls this focus into question. Modern computer systems are expected to integrate tens to hundreds of processor cores onto single chips, often used in the service of single users, potentially as a way to access the Internet. Here, the design goal is to integrate as much functionality as possible during a given time window. Without the ability to correctly identify optimal designs, not only will the best performing designs not be found, but resources will be wasted and there will be a lack of insight to what leads to better performing designs. To address performance evaluation challenges of the next generation of computer systems, such as multicore computers inside of cell phones, we found that a structurally different metric is needed and proceeded to develop such a metric. In contrast to single-valued metrics, Capacity is a surface with dimensionality related to the number of input streams, or channels, processed by the CHM. We develop some fundamental Capacity curves in two dimensions and show how Capacity shapes reveal interaction of not only programs and data, but the interaction of multiple data streams as they compete for access to resources on a CHM as well. For the analysis of Capacity surface shapes, we propose the development of a demand characterization method in which its output is in the form of a surface. By overlaying demand surfaces over Capacity surfaces, we are able to identify when a system meets its demands and by how much. Using the Capacity metric, computer performance optimization is evaluated against workloads in the service of individual users instead of individual applications, aggregate applications, or parallel applications. Because throughput was originally derived by drawing analogies between processor design and pipelines in the automobile industry, we introduce our Capacity metric for CHMs by drawing an analogy to automobile production, signifying that Capacity is the successor to throughput. By developing our Capacity metric, we illustrate how and why different processor organizations cannot be understood as being better performers without both magnitude and shape analysis in contrast to other metrics, such as throughput, that consider only magnitude. In this work, we make the following major contributions: â ¢ Definition and development of the Capacity metric as a surface with dimensionality related to the number of input streams, or channels, processed by the CHM. â ¢ Techniques for analysis of the Capacity metric. Since the Capacity metric was developed out of necessity, while pursuing the development of WSPs, this work also makes the following minor contributions: â ¢ Definition and development of three foundations in order to establish an experimental foundation â a CHM model, a multimedia cell phone example, and a Workload Specific Processor (WSP). â ¢ Definition of Workload Modes, which was the original objective of this thesis. â ¢ Definition and comparison of two approaches to workload mode identification at run time; The Workload Classification Model (WCM) and another model that is based on Hidden Markov Models (HMMs). â ¢ Development of a foundation for analysis of the Capacity metric, so that the impact of architectural features in a CHM may be better understood. In order to do this, we develop a Demand Characterization Method (DCM) that characterizes the demand of a specific usage pattern in the form of a curve (or a surface in general). By doing this, we will be able to overlay demand curves over Capacity curves of different architectures to compare their performance and thus identify optimal performing designs.
Ph. D.

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

The present research developed and assessed the Team Workload Questionnaire (TWLQ). Despite extensive workload studies, little research has been conducted on the workload experienced by teams. Team workload has largely been ignored by research with no validated theory constructed or dedicated team workload measures available to researchers and practitioners. The research was conducted in two studies with study 1 focusing on the development of the TWLQ with 216 members of sports team completing a team workload measure after games or practise. In study 2, 14 dyadic teams performed two sessions of an unmanned aerial vehicle (UAV) search-and-rescue task. The TWLQ was used to measure the team workload demand of the task. Study 1: Principle Axis Factoring method with Direct Oblimin rotation indicated three separate factors for the TWLQ with the factors classified as Task Workload, Team Workload, and Task-Team Balancing. Study 2: The TWLQ exhibited differential sensitivity, with the three factors measuring unique components of the workload demands in teams. The TWLQ is a valid and reliable subjective measure that can be used to assess the workload demand in team tasks. It provides researchers a tool to advance the understating of team workload and gives practitioners the means to assess the workload demands of team tasks in applied settings.

Advanced development in processor design, increasing the heterogeneity of computer system, by involving Graphics Processing Units (GPUs), Field-Programmable Gate Arrays (FPGAs) and custom accelerators, and increasing the number of cores and threads in such systems puts extra pressure on the main memory, demanding a higher performance. Current computing trends are putting ever more pressure on main memory. In modern computer systems, this is generally Dynamic Random Access Memory (DRAM) which consists of a multi-level access hierarchy (e.g. Rank, Bank, Row etc.). This heterogeneity of structure implies different access latencies (and power consumption), resulting in performance differences according to memory access patterns. DRAM controllers manage access and satisfy the timing constraints and now employ complex scheduling and prediction algorithms to mitigate the effect on performance. This complexity can limit the scalability of a controller with the size of memory, while maintaining performance. The focus of this PhD thesis is to improve performance, reliability and scalability (with respect to memory size) of DRAM controllers. To this end, it covers three significant contributors to the performance and reliability of a memory controller: ‘Address Mapping’, ‘Page Closure Policies’ and ‘Reliability Monitoring’. A detailed DRAM simulator is used as an evaluation platform throughout this work. The following contributions are presented in this thesis. Hybrid Address-based Page PolicY (HAPPY): Memory controllers have used static page-closure policies to decide whether a row should be left open (open-page policy) or closed immediately (close-page policy) after use. The appropriate choice can reduce the average memory latency. Since access patterns are dynamic, static page policies cannot guarantee to deliver optimum execution time. Hybrid page policies can cover dynamic scenarios and are now implemented in state-of-the-art processors. These switch between open-page and close-page policies by monitoring the access pattern of row hits/conflicts and predicting future behaviour. Unfortunately, as the size of DRAM memory increases, fine-grain tracking and analysis of accesses does not remain practical. HAPPY proposes a compact, memory address-based encoding technique which can maintain or improve page closure predictor performance while reducing the hardware overhead. As a case study, HAPPY is integrated, with a state-of-the-art monitor – the Intel-adaptive open-page policy predictor employed by the Intel Xeon X5650 – and a traditional Hybrid page policy. The experimental results show that using the HAPPY encoding applied to the Intel-adaptive page closure policy can reduce the hardware overhead by 5× for the evaluated 64 GB memory (up to 40× for a 512 GB memory) while maintaining the prediction accuracy. Dynamic Re-arrangement of Address Mapping (DReAM): The initial location of data in DRAMs is determined and controlled by the ‘address-mapping’ and even modern memory controllers use a fixed and runtime-agnostic address-mapping. On the other hand, the memory access pattern seen at the memory interface level will be dynamically changed at run-time. This dynamic nature of memory access pattern and the fixed behaviour of address mapping process in DRAM controllers, implied by using a fixed address-mapping scheme, means that DRAM performance cannot be exploited efficiently. DReAM is a novel hardware technique that can detect a workload-specific address mapping at run-time based on the application access pattern. The experimental results show that DReAM outperforms the best evaluated baseline address mapping by 5%, on average, and up to 28% across all the workloads. A Run-time Memory hot-row detectOR (ARMOR): DRAM needs refreshing to avoid data loss. Data can also be corrupted within a refresh interval by crosstalk caused by repeated accesses to neighbouring rows; this is the row hammer effect and is perceived as a potentially serious reliability and security threat. ARMOR is a novel technique which improves memory reliability by detecting which rows are potentially being “hammered” within the memory controller, which can then insert extra refresh operations. It can detect (and thus prevent) row hammer errors with minimal execution time overhead and hardware requirements. Alternatively by adding buffers inside the memory controller to cache such hammered rows, execution times are reduced with small hardware costs. The ARMOR technique is now the basis of a patent applicant and under process for commercial exploitation. As a final step of this PhD thesis, an adaptive memory controller was developed integrating HAPPY, DReAM and ARMOR into a standard memory controller. The performance and the implementation cost of such an adaptive memory controller were compared against a state-of-the-art memory controller, as a baseline. The experimental results show that the adaptive memory controller outperforms the baseline, on average by 18%, and up to 35% for some workloads, while requiring around 6 KB-900 KB more storage than the baseline to support a wide range of memory sizes (from 4 GB up to 512 GB).

The growing disparity in data storage and retrieval needs of modern applications is driving the proliferation of a wide variety of storage systems (e.g., key-value stores, cloud storage services, distributed filesystems, and flash cache, etc.). While extant storage systems are designed and tuned for a specific set of applications targeting a range of workload characteristics, they lack the flexibility in adapting to the ever-changing workload behaviors. Moreover, the complexities in implementing modern storage systems and adapting ever-changing storage requirements present unique opportunities and engineering challenges. In this dissertation, we design and develop a series of novel data management and storage systems solutions by applying a simple yet effective rule---workload awareness. We find that simple workload-aware data management strategies are effective in improving the efficiency of modern storage systems, sometimes by an order of magnitude. The first two works tackle the data management and storage space allocation issues at distributed and cloud storage level, while the third work focuses on low-level data management problems in the local storage system, which many high-level storage/data-intensive applications rely on. In the first part of this dissertation (Chapter~ref{ch:mbal}), we propose and develop MBal, a high-performance in-memory object caching framework with adaptive multi-phase load balancing, which supports not only horizontal (scale-out) but vertical (scale-up) scalability as well. MBal is able to make efficient use of available resources in the cloud through its fine-grained, partitioned, lockless design. In the second part of this dissertation (Chapter~ref{ch:cast} and Chapter~ref{ch:pricing}), we design and build CAST (Chapter~ref{ch:cast}), a Cloud Analytics Storage Tiering solution that cloud tenants can use to reduce monetary cost and improve performance of analytics workloads. The approach takes the first step towards providing storage tiering support for data analytics in the cloud. Furthermore, we propose a hybrid cloud object storage system (Chapter~ref{ch:pricing}) that could effectively engage both the cloud service providers and cloud tenants via a novel dynamic pricing mechanism. In the third part of this dissertation (Chapter~ref{ch:offline}), targeting local storage, we explore offline algorithms for flash caching in terms of both hit ratio and flash lifespan. We design and implement a multi-stage heuristic by synthesizing several techniques that manage data at the granularity of a flash erasure unit (which we call a container) to approximate the offline optimal algorithm. In the fourth part of this dissertation (Chapter~ref{ch:turnkey}), we are focused on how to enable fast prototyping of efficient distributed key-value stores targeting a proxy-based layered architecture. In this work, we design and build {con}, a framework that significantly reduce the engineering effort required to build a full-fledged distributed key-value store. Our dissertation shows that simple workload-aware data management strategies can bring huge benefit in terms of both efficiency (i.e., performance, monetary cost, etc.) and flexibility (i.e., ease-of-use, ease-of-deployment, programmability, etc.). The principles of leveraging workload dynamicity and storage heterogeneity can be used to guide next-generation storage system software design, especially when being faced with new storage hardware technologies.
Ph. D.

The purpose of this study was to explore workload allocation, what informed workload allocation in secondary schools and analyse documents relevant to educator workload. A qualitative interpretive approach using a case study as a research design was used to complete the study. Sixteen educators which consist of 6 heads of departments, principal and 9 post level one educators were purposively sampled and interviewed from different types of schools( rural, township and former model C schools). The findings of the study suggested that, workload in the secondary schools under study was allocated in a transparent and flexible manner. Educators were consulted and their inputs were regarded imperative in decision making. Further, it was found that experience, specialisation and qualifications informed workload allocation in schools. During the analysis of data, themes such as educator reputation meaning their competence, learner results and commitment emerged as factors that also informed workload allocation in schools. Allocators considered factors like the number of subjects, number of preparations and number of classes but ignored the number of learners in classes when allocating work in schools. Therefore, the differences in terms of number of learners would mean there was no equity in allocation of educators because the number of learners affected marking of assessments, feedback to learner, reaching gifted and not gifted learners, discipline in classrooms, timeous submissions of marks, and regular control of learner books. Majority of educators were allocated teaching time below the requirements as stipulated in the Personnel Administration Measures (PAM) Government Gazette No. 24948 dated 21 February 2003. Therefore workload of most educators was manageable. The majority of post level one educators were allocated teaching time below 85%. Only one post level one educator from school A and B was allocated within the stipulated teaching time as expected by the department and most educators were allocated below. From the allocation of school C only 3 post level one educators out of a maximum of twenty five paid by the government were allocated within the stipulated time. Allocation changed throughout the year because promotions and redeployment of educators were done at any time during the year.
Dissertation (MEd)--University of Pretoria, 2014.
tm2015
Education Management and Policy Studies
MEd
Unrestricted

The consumers’ increasing desire to be connected at all times and the advancement of integrated functionality within the vehicle, increases the risk that drivers could be faced with information overload while driving. Given the importance of human interaction with technology within the vehicle, automobile manufacturers are introducing workload manager systems within the vehicles to help prevent driver overload. However the ability of the system to decide in a timely manner requires anticipation of changes in workload, depending on the capacity of the driver and matching it with the demand expected from the driving task such as the dynamic traffic environment. In relation to the need to understand the influence of traffic demand on driver workload, the work here comprises the systematic manipulation of traffic complexity and exploration of workload measures to highlight which are sensitive to primary task demand manipulated. A within-subjects design was used in the studies explored in this thesis to allow comparison between different manipulated traffic conditions. In the first simulator test, the ability of various objective and subjective workload measures to tap into drivers’ momentary workload was examined. Following the identification of a subjective measure that was sensitive to the influence of lane changes performed by neighbouring vehicle on drivers’ momentary workload, the characteristics of the lane change were explored in the subsequent studies involving single and dual-task conditions. Overall, these studies suggested suppression of non-urgent communications by a workload manager during safety-critical conditions involving critical cut-ins would be advantageous to both younger and older drivers. This thesis offers a novel and valuable contribution to the design of a workload estimator so as to ensure that the driving demand is always within drivers’ capacity to avoid driver overload. Results of these studies have also highlighted the utility of vehicle-based sensor data in improving workload manager functionality.

With the widespread use of computers in today's industry, planning system configurations in computer sites plays an increasingly important role. The process of planning system configurations or determining hardware requirements for new or existing systems is commonly known as capacity planning among performance researchers and analysts. This thesis presents a refined capacity planning process for centralized computing system, with special attention to characterizing user workload for capacity planning. The objective is to make the entire process simpler for the computer user community, while relieving the capacity planner or performance analyst from having to rely on guesswork for the user workload performance factors. The process is divided into four phases; namely, data collection, data reduction, workload/user classification and, modeling and performance analysis. The second and third phases are collectively known as user workload characterization. The main objective of our workload characterization is to avoid any guess work on the performance factors that cannot be easily measured. The results of the workload characterization process are specifically meant to be used in analytic and simulation modeling. Three software tools required for the data reduction, workload/user classification and performance analysis phases have been developed and are discussed in the thesis.
Science, Faculty of
Computer Science, Department of
Graduate

Workload Control (WLC) is one of few Production Planning & Control (PPC) solutions appropriate for Make- To-Order (MTO) companies and Small & Medium sized Enterprises (SMEs), yet its successful implementation remains an enduring challenge. Much research attention has focused on developing the concept in a theoretical or simulation context; relatively little has focused on implementing the concept in practice, and more empirical evidence is needed on successful implementations. Of the few successful WLC implementations which have been published previously, the focus has been on the result of implementation while the process of implementation itself is still a 'black box'. Where more detail on the implementation process has been given in previous studies, evidence of effectiveness in practice has not been provided. To address this research gap, this thesis presents a successful implementation of a comprehensive WLC approach through action research; this is the first study which demonstrates the impact of WLC on performance in practice alongside a detailed account of the implementation process. Performance improvements observed include: reduced lead times; improvements in lateness and tardiness; reduced costs; improved internal and external co-ordination; and higher quality. In addition to details of this successful implementation, a wider body of evidence on the characteristics of MTO SMEs that affect WLC implementation has been obtained through a survey of 41 companies using semi-structured face-to-face interviews. This compensates for the limitation of a single case and adds an element of generality to the research findings. Thus, a generalised set of WLC specific implementation issues and an implementation strategy for the widespread adoption of WLC in practice has been developed.

The purpose of this thesis was to design and implement a program that can simulate configurable workload similar to a Virtual Network Function (VNF). When designing a Network Function Virtualization solution the contents of the environment are not always known and in these cases it would be helpful to have a simulator that can generate workload similar to VNFs. Characteristics of applications were studied and the simulator presented in this paper is able to generate workload based on a given configuration.

Thesis (MTech (Business Administration))--Cape Technikon, Cape Town, 2000
The current rationalisation of health care in the Western Cape may result in a decrease in the number of patients attending the Trauma Unit at Groote Schuur Hospital (GSH), one of the two large tertiary care hospitals in the Western Cape. This in turn may result in cuts in staff allocations to this unit. The nursing staff need to be proactive in preventing potential cuts which may compromise the services that they offer. Current statistics collected by nursing managers in the trauma unit at GSH provide an indication of the volume of work handled, but do not necessarily capture the intensity of that work. The purpose of this research project will determine the extent to which nursing care required by patients attending the trauma unit at GSH has increased and to establish appropriate staff workload scheduling. The existing classification systems available for assessing patient acuity levels are no longer suitable as they use patient numbers to describe workload. By using a classification system specifically developed for the use by nurse managers in high care units (trauma units), the appropriate staffing norms based on the acuity level of patients can be determined. Finally, this research project will determine a suitable model for measuring the intensity of workload specific to a trauma unit environment for the effective and efficient allocation of staff.

Human information processing consists of multiple and limited resources; some of them are shared while some are separate and non-interchangeable. High pilot mental workload (PMWL) - and the subsequent decline in performance - results from the imbalance between the mental resources available to perform the task and the amount of resources needed to perform it. When the pilot’s proficiency is evaluated, s/he should deliver an acceptable performance while being able to reserve enough mental capacity for the unexpected, additional resource demands. The task demands and cognitive stressors of air combat have potential to degrade pilot performance to an unacceptable level. Therefore, it is important to understand the amount of mental workload the pilots are experiencing and how much spare capacity they have available to cope with the possible additional resource demands. This thesis was aimed at understanding the relationship between PMWL and performance. The approach presented in this thesis was expected to support the development of reliable metrics for predicting the pilot performance under the stress of combat. In terms of practical applications, this thesis contributed to the development of the methodological principles that could help assuring the pilots’ ability to cope with the task demands higher than those experienced during training or proficiency checks. Heart rate (HR) and heart rate variation (HRV) were used as indexes of PMWL. The selection was done for several reasons. HR and HRV measures were accepted by the pilots as they were non-intrusive and they appeared to be objective. In addition, the implementation requirements were by no means excessive. Considering the aims of this thesis, the low diagnosticity of HR/HRV was not an issue. Finally, HR and HRV proved to be sensitive measures of varying task demands – especially when measured together with the pilots’ awareness of the mission requirements. Simulated fighter missions were used to manipulate the pilots’ task demand and to measure their performance and HR/HR. The thesis is constructed around three studies. In the first study, the subjects were required to fly instrument approaches in a high fidelity simulator under various levels of task demand. The task demand was manipulated by increasing the load on the subjects by reducing the range at which they commenced the approach. HR and the time domain components of HRV were used as measures of PMWL. The findings indicated that HR and HRV were sensitive to varying task demands. HR and HRV were able to distinguish the level of PMWL after which the subjects were no longer able to cope with the increasing task demands and their performance fell to a sub-standard level. The major finding of the first study was the HR/HRV’s ability to differentiate the sub-standard performance approaches from the high performance approaches. In the second study, fighter pilots’ performance and PMWL were both measured during a real instrument flight rules proficiency check in an F/A-18 simulator. PMWL was measured using HR and HRV. Performance was rated using Finnish Air Force’s official rating scales. Results indicated that HR and HRV were able to differentiate varying task demands in situations where variations in performance were insignificant. It was concluded that during a proficiency check, PMWL should be measured together with the task performance measurement. In the third study, fighter pilots’ HRV and performance were examined during instrument approaches and air combat. The subjects’ performance was rated by a weapons instructor. In addition, the subjects’ HRV was measured and used as an indicator of PMWL. During the instrument approaches, low performance was associated with high PMWL as expected. However, during the combat phases of the mission, low performance was associated with low PMWL. When the subject’s awareness of the mission requirements was studied, it was found that the combination of low performance and low PMWL was associated with the subjects’ low awareness of the mission requirements. The major finding was that unless the subjects’ awareness of the mission requirements is examined, the relationship between the mental workload and performance during a complex combat mission may be difficult to explain. It is concluded that HR and HRV are sensitive measures of PMWL in a simulated fighter aviation environment. HR and HRV proved to be associated with the changes in task demands and pilots’ performance during simulated instrument approaches and air combat. However, the results of this thesis suggest that measuring just PMWL and performance is not sufficient – especially if the task of interest is complex and dynamic. To fully understand the pilot performance in such environment, the relationship between awareness of the mission requirements, workload and performance needs to be untangled. While this thesis provides encouraging results to understand this phenomena, further research is still needed before awareness of the situation requirements (or more broadly, situation awareness), performance and mental workload can be measured simultaneously, objectively and in real time.

Workload transitions are situations where operators are suddenly confronted with levels of workload substantially different from previously established levels. Workload transitions may affect the operators' state of stress and coping behaviors but previous research has not conclusively demonstrated the nature of those. The first goal of the current work was to investigate the discrepant findings of the previous literature. Two experiments were conducted where participants were asked to perform a digit detection task that suddenly shifted between low and high event rates (i.e., low and high workload, respectively). The first experiment used a large magnitude transition that resulted in a decrease in reported levels of task engagement and effort. Over time, the reported stress and workload ratings of the transitioned groups approached the nontransitioned control groups. A second experiment was conducted using a moderate magnitude transition. This second experiment replicated the findings from the first experiment, with the key difference being that the transition from a low to more a more moderate level of workload resulted in higher, sustained task engagement and effort. Two main conclusions are drawn from these results. First, over time the stress and workload levels of individuals who experience a transition will approach those reported by nontransitioned individuals. Future workload transition research must therefore consider the effect of the time from transition. Second, the magnitude of the transition may influence the coping response such that a moderate transition may result in increased task-oriented, effortful coping whereas a large magnitude transition may result in decreased effortful coping.

When it comes to game design, two features that have been linked to the success of a game are playability and the subjective game experience. This is perhaps not surprising, as the main purpose of a game is to entertain. What cognitive factors that may underlie these features has, however, not been explored. This study examines the relationship between both workload and cognitive workload and player experience. The results suggest that an increase in workload, including cognitive workload, positively affect the player experience of the game as well as the player’s intrinsic motivation.

Approved for public release; distribution is unlimited
The Defense Logistics Agency (DLA) predicts issue and receipt workload for its distribution agency in order to maintain adequate staffing levels and set proper rates for customers. Inaccurate forecasts lead to inaccurate staffing, subsequently leading to inaccurate pricing. DLA’s current regression forecasting model is no longer adequate for predicting future workload for DLA Distribution. We explore multiple forecasting techniques and provide a methodology for selecting a model that is a viable and accurate alternative for DLA. Our methodology encompasses best-fit determination, a comparison of predictability through back-casting, and a sensitivity exercise to see reaction and stability of our selected models’ predictions. Finally, we compare our best performing model with the current regression model to see what would have been reported if our model had been used instead of the current model for recent Program Budget Review (PBR) cycles. Our results suggest that an auto-regressive integrated moving average (ARIMA) model used with critical assessment and managerial judgment offers a viable alternative to the current model for predicting distribution workload.

The virtualization technology has many excellent features beneficial for today’s high-performance computing (HPC). It enables more flexible and effective utilization of the computing resources. However, a major barrier for its wide acceptance in HPC domain lies in the relative large performance loss for workloads. Of the major performance-influencing factors, memory management subsystem for virtual machines is a potential source of performance loss. Many efforts have been invested in seeking the solutions to reduce the performance overhead in guest memory address translation process. This work contributes two novel solutions - “DPMS” and “STDP”. Both of them are presented conceptually and implemented partially for a hypervisor - KVM. The benchmark results for DPMS show that the performance for a number of workloads that are sensitive to paging methods can be more or less improved through the adoption of this solution. STDP illustrates that it is feasible to reduce the performance overhead in the second dimension paging for those workloads that cannot make good use of the TLB.
Virtualisierungstechnologie verfügt über viele hervorragende Eigenschaften, die für das heutige Hochleistungsrechnen von Vorteil sind. Es ermöglicht eine flexiblere und effektivere Nutzung der Rechenressourcen. Ein Haupthindernis für Akzeptanz in der HPC-Domäne liegt jedoch in dem relativ großen Leistungsverlust für Workloads. Von den wichtigsten leistungsbeeinflussenden Faktoren ist die Speicherverwaltung für virtuelle Maschinen eine potenzielle Quelle der Leistungsverluste. Es wurden viele Anstrengungen unternommen, um Lösungen zu finden, die den Leistungsaufwand beim Konvertieren von Gastspeicheradressen reduzieren. Diese Arbeit liefert zwei neue Lösungen DPMS“ und STDP“. Beide werden konzeptionell vorgestellt und teilweise für einen Hypervisor - KVM - implementiert. Die Benchmark-Ergebnisse für DPMS zeigen, dass die Leistung für eine Reihe von pagingverfahren-spezifischen Workloads durch die Einführung dieser Lösung mehr oder weniger verbessert werden kann. STDP veranschaulicht, dass es möglich ist, den Leistungsaufwand im zweidimensionale Paging für diejenigen Workloads zu reduzieren, die die von dem TLB anbietende Vorteile nicht gut ausnutzen können.

The sport of cricket is challenged by three formats of the game; each with varying workload demands. The most recent format is T20 cricket, first played internationally in 2005. Further to this, elite performers are often required to play for upwards of four different professional teams across the year; increasing the complexities in player workload management and other sports science-related support. Fast bowlers have greater overall match-play demands than other playing positions in cricket. Wearable microtechnology for tracking external load in athletes is common practice. Despite microtechnology enabling meaningful analyses of workload beyond routinely reported metrics, little application has occurred within fast bowling. The high injury risk in fast bowlers is well established, yet the intensive demands on these athletes remain poorly understood. The overall aim of this program of research was to use scientific literature to first understand the interaction of workload, injury and performance in elite level fast bowlers and then improve the understanding of workload management using advances in wearable microtechnology. The program of research in this thesis “with publication” first generated studies identifying the problem (a systematic review). The four subsequent chapters of original research built on the review to profile the match-play and training demands of cricketers, explore the variability of wearable microtechnology outputs during fast bowling, and finally develop and quantify an innovative means to monitor and manage workload within the specific demands of fast bowling in cricket. Although monitoring acute and chronic workloads of fast bowlers remains the most ideal method for identifying preparedness and injury likelihood in fast bowlers, complexities exist that make the systematic prescription of bowling workloads difficult. The results confirmed that the external load of cricket match-play and training varied between fast bowlers and non-fast bowlers. Furthermore, external loads experienced by 26 elite performing cricketers differentially affected the neuromuscular, endocrine, and perceptual fatigue responses of these players. Outputs from wearable microtechnology provided adequate stability across the performance of elite fast bowlers. These outputs were comparable with routinely used measures of fast bowling performance and intensity. Algorithms linking microtechnology outputs demonstrated good sensitivity in detecting fast bowling events in elite cricketers across competition (99.5%) and training (99.0%). The specificity of detecting fast bowling events decreased in competition (74.0%) however, remained high during training (98.1%). With the ability to automatically detect fast bowling events, metrics of bowling intensity can be explored more rigorously. Outputs from the gyroscope and accelerometers in the wearable technology provided strong associations with prescribed bowling intensity. Collectively, this thesis has highlighted the challenges of applied research in cricket, and more specifically the capacity to more objectively monitor external load in cricket fast bowlers. Wearable microtechnology has the potential to advance and refine measures of bowling workload and provide a greater depth of support for cricket fast bowlers.

Las nuevas aplicaciones y servicios web, cada vez má¡s populares en nuestro día a día, han cambiado completamente la forma en la que los usuarios interactúan con la Web. En menos de media década, el papel que juegan los usuarios ha evolucionado de meros consumidores pasivos de información a activos colaboradores en la creación de contenidos dinámicos, típicos de la Web actual. Y, además, esta tendencia se espera que aumente y se consolide con el paso del tiempo. Este comportamiento dinámico de los usuarios es una de las principales claves en la definición de cargas de trabajo adecuadas para estimar con precisión el rendimiento de los sistemas web. No obstante, la dificultad intrínseca a la caracterización del dinamismo del usuario y su aplicación en un modelo de carga, propicia que muchos trabajos de investigación sigan todavía empleando cargas no representativas de las navegaciones web actuales. Esta tesis doctoral se centra en la caracterización y reproducción, para estudios de evaluación de prestaciones, de un tipo de carga web más realista, capaz de imitar el comportamiento de los usuarios de la Web actual. El estado del arte en el modelado y generación de cargas para los estudios de prestaciones de la Web presenta varias carencias en relación a modelos y aplicaciones software que representen los diferentes niveles de dinamismo del usuario. Este hecho nos motiva a proponer un modelo más preciso y a desarrollar un nuevo generador de carga basado en este nuevo modelo. Ambas propuestas han sido validadas en relación a una aproximación tradicional de generación de carga web. Con este fin, se ha desarrollado un nuevo entorno de experimentación con la capacidad de reproducir cargas web tradicionales y dinámicas, mediante la integración del generador propuesto con un benchmark de uso común. En esta tesis doctoral también se analiza y evalúa por primera vez, según nuestro saber y entender, el impacto que tiene el empleo de cargas de trabajo dinámicas en las métrica
Peña Ortiz, R. (2013). Accurate workload design for web performance evaluation [Tesis doctoral]. Editorial Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/21054
Palancia

Current literature reflects escalating concerns regarding the potential organisational damage that can result from overloaded and under loaded workforces. Overloaded and under loaded workforces have been linked to poor employee well-being, reduced productivity, dissatisfaction and higher turnover rates. This study aimed to develop a scale for the measurement of workload within South African organisations. The initial scale contained six dimensions and a total of 71 items. These items were then sent to subject matter experts in order to determine their content validity. The survey was then completed by 224 employed individuals. An exploratory factor analysis (EFA) was performed and six factors were indicated. The overall reliability of the scale was highly satisfactory with inter-correlations between scale items. The results suggest that the South African Workload Scale (SAWS) is a promising instrument for the measurement of workload within South African organisations. Copyright 2010, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. Please cite as follows: Myburgh, T 2010, A workload inventory for South African Organisations, MCom dissertation, University of Pretoria, Pretoria, viewed yymmdd < http://upetd.up.ac.za/thesis/available/etd-02212012-115206 / > C12/4/64/gm
Dissertation (MCom)--University of Pretoria, 2010.
Human Resource Management
unrestricted

Bibliography: p. 163-167.
The simulation of packet switched networks depends on accurate web workload models as input for network models. We derived a workload model for traffic generated by an individual browsing the web. We derived the workload model by studying packet traces of web traffic generated by individuals browsing the web on a campus network.

Unmanned aerial systems (UASs) often require multiple human operators fulfilling diverse roles for safe and correct operation. Reliably designing the human interaction, autonomy, and decision making aspects of these systems requires the use of modeling. We propose a conceptual model that models human machine interaction systems as a group of actors connected by a network of communication channels. We present a simulation framework implemented in Java, with an optional XML model parser that can be analyzed using the Java Pathfinder (JPF) model checker. We propose two human workload metrics based on a taxonomy extracted from the relevant literature. Using the simulator to produce a workload profile over time for each human actor, we conducted a case study by modeling a UAS integrated into the National Airspace System. Additionally we adapted an existing cognitive workload metric to act as a baseline. The results of this case study were consistent with known workload events and the results of our baseline metric.

Workers experience combined physical and mental demands in their daily jobs, yet the contribution of these concurrent demands in the development of work-related musculoskeletal disorders (WMSDs) is not clearly understood. There is a need to understand how concurrent demands interact with different work parameters, such as force levels, muscles employed, and types of exertion, to influence physiological responses. Furthermore, whether muscle capacity is altered with these concurrent demands remains unclear. The current research was conducted to address these needs through three experimental studies that evaluated changes in physiological, performance, and subjective measures. The first study investigated muscle-specific responses to concurrent physical and mental demands during intermittent static work. Mental demands adversely affected physiological responses with increasing physical demand. Furthermore, greater motor and mental performance impairment was observed at either end of the physical demand spectrum. Finally, these interactions were muscle-dependent, with postural (shoulder and torso) muscles indicating a greater propensity to interference due to concurrent demands than executive (wrist) muscles. The aim of the second study was to evaluate differential effects of exertion type (static and dynamic) during concurrent physical and mental work. Concurrent physical and mental demands adversely affected physiological responses during static exertions compared to dynamic exertions. Furthermore, static exertions were more susceptible to decrements in muscle output and mental task performance than dynamic exertions, specifically at higher force levels. The last study quantified the effects of concurrent physical and mental demands on muscle capacity (endurance, fatigue, and recovery) during intermittent static work. Additional mental processing was associated with shorter endurance times, greater strength decline, increased fatigability, and slower cardiovascular recovery. Concurrent demand conditions were also associated with higher levels of perceived fatigue, and rapid increases in rates of perceived exertion, time pressure, mental load, and stress. Overall, the current research provides a comprehensive understanding of the interactive effects of physical and mental demands on physiological responses and task performance. These findings may facilitate the development of task design strategies to help reduce the risk of workplace injuries and to increase worker performance. Finally, outcomes from this research can contribute towards the revision of current ergonomic guidelines to incorporate concurrent assessment of physical and mental demands.
Ph. D.

Abstract The psychological workload a pilot is exposed to during military flying is considered to be high, and good stress tolerance is needed. During military flying a huge amount of environmental information is transformed to neural signals which finally lead to motor and behavioral changes, and also to chemial secretion of neuroendocrine hormones. This study deals with neuroendocrine measurements performed in four procedures: psychomotor test during military pilot selection, instrument flying (IFR) with piston-engine primary trainer, real and simulated jet trainer flight, and simulated combat fighter flight. Neuroendocrine hormones, hypothalamic CRH, pituitary ACTH, beta-endorphin, prolactin and vasopressin, the adrenal hormones cortisol, adrenaline and noradrenaline and a cardiac hormone, ANP, were assayed from plasma by using immunoassay and HPLC techniques. In the psychomotor test (procedure 1) plasma prolactin, ACTH and cortisol responses were associated with a high number of delayed responses, which was used as an indicator of information overload. Anticipatory type ACTH response, i.e. high ACTH level before the test, predicted poor overall result in the psychomotor test. In response to IFR flying (procedure II) the student pilots showed increased plasma prolactin, ACTH, cortisol, adrenaline and noradrenaline levels. Postflight adrenaline response correlated significantly with poor flight performance as well as a poor psychomotor test result. Low emotional control and high performance motivation measured by an aviation psychologist correlated significantly with neuroendocrine responses after the instrument flight. Flight with jet trainer (procedure III) led to increased plasma prolactin levels, evidently due to psychological workload, but no statistically significant plasma prolactin increase was found in the simulator. This suggests that psychological workload in the flight simulator is lower compared to real jet trainer. A significant ANP response to jet trainer flight was apparently associated with increased heart rate due to psychological workload of the flight mission. Simulated combat fighter flight (procedure IV) resulted in an anticipatory type stress reaction as judged from the elevated preflight plasma ACTH, and a direct type reaction was observed in cortisol. In one pilot the neuroendocrine activation was extreme and global, suggesting low stress tolerance under high information load. Increased neuroendocrine activation is associated with psychological workload of military flying. Neuroendocrine measurements can be used in a follow-up system of military pilots.

The requirements for real-time systems in safety-critical applications typically contain strict timing constraints. The design of such a system must be subject to extensive validation to guarantee that critical timing constraints will never be violated while the system operates. A mathematically rigorous technique to do so is to perform a schedulability analysis for formally verifying models of the computational workload. Different workload models allow to describe task activations at different levels of expressiveness, ranging from traditional periodic models to sophisticated graph-based ones. An inherent conflict arises between the expressiveness and analysis efficiency of task models. The more expressive a task model is, the more accurately it can describe a system design, reducing over-approximations and thus minimizing wasteful over-provisioning of system resources. However, more expressiveness implies higher computational complexity of corresponding analysis methods. Consequently, an ideal model provides the highest possible expressiveness for which efficient exact analysis methods exist. This thesis investigates the trade-off between expressiveness and analysis efficiency. A new digraph-based task model is introduced, which generalizes all previously proposed models that can be analyzed in pseudo-polynomial time without using any analysis-specific over-approximations. We develop methods allowing to efficiently analyze variants of the model despite their strictly increased expressiveness. A key contribution is the notion of path abstraction which enables efficient graph traversal algorithms. We demonstrate tractability borderlines for different classes of schedulers, namely static priority and earliest-deadline first schedulers, by establishing hardness results. These hardness proofs provide insights about the inherent complexity of developing efficient analysis methods and indicate fundamental difficulties of the considered schedulability problems. Finally, we develop a novel abstraction refinement scheme to cope with combinatorial explosion and apply it to schedulability and response-time analysis problems. All methods presented in this thesis are extensively evaluated, demonstrating practical applicability.

Major Cloud providers offer a seemingly unlimited supply of compute resources for rent on-demand, with instances (virtual machines) being particularly popular amongst a range of service offerings. However, variation in performance across supposedly identical instances, supported by heterogeneous hardware, sold at the same price leads to variation in workload execution costs. Indeed, users pay more to have work delivered slower whilst missing out on the concomitant benefits of completing work faster and receive no performance assurances. To address price, performance, and assurance, we propose and evaluate a broker that re-prices cloud provider instances according to measured performance levels to offer performance-assured instances. Such a broker does not impose changes on Cloud provider business models, but to be viable the broker must be profitable and yet profitable Cloud brokers seem not to exist in the literature. We investigate broker profitability through simulations that model a commodity exchange analogously to extant financial exchanges, with sellers characterised in accordance with extant major Cloud providers and the broker modelled as a so-called Zero Intelligence (ZI) trading agent. Instance performance data are drawn from extensive benchmarking of Amazon’s Elastic Compute Cloud (EC2), and a Google workload trace comprising some 650,000 jobs provides for buyer willingness. The maximum profit margin that could be achieved by the proposed broker across multiple demand profiles is 4%, and achieving this requires 4 different types of hardware that exhibit an average performance degrade of 52% from best to worst. A loss is made under a variety of other conditions. At best, such a broker would support a low margin high volume business, leaving it sensitive to market competition, vagaries in demand, exchange transaction fees and gaming strategies that clients may be able to employ. As such, we question the viability of brokers proposed elsewhere which claim to offer performance services of various kinds, despite profitability not having been evaluated and, worse, without operational costs addressed. Original contributions from this research include: (1) quantification and characterisation of performance variation amongst Cloud instances; (2) a model of instance performance that is qualitatively similar to results found empirically in both cross-sectional and longitudinal studies; (3) an exposition of the underestimation of risk in extant performance improvement strategies; (4) a Cloud broker offering performance-assured instances and the set of assumptions to be met for profitability; and (5) a strategy for minimising risks to performance due to correlated instance usage.

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 89-90).
In this work we develop strategies for mining telemetry streams in virtualized clusters to automatically discover relationships between sets of virtual machines. Examples of relationships include correlations between virtual machines, similarities in resource consumption patterns or dominant resources, and similarities in metric variations. The main challenge in our approach is to transform the raw captured data consisting of resource usage and VM-related metrics into a meaningful fingerprint that identifies the virtual machine and describes its performance. In our analysis we try to determine which of these metrics are relevant and how they can be expressed as a light-weight and robust fingerprint that offers insight about the status of the machine.
by Dragos Ciprian Ionescu.
M. Eng.

Thesis advisor: Patricia Tabloski
Fatigue is a factor in human error particularly on tasks requiring sustained attention (Dinges, 1995). Work-hour studies of staff nurses have demonstrated that the risks of making an error increased when nurses worked longer shifts (Rogers, Hwang, Scott, Aiken, and Dinges, 2004. Workload in anesthesia care can vary widely with diverse cognitive and physical demands (Gaba and Lee, 1990; Weinger, Herndon, Zornow, Paulus, Gaba, and Dallen, 1994; Weinger, Reddy, and Slagle, 2004; Weinger and Slagle 2001). The purpose of the study was to examine the influence of work hours and workload on fatigue in certified registered nurse anesthetists (CRNAs). A predictive, correlational design was employed and utilized an electronic survey of 10,000 active certified and active recertified CRNAs. A total of 928 CRNAs completed the survey which included a self-report of work hours. Workload was measured by the NASA Task Load Index and fatigue by the Checklist Individual Strength (CIS-20). Hierarchical multiple regression analysis was applied to the data to test the hypotheses that 1) after controlling for demographic variables, the number of work hours and workload will positively influence post-shift fatigue in nurse anesthetists and 2) after controlling for demographic variables, there will be an interaction between work hours and workload in nurse anesthetists. Work hours and workload explained 19 % of the variance in fatigue in nurse anesthetists with the greatest contribution being from the number of work hours and the workload dimension of performance satisfaction. The study findings suggest that increasing hours of anesthesia time and increasing workload, particularly dissatisfaction with meeting the goals of the anesthetic (performance dimension) increase fatigue in nurse anesthetists. The implications for practice, policy, and research are discussed
Thesis (PhD) — Boston College, 2013
Submitted to: Boston College. Connell School of Nursing
Discipline: Nursing

Resource management is to arrange and allocate resources for computing operations and applications. In large scale data centers that contain thousands of servers, resource management is critical for efficient operation. To know workload characteristics in advance helps us proactively control resources in data centers, leading to benefits such as power savings and improved service performance. Workload prediction can be used, e.g., to decide how many resources to allocate for each application in a data center in the future. The accuracy of workload prediction varies depending on the used prediction methods and the characteristics of the workload. In this thesis work, we investigate three different methods: Linear Regression (LR), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), and Nonlinear Autoregressive Network with Exogenous Inputs (NARX). These methods are used to build models of resource consumption such as memory, CPU, and disk. Based on these models, future workload resource usage is predicted, and the accuracy of prediction is assessed. We analyze a trace from a production cluster at Google, predict resource consumption for different time intervals, and compute the error between predicted and actual values. The results show that NARX gives higher accuracy than ANFIS and LR when forecasting one-step ahead prediction, and that the ANFIS method provides the best result with multi-step ahead prediction compared to the others. Finally, time to train and re-train LR, ANFIS and NARX are computed. The running times are short, suggesting that the methods can be used in real-time operation.

Thesis (MTech(Human Resource Management))--Cape Technikon, Cape Town, 2000
This research project investigated the need for a method of determining an equitable workload for academic staffing in higher education. With the possibility of the introduction of a performance management system at the Cape Technikon it became imperative that an agreed, objective and user-friendly method of determining the workload of each academic member of staff be established. The research project established the main parameters of the job of an academic staff member and their dimensions that would influence both the quantity and quality of work produced. They were established based on the views of a panel of educators drawn from a diverse range of disciplines. Using the identified dimensions an algorithm was developed and refined to reflect the consensus views regarding the contributory weightings of each of the parameters' dimensions. This algorithm was tested and refined using a base group of academic staff who were identified by their colleagues as those whose workload could be considered a benchmark for their discipline. The most significant result of the research programme is the agreed algorithm that can form the basis for a performance management system in higher education. The user interface that was developed at the same time reflects the transparency of the system and allows for it to be adapted to the needs of various groups of users or individuals within an organisation. On the basis of this research it has been established that a system for determining an equitable workload which encompasses an extensive range of parameters can be developed using a participatory approach. Using a significant sample of academic staff as a basis, it would appear that the system is valid, reliable, useful and acceptable to academic staff in the context of a performance management system.

Understanding and identifying individuals’ capabilities and limitations has always been a challenge within work contexts, but its importance cannot be underestimated. Humans have a limited mental capacity [142], which means that they can only perform a nite set of tasks at any given period of time. Identifying these limitations is a key factor in the reduction and prevention of what is referred to as Mental Workload Overload. These measures are used in research and industry to evaluate the interaction of users with new systems and tasks. Current techniques involve asking users to subjectively assess and self report their levels of workloads using techniques and questionnaires such as NASA-TLX and Instantaneous Self-Assessment (ISA). The subjective measures become highly important when it comes to evaluating more complex systems and tasks, where performance based measures become highly difficult to measure. Even though they are critical for evaluation of these systems, there are certain limitations that cannot be overlooked when using them. Firstly, subjective measures rely on the participants’ ability to judge and report the state throughout the task. This requires not only extra effort from the operator, but also skill and potential training. Secondly, subjective measures, if used in real-time have the potential to interrupt and negatively affect performance; if used post-task, they rely on the operators’ ability to recall what happened during certain moments in the past. Direct physiological measures offer an opportunity to capture workload whilst overcoming these limitations. However, new research is needed to understand how physiological data can be interpreted within the context of theories of mental workload. The research presented in this thesis explores the use of one particular physiological approach, functional Near Infrared Spectroscopy (fNIRS), to assess workload in controlled laboratory settings, to overcome the limitations and complement the use of subjective measures; a measure based on participants’ brain and physiological responses to task demand, that is independent of the task and/or the operator (without interrupting the task or relying on the operator skill to self report). We have examined the reliability of the technique, and significantly extended our understanding of how artefacts affect recordings during both - a Verbal memory task of remembering a seven digit number and a Spacial memory task of remembering a 6x6 shaped grid. Our results showed that artefacts have a significantly different impact during the two types of tasks, further contributing insights into the existing guidelines of using fNIRS to assess workload during typical human computer interaction evaluation settings. We have further evaluated the sensitivity of the tool and understand the potential implications of using fNIRS as a measure in real-time. Our findings validated fNIRS as a sensitive workload measure, having consistent results in line with subjective measures, confirming a correlation between fNIRS and subjective workload questionnaires NASA-TLX and ISA. Having shown the relationship between fNIRS and workload, the last part of this thesis explores the use of fNIRS as a novel approach to providing users with concurrent feedback of their Mental Workload based on the measurements obtained objectively from fNIRS. We compare this feedback to traditional methods of asking users to self-assess and report their own mental workload during an Air Traffic Controller simulation game. In line with previous work, we con rm that self-reporting methods affect both perceived and actual performance. Furthermore, we found that our objective concurrent feedback technique allowed participants to reflect metacognitively on their Mental Workload during tasks, without reducing either actual or perceived performance. fNIRS showed potential to be a useful and reliable additional channel of information about the user during interaction, without further restricting the user during a typical evaluation settings. We found it sensitive to workload, being able to distinguish between various levels of workload, and with great potential for real time, continuous use during tasks. Finally, we explored a new direction of using fNIRS’s assessment of workload in real time, and we investigated how users can use feedback of their current workload state during tasks. This proved to allow users to think metacognitively about their workload during tasks, without negatively affecting their performance or workload.

The increasing demand for storage, computation, and business continuity has driven the growth of data centers. Managing data centers efficiently is a difficult task because of the wide variety of datacenter applications, their ever-changing intensities, and the fact that application performance targets may differ widely. Server virtualization has been a game-changing technology for IT, providing the possibility to support multiple virtual machines (VMs) simultaneously. This dissertation focuses on how virtualization technologies can be utilized to develop new tools for maintaining high resource utilization, for achieving high application performance, and for reducing the cost of data center management.;For multi-tiered applications, bursty workload traffic can significantly deteriorate performance. This dissertation proposes an admission control algorithm AWAIT, for handling overloading conditions in multi-tier web services. AWAIT places on hold requests of accepted sessions and refuses to admit new sessions when the system is in a sudden workload surge. to meet the service-level objective, AWAIT serves the requests in the blocking queue with high priority. The size of the queue is dynamically determined according to the workload burstiness.;Many admission control policies are triggered by instantaneous measurements of system resource usage, e.g., CPU utilization. This dissertation first demonstrates that directly measuring virtual machine resource utilizations with standard tools cannot always lead to accurate estimates. A directed factor graph (DFG) model is defined to model the dependencies among multiple types of resources across physical and virtual layers.;Virtualized data centers always enable sharing of resources among hosted applications for achieving high resource utilization. However, it is difficult to satisfy application SLOs on a shared infrastructure, as application workloads patterns change over time. AppRM, an automated management system not only allocates right amount of resources to applications for their performance target but also adjusts to dynamic workloads using an adaptive model.;Server consolidation is one of the key applications of server virtualization. This dissertation proposes a VM consolidation mechanism, first by extending the fair load balancing scheme for multi-dimensional vector scheduling, and then by using a queueing network model to capture the service contentions for a particular virtual machine placement.