31,065 research outputs found
Scaling Virtualized Smartphone Images in the Cloud
Üks selle Bakalaureuse töö eesmärkidest oli Android-x86 nutitelefoni platvormi juurutamine
pilvekeskkonda ja välja selgitamine, kas valitud instance on piisav virtualiseeritud nutitelefoni
platvormi juurutamiseks ning kui palju koormust see talub. Töös kasutati Amazoni instance'i
M1 Small, mis oli piisav, et juurutada Androidi virtualiseeritud platvormi, kuid jäi kesisemaks
kui mobiiltelefon, millel teste läbi viidi. M1 Medium instance'i tüüp oli sobivam ja näitas
paremaid tulemusi võrreldes telefoniga.
Teostati koormusteste selleks vastava tööriistaga Tsung, et näha, kui palju üheaegseid
kasutajaid instance talub. Testi läbiviimiseks paigaldasime Dalviku instance'ile Tomcat
serveri.
Pärast teste ühe eksemplariga, juurutasime külge Elastic Load Balancing ja
automaatse skaleerimise Amazon Auto Scaling tööriista. Esimene neist jaotas koormust
instance'ide
vahel.
Automaatse
skaleerimise
tööriista
kasutasime,
et
rakendada
horisontaalset skaleerimist meie Android-x86 instance'le. Kui CPU tõusis üle 60% kauemaks
kui üks minut, siis tehti eelmisele identne instance ja koormust saadeti edaspidi sinna. Seda
protseduuri vajadusel korrati maksimum kümne instance'ini. Meie teostusel olid tagasilöögid,
sest Elastic Load Balancer aegus 60 sekundi pärast ning me ei saanud kõikide välja
saadetud päringutele vastuseid. Serverisse saadetud faili kirjutamine ja kompileerimine olid
kulukad tegevused ja seega ei lõppenud kõik 60 sekundi jooksul. Me ei saanud koos Load
Balancer'iga läbiviidud testidest piisavalt andmeid, et teha järeldusi, kas virtualiseeritud
nutitelefoni platvorm Android on hästi või halvasti skaleeruv.In this thesis we deployed a smartphone image in an Amazon EC2 instance and ran stress tests on them to know how much users can one instance bear and how scalable it is. We tested how much time would a method run in a physical Android device and in a cloud instance. We deployed CyanogenMod and Dalvik for a single instance. We used Tsung for stress testing. For those tests we also made a Tomcat server on Dalvik instance that would take the incoming file, the file would be compiled with java and its class file would be wrapped into dex, a Dalvik executable file, that is later executed with Dalvik. Three instances made a Tsung cluster that sent load to a Dalvik Virtual Machine instance. For scaling we used Amazon Auto Scaling tool and Elastic Load Balancer that divided incoming load between the instances
A high-flux BEC source for mobile atom interferometers
Quantum sensors based on coherent matter-waves are precise measurement
devices whose ultimate accuracy is achieved with Bose-Einstein condensates
(BEC) in extended free fall. This is ideally realized in microgravity
environments such as drop towers, ballistic rockets and space platforms.
However, the transition from lab-based BEC machines to robust and mobile
sources with comparable performance is a challenging endeavor. Here we report
on the realization of a miniaturized setup, generating a flux of quantum degenerate Rb atoms every 1.6s. Ensembles of atoms can be produced at a 1Hz rate. This is achieved by loading a
cold atomic beam directly into a multi-layer atom chip that is designed for
efficient transfer from laser-cooled to magnetically trapped clouds. The
attained flux of degenerate atoms is on par with current lab-based BEC
experiments while offering significantly higher repetition rates. Additionally,
the flux is approaching those of current interferometers employing Raman-type
velocity selection of laser-cooled atoms. The compact and robust design allows
for mobile operation in a variety of demanding environments and paves the way
for transportable high-precision quantum sensors.Comment: 22 pages, 6 figure
Optical network technologies for future digital cinema
Digital technology has transformed the information flow and support infrastructure for numerous application domains, such as cellular communications. Cinematography, traditionally, a film based medium, has embraced digital technology leading to innovative transformations in its work flow. Digital cinema supports transmission of high resolution content enabled by the latest advancements in optical communications and video compression. In this paper we provide a survey of the optical network technologies for supporting this bandwidth intensive traffic class. We also highlight the significance and benefits of the state of the art in optical technologies that support the digital cinema work flow
Mobile, collaborative augmented reality using cloudlets
The evolution in mobile applications to support advanced interactivity and demanding multimedia features is still ongoing. Novel application concepts (e.g. mobile Augmented Reality (AR)) are however hindered by the inherently limited resources available on mobile platforms (not withstanding the dramatic performance increases of mobile hardware). Offloading resource intensive application components to the cloud, also known as "cyber foraging", has proven to be a valuable solution in a variety of scenarios. However, also for collaborative scenarios, in which data together with its processing are shared between multiple users, this offloading concept is highly promising. In this paper, we investigate the challenges posed by offloading collaborative mobile applications. We present a middleware platform capable of autonomously deploying software components to minimize average CPU load, while guaranteeing smooth collaboration. As a use case, we present and evaluate a collaborative AR application, offering interaction between users, the physical environment as well as with the virtual objects superimposed on this physical environment
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Densely distributed and real-time scour hole monitoring using piezoelectric rod sensors
This study aims to validate a piezoelectric driven-rod scour monitoring system that can sense changes in scour depth along the entire rod at its instrumented location. The proposed sensor is a polymeric slender rod with a thin strip of polyvinylidene fluoride that runs through its midline. Extraction of the fundamental frequency allows the direct calculation of the exposed length (or scour depth) of the slender rod undergoing fluid flow excitation. First, laboratory validation in dry conditions is presented. Second, hydrodynamic testing of the sensor system in a soil-bed flume is discussed. Each rod was installed using a three-dimensional-printed footing designed for ease of installation and stabilization during testing. The sensors were installed in a layout designed to capture symmetric scour conditions around a scaled pier. In order to analyze the system out of steady-state conditions, water velocity was increased in stages during testing to induce different degrees of scour. As ambient water flow excited the portion of the exposed rods, the embedded piezoelectric element outputted a time-varying voltage signal. Different methods were then employed to extract the fundamental frequency of each rod, and the results were compared. Further testing was also performed to characterize the relationship between frequency outputs and flow velocity, which were previously thought to be independent. In general, the proposed driven-rod scour monitoring system successfully captured changing frequencies under varied flow conditions
Mechanotransduction and growth factor signalling to engineer cellular microenvironments
Engineering cellular microenvironments involves biochemical factors, the extracellular matrix (ECM) and the interaction with neighbouring cells. This progress report provides a critical overview of key studies that incorporate growth factor (GF) signalling and mechanotransduction into the design of advanced microenvironments. Materials systems have been developed for surface-bound presentation of GFs, either covalently tethered or sequestered through physico-chemical affinity to the matrix, as an alternative to soluble GFs. Furthermore, some materials contain both GF and integrin binding regions and thereby enable synergistic signalling between the two. Mechanotransduction refers to the ability of the cells to sense physical properties of the ECM and to transduce them into biochemical signals. Various aspects of the physics of the ECM, i.e. stiffness, geometry and ligand spacing, as well as time-dependent properties, such as matrix stiffening, degradability, viscoelasticity, surface mobility as well as spatial patterns and gradients of physical cues are discussed. To conclude, various examples illustrate the potential for cooperative signalling of growth factors and the physical properties of the microenvironment for potential applications in regenerative medicine, cancer research and drug testing
Deep Learning in the Automotive Industry: Applications and Tools
Deep Learning refers to a set of machine learning techniques that utilize
neural networks with many hidden layers for tasks, such as image
classification, speech recognition, language understanding. Deep learning has
been proven to be very effective in these domains and is pervasively used by
many Internet services. In this paper, we describe different automotive uses
cases for deep learning in particular in the domain of computer vision. We
surveys the current state-of-the-art in libraries, tools and infrastructures
(e.\,g.\ GPUs and clouds) for implementing, training and deploying deep neural
networks. We particularly focus on convolutional neural networks and computer
vision use cases, such as the visual inspection process in manufacturing plants
and the analysis of social media data. To train neural networks, curated and
labeled datasets are essential. In particular, both the availability and scope
of such datasets is typically very limited. A main contribution of this paper
is the creation of an automotive dataset, that allows us to learn and
automatically recognize different vehicle properties. We describe an end-to-end
deep learning application utilizing a mobile app for data collection and
process support, and an Amazon-based cloud backend for storage and training.
For training we evaluate the use of cloud and on-premises infrastructures
(including multiple GPUs) in conjunction with different neural network
architectures and frameworks. We assess both the training times as well as the
accuracy of the classifier. Finally, we demonstrate the effectiveness of the
trained classifier in a real world setting during manufacturing process.Comment: 10 page
Computational Simulation and 3D Virtual Reality Engineering Tools for Dynamical Modeling and Imaging of Composite Nanomaterials
An adventure at engineering design and modeling is possible with a Virtual
Reality Environment (VRE) that uses multiple computer-generated media to let a
user experience situations that are temporally and spatially prohibiting. In
this paper, an approach to developing some advanced architecture and modeling
tools is presented to allow multiple frameworks work together while being
shielded from the application program. This architecture is being developed in
a framework of workbench interactive tools for next generation
nanoparticle-reinforced damping/dynamic systems. Through the use of system, an
engineer/programmer can respectively concentrate on tailoring an engineering
design concept of novel system and the application software design while using
existing databases/software outputs.Comment: Submitted on behalf of TIMA Editions
(http://irevues.inist.fr/tima-editions
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