PIASA: A power and interference aware resource management strategy for heterogeneous workloads in cloud data centers

Cloud data centers have been progressively adopted in different scenarios, as reflected in the execution of heterogeneous applications with diverse workloads and diverse quality of service (QoS) requirements. Virtual machine (VM) technology eases resource management in physical servers and helps cloud providers achieve goals such as optimization of energy consumption. However, the performance of an application running inside a VM is not guaranteed due to the interference among co-hosted workloads sharing the same physical resources. Moreover, the different types of co-hosted applications with diverse QoS requirements as well as the dynamic behavior of the cloud makes efficient provisioning of resources even more difficult and a challenging problem in cloud data centers. In this paper, we address the problem of resource allocation within a data center that runs different types of application workloads, particularly CPU- and network-intensive applications. To address these challenges, we propose an interference- and power-aware management mechanism that combines a performance deviation estimator and a scheduling algorithm to guide the resource allocation in virtualized environments. We conduct simulations by injecting synthetic workloads whose characteristics follow the last version of the Google Cloud tracelogs. The results indicate that our performance-enforcing strategy is able to fulfill contracted SLAs of real-world environments while reducing energy costs by as much as 21%.

Federated IaaS Resource Brokerage

This paper presents the CloudAnchor brokerage platform for the transaction of single provider as well as federated Infrastructure as a Service (IaaS) resources. The platform, which is a layered Multi-Agent System (MAS), provides multiple services, including (consumer or provider) business registration and deregistration, provider coalition creation and termination, provider lookup and invitation and negotiation services regarding brokerage, coalitions and resources. Providers, consumers and virtual providers, representing provider coalitions, are modelled by dedicated agents within the platform. The main goal of the platform is to negotiate and establish Service Level Agreements (SLA). In particular, the platform contemplates the establishment of brokerage SLA – bSLA – between the platform and each provider or consumer, coalition SLA – cSLA – between the members of a coalition of providers and resource SLA – rSLA – between a consumer and a provider. Federated resources are detained and negotiated by virtual providers on behalf of the corresponding coalitions of providers.

Potencial Utilização de um Enterprise Resource Planning System para Suportar Práticas de Gestão de Conhecimento nas Organizações. Uma Aplicação com Dynamics Nav da Microsoft

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

A technology diffusion perspective of Enterprise Resource Planning across European Small and Medium Enterprises: from determinants to Use to Value

Tese apresentada como requisito parcial para obtenção do grau de Doutor em Gestão de Informação

Computational modeling of prefrontal cortex circuits

Dissertation presented to obtain the Ph.D degree in Biology

Towards an algorithmic skeleton framework for programming the Intel R Xeon PhiTM processor

The Intel R Xeon PhiTM is the first processor based on Intel’s MIC (Many Integrated Cores) architecture. It is a co-processor specially tailored for data-parallel computations, whose basic architectural design is similar to the ones of GPUs (Graphics Processing Units), leveraging the use of many integrated low computational cores to perform parallel computations. The main novelty of the MIC architecture, relatively to GPUs, is its compatibility with the Intel x86 architecture. This enables the use of many of the tools commonly available for the parallel programming of x86-based architectures, which may lead to a smaller learning curve. However, programming the Xeon Phi still entails aspects intrinsic to accelerator-based computing, in general, and to the MIC architecture, in particular. In this thesis we advocate the use of algorithmic skeletons for programming the Xeon Phi. Algorithmic skeletons abstract the complexity inherent to parallel programming, hiding details such as resource management, parallel decomposition, inter-execution flow communication, thus removing these concerns from the programmer’s mind. In this context, the goal of the thesis is to lay the foundations for the development of a simple but powerful and efficient skeleton framework for the programming of the Xeon Phi processor. For this purpose we build upon Marrow, an existing framework for the orchestration of OpenCLTM computations in multi-GPU and CPU environments. We extend Marrow to execute both OpenCL and C++ parallel computations on the Xeon Phi. We evaluate the newly developed framework, several well-known benchmarks, like Saxpy and N-Body, will be used to compare, not only its performance to the existing framework when executing on the co-processor, but also to assess the performance on the Xeon Phi versus a multi-GPU environment.

A method to correct the flow distortion of offshore wind data using CFD simulation and experimental wind tunnel tests

The assessment of wind energy resource for the development of deep offshore wind plants requires the use of every possible source of data and, in many cases, includes data gathered at meteorological stations installed at islands, islets or even oil platforms—all structures that interfere with, and change, the flow characteristics. This work aims to contribute to the evaluation of such changes in the flow by developing a correction methodology and applying it to the case of Berlenga island, Portugal. The study is performed using computational fluid dynamic simulations (CFD) validated by wind tunnel tests. In order to simulate the incoming offshore flow with CFD models a wind profile, unknown a priori, was established using observations from two coastal wind stations and a power law wind profile was fitted to the existing data (a=0.165). The results show that the resulting horizontal wind speed at 80 m above sea level is 16% lower than the wind speed at 80 m above the island for the dominant wind direction sector.

Modern optimization in earthwork construction

Earthworks tasks are often regarded in transportation projects as some of the most demanding processes. In fact, sequential tasks such as excavation, transportation, spreading and compaction are strongly based on heavy mechanical equipment and repetitive processes, thus becoming as economically demanding as they are time-consuming. Moreover, actual construction requirements originate higher demands for productivity and safety in earthwork constructions. Given the percentual weight of costs and duration of earthworks in infrastructure construction, the optimal usage of every resource in these tasks is paramount. Considering the characteristics of an earthwork construction, it can be looked at as a production line based on resources (mechanical equipment) and dependency relations between sequential tasks, hence being susceptible to optimization. Up to the present, the steady development of Information Technology areas, such as databases, artificial intelligence and operations research, has resulted in the emergence of several technologies with potential application bearing that purpose in mind. Among these, modern optimization methods (also known as metaheuristics), such as evolutionary computation, have the potential to find high quality optimal solutions with a reasonable use of computational resources. In this context, this work describes an optimization algorithm for earthworks equipment allocation based on a modern optimization approach, which takes advantage of the concept that an earthwork construction can be regarded as a production line.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational in- telligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two il- lustrative Traffic Engineering methods are described, allowing to attain routing con- figurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Implementation of integral viscoelastic constitutive models in OpenFOAM® computational library

This work reports the implementation and verification of a new so lver in OpenFOAM® open source computational library, able to cope with integral viscoelastic models based on the integral upper-convected Maxwell model. The code is verified through the comparison of its predictions with analytical solutions and numerical results obtained with the differential upper-convected Maxwell model

Audit quality: a resource-based perspective

This study considers the Certified Public Accountants (CPA) partners of the audit firms as the core producers of these knowledge-based organisations and investigates the effects of audit firm-level of CPA partners’ experience in audit quality. Audit quality was measured through the audit clients’ earnings quality. The main findings suggested that the audit firm-level of CPA partners’ general experience is positively associated with audit quality. Also, the audit firm-level of CPA partners’ experience acquired with prior audit firms significantly improves audit quality. Concerning the effects of audit firm-level of CPA partners’ experience acquired in the current audit firm in audit quality, results were statistically insignificant. Finally, we found that changes in audit firm-level of CPA partners’ general experience also influence audit quality. We verified that the more positive the change in the audit firm stock of CPA partners’ general experience, the higher is audit quality. We interpret this finding as revealing that the year-to-year changes in audit firm’s stock of CPA partners’ general experience is the mechanism allowing these firms to achieve and maintain the critical mass of this resource and reach higher performance levels. We further showed that our main results were not driven by the engagement partner experience.

Development of computational tools for the integrated analysis of DNA microarray data with applications in cancer research

The MAP-i Doctoral Program of the Universities of Minho, Aveiro and Porto

Omnivory and resource - sharing in nutrient - deficient Rio Negro waters: stabilization of biodiversity?

Amazonian biodiversity is notorious, this is also valid for the fauna of the mineral-deficient waters of the Rio Negro System. Some 25 years of research on the benthic fauna of Central Amazonian streams resulted in species-rich foodwebs with a high degree of omnivory within dense animal communities. To exemplify the taxonomic range of omnivorous consumers, the detailed resource spectra of 18 consumer species, including Protozoa (2 species), Platyhelminthes (1 species), insects (2 species), fish (6 species) and shrimps (Decapoda, 7 species), associated primarily with the benthic habitats of Rio Negro tributaries, are presented. Special features of omnivory are characterized, and the importance of litter-decomposing fungi as essential energy input into the foodwebs is documented. It is shown that general omnivory -diverse omnivore consumers sharing most of the resource types- is a prevalent feature. The relevance of this general omnivory for the maintenance of biodiversity is discussed.