Simulation of SLA-based VM-scaling algorithms for cloud-distributed applications

Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.

Sports after Busy Work: Work-Related Cognitive Failure Corresponds to Risk Bearing Behaviors and Athletic Injury

Although employees are encouraged to take exercise after work to keep physically fit, they should not suffer injury. Some sports injuries that occur after work appear to be work-related and preventable. This study investigated whether cognitive failure mediates the influence of mental work demands and conscientiousness on risk-taking and risky and unaware behaviour during after-work sports activities. Participants were 129 employees (36% female) who regularly took part in team sports after work. A structural equation model showed that work-related cognitive failure significantly mediated the influence of mental work demands on risky behaviour during sports (p < .05) and also mediated the directional link between conscientiousness and risky behaviour during sports (p < .05). A path from risky behaviour during sports to sports injuries in the last four weeks was also significant (p < .05). Performance constraints, time pressure, and task uncertainty are likely to increase cognitive load and thereby boost cognitive failures both during work and sports activities after work. Some sports injuries after work could be prevented by addressing the issue of work redesign.

Impact of development of job control and task-related stressors on resigned job attitude.

With more experience in the labor market, some job characteristics increase, some decrease. For example, among young employees who just entered the labor market, job control may initially be low but increase with more routine and experience. Job control is a job resource that is valued in itself and is positively associated with job satisfaction; but job control also helps dealing with stressors at work. There is little research on correlated changes, but the existing evidence suggests a joint development over time. However, even less is known about the relevance of such changes for employees. Usually, research tends to use mean levels to predict mean levels in outcomes but development in job control and stressors may be as relevant for job satisfaction as having a certain level in those job characteristics. Job satisfaction typically is regarded as a positive attitude towards one’s work. What has received less attention is that some employees may lower their expectations if their job situation does not reflect their needs, resulting in a resigned attitude towards one’s job. The present study investigates the development of job control and task-related stressors over ten years and tests the predictive value of changes in job control and task-related stressors for resigned attitude towards one’s job. We used data from a Swiss panel study (N=356) ranging over ten years. Job control, task-related stressors (an index consisting of time pressure, concentration demands, performance constraints, interruptions, and uncertainty about tasks), and resigned attitude towards one’s job were assessed in 1998, 1999, 2001, and 2008. Latent growth modeling revealed that growth rates of job control and task-related stressors were not correlated with one another. We predicted resigned attitude towards one’s job in 2008 a) by initial levels, and b) by changes in job control and stressors, controlling for resigned attitude in 1998. There was some prediction by initial levels (job control: β = -.15, p < .05; task-related stressors: β = .12, p = .06). However, as expected, changes in control and stressors predicted resigned attitude much better, with β = -.37, p < .001, for changes in job control, and β = .31, p < .001, for changes in task-related stressors. Our data confirm the importance of having low levels of task-related stressors and higher levels of job control for job attitudes. However, development in these job characteristics seems even more important than initial levels.

Service Level Agreements-Driven Management of Distributed Applications in Cloud Computing Environments

Cloud Computing enables provisioning and distribution of highly scalable services in a reliable, on-demand and sustainable manner. However, objectives of managing enterprise distributed applications in cloud environments under Service Level Agreement (SLA) constraints lead to challenges for maintaining optimal resource control. Furthermore, conflicting objectives in management of cloud infrastructure and distributed applications might lead to violations of SLAs and inefficient use of hardware and software resources. This dissertation focusses on how SLAs can be used as an input to the cloud management system, increasing the efficiency of allocating resources, as well as that of infrastructure scaling. First, we present an extended SLA semantic model for modelling complex service-dependencies in distributed applications, and for enabling automated cloud infrastructure management operations. Second, we describe a multi-objective VM allocation algorithm for optimised resource allocation in infrastructure clouds. Third, we describe a method of discovering relations between the performance indicators of services belonging to distributed applications and then using these relations for building scaling rules that a CMS can use for automated management of VMs. Fourth, we introduce two novel VM-scaling algorithms, which optimally scale systems composed of VMs, based on given SLA performance constraints. All presented research works were implemented and tested using enterprise distributed applications.

Graph-Based Multi-Surface Segmentation of OCT Data Using Trained Hard and Soft Constraints

Optical coherence tomography (OCT) is a well-established image modality in ophthalmology and used daily in the clinic. Automatic evaluation of such datasets requires an accurate segmentation of the retinal cell layers. However, due to the naturally low signal to noise ratio and the resulting bad image quality, this task remains challenging. We propose an automatic graph-based multi-surface segmentation algorithm that internally uses soft constraints to add prior information from a learned model. This improves the accuracy of the segmentation and increase the robustness to noise. Furthermore, we show that the graph size can be greatly reduced by applying a smart segmentation scheme. This allows the segmentation to be computed in seconds instead of minutes, without deteriorating the segmentation accuracy, making it ideal for a clinical setup. An extensive evaluation on 20 OCT datasets of healthy eyes was performed and showed a mean unsigned segmentation error of 3.05 ±0.54 μm over all datasets when compared to the average observer, which is lower than the inter-observer variability. Similar performance was measured for the task of drusen segmentation, demonstrating the usefulness of using soft constraints as a tool to deal with pathologies.

Multiscale methods for shape constraints in deconvolution: Confidence statements for qualitative features

We derive multiscale statistics for deconvolution in order to detect qualitative features of the unknown density. An important example covered within this framework is to test for local monotonicity on all scales simultaneously. We investigate the moderately ill-posed setting, where the Fourier transform of the error density in the deconvolution model is of polynomial decay. For multiscale testing, we consider a calibration, motivated by the modulus of continuity of Brownian motion. We investigate the performance of our results from both the theoretical and simulation based point of view. A major consequence of our work is that the detection of qualitative features of a density in a deconvolution problem is a doable task, although the minimax rates for pointwise estimation are very slow.

Irrigation development in Eritrea: potentials and constraints: Proceedings of the workshop of AEAS and SLM Programme Eritrea

Development of irrigation, which is of crucial importance in Eritrea, is perceived by many as the main technique for improving the precarious food security situation in this Sahelian country in the Horn of Africa. The present publication presents the outcome of a nationwide workshop held in 2003, which brought together administrators, scientists, and members of public development agencies and NGOs. These workshop participants presented experiences, lessons learnt, and ideas about how to move forward in relation to development of irrigation in Eritrea. Specifically, the publication deals with the following broad themes, lessons learnt, and experiences in Eritrea: · spate irrigation systems and measurement of performance, as well as experience with modernisation of spate irrigation systems in Eritrea · small-scale irrigation systems and their potentials and pitfalls, including development of low-cost micro irrigation · climate and irrigation, including rainfall forecasts · socio-economic aspects of irrigation, including gender questions, institutional requirements, and irrigation and livelihoods The publication contains an extensive summary in the Tigrinya language, in order to facilitate access to the key findings by local non-English-speaking stakeholders in irrigation development.