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• 151.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Live VM Migration: Principles and Performance2012Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)

Virtualization is a key technology for cloud computing as it allows several operating system instances to run on the same machine, enhances resource manageability and enables flexible definition of billing units. Virtualization works by adding a software layer, a hypervisor, on top of the hardware platform. Virtual Machines, \emph{VMs}, are run on top of the hypervisor, which provisions hardwares resources to the VM guests. In addition to enabling higher utilization of hardware resources, the ability to move VMs from one host to another is an important feature.

Live migration is the concept of migrating a VM while it is running and responding to requests. Since VMs can be re-located while running, live migration allows for better hardware utilization. This is because placement of services can be performed dynamically and not only when the are started. Live migration is also a useful tool for administrative purposes. If a server needs to be taken off-line for maintenance reasons, it can be cleared of services by live migrating these to other hosts.

This thesis investigates the principles behind live migration. The common live migration approaches in use today are evaluated and common objectives are presented as well as challenges that have to be overcome in order to implement an ideal live migration algorithm. The performance of common live migration approaches is also evaluated and it is found that even though live migration is supported by most hypervisors, it has drawbacks which makes the technique hard to use in certain situations. Migrating CPU and/or memory intensive VMs or migrating VMs over low-bandwidth links is a problem regardless of which approach that is used. To tackle this problem, two improvements to live migration are proposed and evaluated, delta compression and dynamic page transfer reordering. Both improvements demonstrate better performance than the standard algorithm when migrating CPU and/or memory intensive VMs and migrating over low bandwidth links. Finally, recommendations are made on which live migration approach to use depending on the scenario and also what improvements to the standard live migration algorithms should be used and when.

• 152.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
The Noble art of Live MigrationManuskript (preprint) (Övrigt vetenskapligt)

Although a mature technique and an important feature of virtualization, live VM migration still suffers from performance and robustness issues, limiting its usefulness. This is particularly true if the migration technique is not appropriately selected for the usage scenario. In this contribution, we define requirements for live migration and discuss some of the challenges that arise in meeting these. We investigate, categorize, and compare current approaches to live migration as well as provide guidelines for which to use in different scenarios. Our investigation is validated by a set of experiments that highlights different characteristics of these approaches. We also propose methods for hybrid live migration and an improved memory page reordering algorithm. Finally we outline the future research landscape in the area.

• 153. Talyansky, Roman
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Towards Optimized Self-Management of Distributed Object Storage Systems2015Rapport (Övrigt vetenskapligt)

Cloud storage is increasingly adopted by users due to simplified storage systems compared to on-premise storage. These systems are mostly presented as Object Storage Systems (OSSs), hiding issues, such as redundancy, from users. As new industries are considering adopting clouds for storage, OSSs have to evolve to support new needs. Among the most challenging is assuring guaranteed performance.

In this paper, we present Controllable Trade-offs (CTO), an OSS-agnostic solution to add performance guarantees. CTO presents itself as a thin layer that mediates requests between the user and the OSS. For generic support, performance is controlled by tuning the rejection probability, and implemented as a user-side queue. Results show that CTO may reduce penalties 3.23 times on average and up to 68 times when the load is high.

• 154.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Energy-efficient cloud computing: autonomic resource provisioning for datacenters2018Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)

Energy efficiency has become an increasingly important concern in data centers because of issues associated with energy consumption, such as capital costs, operating expenses, and environmental impact. While energy loss due to suboptimal use of facilities and non-IT equipment has largely been reduced through the use of best-practice technologies, addressing energy wastage in IT equipment still requires the design and implementation of energy-aware resource management systems. This thesis focuses on the development of resource allocation methods to improve energy efficiency in data centers. The thesis employs three approaches to improve efficiency for optimized power and performance: scaling virtual machine (VM) and server processing capabilities to reduce energy consumption; improving resource usage through workload consolidation; and exploiting resource heterogeneity.

To achieve these goals, the first part of the thesis proposes models, algorithms, and techniques that reduce energy usage through the use of VM scaling, VM sizing for CPU and memory, CPU frequency adaptation, as well as hardware power capping for server-level resource allocation. The proposed online performance and power models capture system behavior while adapting to changes in the underlying infrastructure. Based on these models, the thesis proposes controllers that dynamically determine power-efficient resource allocations while minimizing performance penalty.

These methods are then extended to support resource overbooking and workload consolidation to improve resource utilization and energy efficiency across the cluster or data center. In order to cater for different performance requirements among collocated applications, such as latency-sensitive services and batch jobs, the controllers apply service differentiation among prioritized VMs and performance isolation techniques, including CPU pinning, quota enforcement, and online resource tuning.

This thesis also considers resource heterogeneity and proposes heterogeneousaware scheduling techniques to improve energy efficiency by integrating hardware accelerators (in this case FPGAs) and exploiting differences in energy footprint of different servers. In addition, the thesis provides a comprehensive study of the overheads associated with a number of virtualization platforms in order to understand the trade-offs provided by the latest technological advances and to make the best resource allocation decisions accordingly. The proposed methods in this thesis are evaluated by implementing prototypes on real testbeds and conducting experiments using real workload data taken from production systems and synthetic workload data that we generated. Our evaluation results demonstrate that the proposed approaches provide improved energy management of resources in virtualized data centers.

• 155.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Virtualization Techniques Compared: Performance, Resource, and Power Usage Overheads in Clouds2018Manuskript (preprint) (Övrigt vetenskapligt)

Virtualization solutions based on hypervisors or containers are enabling technologies

for scalable, flexible, and cost-effective resource sharing. As the fundamental

limitations of each technology are yet to be understood, they need to be regularly

reevaluated to better understand the trade-off provided by latest technological advances.

This paper presents an in-depth quantitative analysis of virtualization

overheads in these two groups of systems and their gaps relative to native environments

based on a diverse set of workloads that stress CPU, memory, storage,

and networking resources. KVM and XEN are used to represent hypervisor-based

virtualization, and LXC and Docker for container-based platforms. The systems

were evaluated with respect to several cloud resource management dimensions including

performance, isolation, resource usage, energy efficiency, start-up time,

and density. Our study is useful both to practitioners to understand the current

state of the technology in order to make the right decision in the selection, operation

and/or design of platforms and to scholars to illustrate how these technologies

evolved over time.

• 156.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Red Hat, Madrid, Spain. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
OptiBook: Optimal Resource Booking for Energy-efficient Datacenters2017Ingår i: 2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS), IEEE Communications Society, 2017Konferensbidrag (Refereegranskat)

A lack of energy proportionality, low resource utilization, and interference in virtualized infrastructure make the cloud a challenging target environment for improving energy efficiency. In this paper we present OptiBook, a system that improves energy proportionality and/or resource utilization to optimize performance and energy efficiency. OptiBook shares servers between latency-sensitive services and batch jobs, over- books the system in a controllable manner, uses vertical (CPU and DVFS) scaling for prioritized virtual machines, and applies performance isolation techniques such as CPU pinning and quota enforcement as well as online resource tuning to effectively improve energy efficiency. Our evaluations show that on average, OptiBook improves performance per watt by 20% and reduces energy consumption by 9% while minimizing SLO violations.

• 157.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
PerfGreen: Performance and Energy Aware Resource Provisioning for Heterogeneous Clouds2018Ingår i: 2018 IEEE International Conference on Autonomic Computing (ICAC), 2018, s. 81-90Konferensbidrag (Refereegranskat)

Improving energy efficiency in a cloud environment is challenging because of poor energy proportionality, low resource utilization, interference as well as workload, application, and hardware dynamism. In this paper we present PerfGreen, a dynamic auto-tuning resource management system for improving energy efficiency with minimal performance impact in heterogeneous clouds. PerfGreen achieves this through a combination of admission control, scheduling, and online resource allocation methods with performance isolation and application priority techniques. Scheduling in PerfGreen is energy aware and power management capabilities such as CPU frequency adaptation and hard CPU power limiting are exploited. CPU scaling is combined with performance isolation techniques, including CPU pinning and quota enforcement, for prioritized virtual machines to improve energy efficiency. An evaluation based on our prototype implementation shows that PerfGreen with its energy-aware scheduler and resource allocator on average reduces energy usage by 53%, improves performance per watt by 64%, and server density by 25% while keeping performance deviations to a minimum.

• 158.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
University of Castilla-La Mancha. University of Castilla-La Mancha.
Opportunistic Energy-Aware Rescheduling in Desktop Grid Environments2013Ingår i: 2013 International Conference on High Performance Computing & Simulation (HPCS2013), 2013, s. 178-185Konferensbidrag (Refereegranskat)

Nowadays either maximizing energy efficiency andimproving resource utilization is a challenge among the differentexisting distributed systems, specially in large scale distributedenvironments such as Grids or Clouds. With this objective, wepropose a rescheduling technique that tries to improve resourceusage, whilst at the same time tries to minimize the energy neededfor the executions of the already accepted jobs by using first/morethe resources that are more energy efficient and without reducingthe QoS provided. The information obtained from a devicecapable of measuring the energy that each desktop resourceneeds is used by the algorithm at the resource selection process,resulting in a noticeable reduction in the energy used as it hasbeen demonstrated in a real desktop Grid environment.

• 159.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Cloudy with a Chance of Load Spikes: Admission Control with Fuzzy Risk Assessments2013Ingår i: 6th IEEE International Conference on Utility and Cloud Computing, 2013, s. 155-162Konferensbidrag (Refereegranskat)

Elasticity is key for the cloud paradigm, wherethe pay-per use nature provides great flexibility for end-users.However, elasticity complicates long-term capacity planning forcloud providers as the exact amount of resources requiredover time becomes uncertain. Admission control techniques arethus needed to handle the trade-off between resource utilizationand potential overload. We define a set of admission controlalgorithms that combine risk assessment methods with a fuzzyaggregation framework. An experimental evaluation using amixture of bursty and steady applications demonstrate that ouralgorithms can increase resource utilization by a factor of twowhile limiting overload problems to a few percent.

• 160.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Improving Cloud Infrastructure Utilization through Overbooking2013Ingår i: Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference, 2013Konferensbidrag (Refereegranskat)

Despite the potential given by the combination of multitenancyand virtualization, resource utilization in today’sdata centers is still low. We identify three key characteristicsof cloud services and infrastructure as-a-service managementpractices: burstiness in service workloads, fluctuationsin virtual machine resource usage over time, and virtual machinesbeing limited to pre-defined sizes only. Based on thesecharacteristics, we propose scheduling and admission controlalgorithms that incorporate resource overbooking to improveutilization. A combination of modeling, monitoring, andprediction techniques is used to avoid overpassing the totalinfrastructure capacity. A performance evaluation using amixture of workload traces demonstrates the potential forsignificant improvements in resource utilization while stillavoiding overpassing the total capacity.

• 161.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik. Nanjing University of Posts and Telecommunications, Nanjing, China. Media technology and interaction design, Royal Institute of Technology (KTH), Sweden; Nanjing University of Posts and Telecommunications, Nanjing, China.
Vibrotactile TV for immersive experience2014Ingår i: Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific, 2014Konferensbidrag (Refereegranskat)

Audio and video are two powerful media forms to shorten the distance between audience/viewer and actors or players in the TV and films. The recent research shows that today people are using more and more multimedia contents on mobile devices, such as tablets and smartphones. Therefore, an important question emerges - how can we render high-quality, personal immersive experiences to consumers on these systems? To give audience an immersive engagement that differs from watching a play', we have designed a study to render complete immersive media which include the emotional information' based on augmented vibrotactile-coding on the back of the user along with audio-video signal. The reported emotional responses to videos viewed with and without haptic enhancement, show that participants exhibited an increased emotional response to media with haptic enhancement. Overall, these studies suggest that the effectiveness of our approach and using a multisensory approach increase immersion and user satisfaction.

• 162.
University of Castilla-La Mancha, Spain.
University of Castilla-La Mancha, Spain. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
A Cloud Scheduler Assisted by a Fuzzy Affinity-Aware Engine2015Ingår i: 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) / [ed] Adnan Yazici, Nikhil R.Pal, Uzay Kaymak, Trevor Martin, Hisao Ishibuchi, Chin-Teng Lin, Joao M. C. Sousa and Bulent Tutmez, IEEE Computer Society, 2015, s. 1-8Konferensbidrag (Refereegranskat)

Recent advances on declarative paradigms have introduced expressive resources based on fuzzy logic. These are very useful for increasing the flexibility of the so-called fuzzy logicprogramming paradigm, resulting in highly expressive languages where the treatment of uncertainty and approximate reasoning is performed in a natural, efficient way. Therefore, making it extremely useful for decision-making scenarios dealing with highlevels of uncertainty. One such scenario is capacity management in cloud environments, where the amount of resources that users will request is unknown and can vary significantly overtime, usually leading to poor resource utilization. Overbooking techniques allow cloud providers to increase utilization, but the risk of degrading application performance due to exhausting resources also increases as applications need to share the servers. Fuzzy logic programming can be used to decide how cloud applications should be co-located with each other, minimizing the interference among them. Therefore, we propose a newscheduling mechanism based on fuzzy logic cores clustering, and applications–cores affinity estimation to decide which applications to co-locate reducing the interference. An experimental evaluation confirms that our affinity-aware fuzzy logic assisted scheduler minimizes the interference among applications, enabling a moresafe overbooking and consequently higher cloud provider revenue.

• 163.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik.
Röstigenkänning med Movidius Neural Compute Stick2018Självständigt arbete på grundnivå (yrkesexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)

Företaget Omicron Ceti AB köpte en Intel Movidius Neural Compute Stick (NCS), som är en usb-enhet där neurala nätverk kan laddas in för att processa data. Min uppgift blev att studera hur NCS används och göra en guide med exempel. Med TensorFlow och hjälpbiblioteket TFLearn gjordes först ett testnätverk för att prova hela kedjan från träning till användning med NCS. Sedan tränades ett nätverk att kunna klassificera 14 olika ord. En mängd olika utformningar på nätverket testades, men till slut hittades ett exempel som blev en bra utgångspunkt och som efter lite justering gav en träffsäkerhet på 86% med testdatat. Vid inläsning i mikrofon så blev resultatet lite sämre, med 67% träffsäkerhet. Att processa data med NCS tog längre tid än med TFLearn men använde betydligt mindre CPU-kraft. I mindre system såsom en Raspberry Pi går det däremot inte ens att använda TensorFlow/TFLearn, så huruvida det är värt att använda NCS eller inte beror på det specifika användningsscenariot.

• 164.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för tillämpad fysik och elektronik. University of Castilla-La Mancha.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. University of Castilla-La Mancha. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
A fuzzy approach to cloud admission control for safe overbooking2013Ingår i: 10th International Workshop on Fuzzy Logic and Applications (WILF), 2013, s. 212-225Konferensbidrag (Refereegranskat)

Cloud computing enables elasticity - rapid provisioning and deprovisioning of computational resources.Elasticity allows cloud users to quickly adapt resource allocation to meet changes in their workloads.For cloud providers, elasticity complicates capacity management as the amount ofresources that can be requested by users is unknown and can vary significantly over time. Overbooking techniques allowproviders to increase utilization of their data centers. For safe overbooking, cloud providersneed admission control mechanisms to handle the tradeoff between increasedutilization (and revenue), and risk of exhausting resources, potentially resulting in penalty fees and/or lost customers.We propose a flexible approach (implemented with fuzzy logic programming) to admission control and the associated risk estimation.Our measures exploit different fuzzy logic operators in order to model optimistic, realistic, and pessimistic behaviour under uncertainty.An experimental evaluation confirm that our fuzzy admission control approach can significantly increaseresource utilization while minimizing the risk of exceeding the total available capacity.

• 165.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Developing digital support for learning and diagnostic reasoning in clinical practice2018Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)

The two main purposes of clinical decision-support systems (CDSSs) are to provide healthcare professionals decision-making support based on evidence-based medical knowledge, and a continuing medical education. This thesis focuses on both purposes and shows how fundamental theory in the field of artificial intelligence can be developed, adapted and implemented in a CDSS for supporting learning and diagnostic reasoning in clinical practice. The main research problems addressed in this thesis are how to represent and manage uncertain, incomplete, inconsistent and distributed knowledge in automated reasoning and decision-making with the clinicians in the loop, how to facilitate the knowledge engineering and maintenance process, and how to detect and support learning and skill development in CDSS users.

Research contributions include theories, methods, and algorithms based on possibilistic logic and formal argumentation for representing and managing uncertain, incomplete, inconsistent and distributed medical knowledge, and for supporting reasoning and decision-making when using a CDSS. The clinician is provided potentially conflicting arguments and their strength based on different diagnostic criteria and the available patient information in order to make an informed decision. The theoretical results were implemented in the Dementia Diagnosis and Management Support System - Web version (DMSS-W), in a multi-agent hypothesis-driven inquiry dialogue system, and in an inference engine serving as a module of ACKTUS.

CDSS maintenance is challenging since new knowledge about diseases and treatments are continuously developed. Typically, knowledge and software engineers are needed to bridge medical experts and CDSSs, leading to time-consuming system development. ACKTUS (Activity-Centered Knowledge and Interaction Tailored to Users) was, as part of this research, further developed as a generic web-based platform for knowledge management and end-user development of CDSSs. It includes the inference engine and a content management system that the medical expert can use to manage knowledge, design and evaluate CDSSs. A graphical user interface generator synchronizes the interface to the ontology serving as the knowledge base. ACKTUS was used for developing DMSS-W, and facilitated the system development and maintenance.

To offer person-tailored support for the clinician's learning, reasoning and decision-making, the CDSS design was based on theories of how novices and experts reason and make decisions. Pilot case studies involving physicians with different levels of expertise who applied DMSS-W in patient cases were conducted in clinical practice to explore methods for detecting skill levels and whether learning is taking place. The results indicated that the skill levels can be detected using the method. The novice was seen to develop reasoning strategies similar to an expert's, indicating that learning was taking place. In future work, tailored educational support will be developed, and evaluated using the methods.

• 166.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
On the use of thin structures to control the far-field properties of an acoustic device2016Rapport (Övrigt vetenskapligt)

This work presents a sensitivity analysis for topology optimization of thin structures inside an acoustic horn in order to improve its far-field directivity properties. The objective function gradient is computed using an adjoint-based method, a well-known approach in the design optimization community due to its ability to compute the design sensitivities when there is a large number of design variables. The accuracy of the computed gradient is verified numerically against a first order finite difference approximation. The report also covers the matrix representations of the far-field pattern evaluation and the variational problem with an interface condition to model the thin structures.

• 167.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Layout optimization of thin sound-hard material to improve the far-field directivity properties of an acoustic horn2017Ingår i: Structural and multidisciplinary optimization (Print), ISSN 1615-147X, E-ISSN 1615-1488, Vol. 55, nr 3, s. 795-808Artikel i tidskrift (Refereegranskat)

To improve the far-field directivity properties of a given mid-range acoustic horn, previously designed by shape optimization to exhibit almost ideal transmission properties in the frequency range 1.6–9.05 kHz, we apply layout optimization of thin sound-hard material in the interior of the horn. The purpose of the optimization is to place scattering material to prevent the sound intensity to increasingly be concentrated, with increasing frequency, along the horn axis. Absence or presence of thin sound-hard material is modeled by an equivalent surface transmission impedance, and the optimization algorithm determines the distribution of air or sound-hard material along a “ground structure” in the form of a grid inside the horn. The surface impedance is numerically handled using a newly developed finite-element formulation that allows exact enforcement of a vanishing impedance, corresponding to air, which would not be possible using a standard formulation. Horns provided with the optimized scatterers show a much improved angular coverage, compared to the initial configuration, with beam widths that exceed 60 ∘ uniformly over the operational frequency range, without destroying the good transmission properties of the initial horn.

• 168.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Service development abstraction: A design methodology and development toolset for abstractive and flexible service-based software2011Ingår i: Cloud Computing and Service Science / [ed] Ivanov, van Sinderen, and Shishkov, Springer, 2011Kapitel i bok, del av antologi (Refereegranskat)
1234 151 - 168 av 168
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