289 research outputs found
Evaluating the performance and intrusiveness of virtual machines for desktop grid computing
Comunicação apresentada no 3rd Workshop on Desktop Grids and Volunteer Computing Systems, Rome, 2009.We experimentally evaluate the performance overhead
of the virtual environments VMware Player, QEMU, VirtualPC
and VirtualBox on a dual-core machine. Firstly, we
assess the performance of a Linux guest OS running on a
virtual machine by separately benchmarking the CPU, file
I/O and the network bandwidth. These values are compared
to the performance achieved when applications are run on a
Linux OS directly over the physical machine. Secondly, we
measure the impact that a virtual machine running a volunteer
@home project worker causes on a host OS. Results
show that performance attainable on virtual machines depends
simultaneously on the virtual machine software and
on the application type, with CPU-bound applications much
less impacted than IO-bound ones. Additionally, the performance
impact on the host OS caused by a virtual machine using all the virtual CPU, ranges from 10% to 35%, depending on the virtual environment
A semi-automatic parallelization tool for Java based on fork-join synchronization patterns
Because of the increasing availability of multi-core machines, clusters, Grids, and combinations of these environments, there is now plenty of computational power available for executing compute intensive applications. However, because of the overwhelming and rapid advances in distributed and parallel hardware and environments, today?s programmers are not fully prepared to exploit distribution and parallelism. In this sense, the Java language has helped in handling the heterogeneity of such environments, but there is a lack of facilities and tools to easily distributing and parallelizing applications. One solution to mitigate this problem and make some progress towards producing general tools seems to be the synthesis of semi-automatic parallelism and Parallelism as a Concern (PaaC), which allows parallelizing applications along with as little modifications on sequential codes as possible. In this paper, we discuss a new approach that aims at overcoming the drawbacks of current Java-based parallel and distributed development tools, which precisely exploit these new conceptsFil: Hirsch, Matias. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Tandil. Instituto Superior de Ingenieria del Software; Argentina;Fil: Zunino, Alejandro. Consejo Nacional de Invest.cientif.y Tecnicas. Ctro Cientifico Tecnologico Conicet - Tandil. Instituto Superior de Ingenieria del Software;Fil: Mateos Diaz, Cristian Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Tandil. Instituto Superior de Ingenieria del Software
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MapReduce based RDF assisted distributed SVM for high throughput spam filtering
This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel UniversityElectronic mail has become cast and embedded in our everyday lives. Billions of legitimate emails are sent on a daily basis. The widely established underlying infrastructure, its widespread availability as well as its ease of use have all acted as catalysts to such pervasive proliferation. Unfortunately, the same can be alleged about unsolicited bulk email, or rather spam. Various methods, as well as enabling architectures are available to try to mitigate spam permeation. In this respect, this dissertation compliments existing survey work in this area by contributing an extensive literature review of traditional and emerging spam filtering approaches. Techniques, approaches and architectures employed for spam filtering are appraised, critically assessing respective strengths and weaknesses.
Velocity, volume and variety are key characteristics of the spam challenge. MapReduce (M/R) has become increasingly popular as an Internet scale, data intensive processing platform. In the context of machine learning based spam filter training, support vector machine (SVM) based techniques have been proven effective. SVM training is however a computationally intensive process. In this dissertation, a M/R based distributed SVM algorithm for scalable spam filter training, designated MRSMO, is presented. By distributing and processing subsets of the training data across multiple participating computing nodes, the distributed SVM reduces spam filter training time significantly. To mitigate the accuracy degradation introduced by the adopted approach, a Resource Description Framework (RDF) based feedback loop is evaluated. Experimental results demonstrate that this improves the accuracy levels of the distributed SVM beyond the original sequential counterpart.
Effectively exploiting large scale, ‘Cloud’ based, heterogeneous processing capabilities for M/R in what can be considered a non-deterministic environment requires the consideration of a number of perspectives. In this work, gSched, a Hadoop M/R based, heterogeneous aware task to node matching and allocation scheme is designed. Using MRSMO as a baseline, experimental evaluation indicates that gSched improves on the performance of the out-of-the box Hadoop counterpart in a typical Cloud based infrastructure.
The focal contribution to knowledge is a scalable, heterogeneous infrastructure and machine learning based spam filtering scheme, able to capitalize on collaborative accuracy improvements through RDF based, end user feedback. MapReduce based RDF Assisted Distributed SVM for High Throughput Spam Filterin
A semi-automatic parallelization tool for Java based on fork-join synchronization patterns
Because of the increasing availability of multi-core machines, clusters, Grids, and combinations of these environments, there is now plenty of computational power available for executing compute intensive applications. However, because of the overwhelming and rapid advances in distributed and parallel hardware and environments, today’s programmers are not fully prepared to exploit distribution and parallelism. In this sense, the Java language has helped in handling the heterogeneity of such environments, but there is a lack of facilities and tools to easily distributing and parallelizing applications. One solution to mitigate this problem and make some progress towards producing general tools seems to be the synthesis of semi-automatic parallelism and Parallelism as a Concern (PaaC), which allows parallelizing applications along with as little modifications on sequential codes as possible. In this paper, we discuss a new approach that aims at overcoming the drawbacks of current Java-based parallel and distributed development tools, which precisely exploit these new concepts.Sociedad Argentina de Informática e Investigación Operativ
Dimensionerings- en werkverdelingsalgoritmen voor lambda grids
Grids bestaan uit een verzameling reken- en opslagelementen die geografisch verspreid kunnen zijn, maar waarvan men de gezamenlijke capaciteit wenst te benutten. Daartoe dienen deze elementen verbonden te worden met een netwerk. Vermits veel wetenschappelijke applicaties gebruik maken van een Grid, en deze applicaties doorgaans grote hoeveelheden data verwerken, is het noodzakelijk om een netwerk te voorzien dat dergelijke grote datastromen op betrouwbare wijze kan transporteren. Optische transportnetwerken lenen zich hier uitstekend toe. Grids die gebruik maken van dergelijk netwerk noemt men lambda Grids. Deze thesis beschrijft een kader waarin het ontwerp en dimensionering van optische netwerken voor lambda Grids kunnen beschreven worden. Ook wordt besproken hoe werklast kan verdeeld worden op een Grid eens die gedimensioneerd is. Een groot deel van de resultaten werd bekomen door simulatie, waarbij gebruik gemaakt wordt van een eigen Grid simulatiepakket dat precies focust op netwerk- en Gridelementen. Het ontwerp van deze simulator, en de daarbijhorende implementatiekeuzes worden dan ook uitvoerig toegelicht in dit werk
Augmenting User Interfaces with Haptic Feedback
Computer assistive technologies have developed considerably over the past decades.
Advances in computer software and hardware have provided motion-impaired operators
with much greater access to computer interfaces. For people with motion
impairments, the main di�culty in the communication process is the input of data
into the system. For example, the use of a mouse or a keyboard demands a high level
of dexterity and accuracy. Traditional input devices are designed for able-bodied
users and often do not meet the needs of someone with disabilities. As the key feature
of most graphical user interfaces (GUIs) is to point-and-click with a cursor this
can make a computer inaccessible for many people.
Human-computer interaction (HCI) is an important area of research that aims
to improve communication between humans and machines. Previous studies have
identi�ed haptics as a useful method for improving computer access. However, traditional
haptic techniques su�er from a number of shortcomings that have hindered
their inclusion with real world software. The focus of this thesis is to develop haptic
rendering algorithms that will permit motion-impaired operators to use haptic assistance
with existing graphical user interfaces. The main goal is to improve interaction
by reducing error rates and improving targeting times. A number of novel haptic
assistive techniques are presented that utilise the three degrees-of-freedom (3DOF)
capabilities of modern haptic devices to produce assistance that is designed speci�-
cally for motion-impaired computer users. To evaluate the e�ectiveness of the new
techniques a series of point-and-click experiments were undertaken in parallel with
cursor analysis to compare the levels of performance. The task required the operator
to produce a prede�ned sentence on the densely populated Windows on-screen keyboard
(OSK). The results of the study prove that higher performance levels can be
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achieved using techniques that are less constricting than traditional assistance
Ad hoc cloud computing
Commercial and private cloud providers offer virtualized resources via a set of co-located
and dedicated hosts that are exclusively reserved for the purpose of offering
a cloud service. While both cloud models appeal to the mass market, there are many
cases where outsourcing to a remote platform or procuring an in-house infrastructure
may not be ideal or even possible.
To offer an attractive alternative, we introduce and develop an ad hoc cloud computing
platform to transform spare resource capacity from an infrastructure owner’s
locally available, but non-exclusive and unreliable infrastructure, into an overlay cloud
platform. The foundation of the ad hoc cloud relies on transferring and instantiating
lightweight virtual machines on-demand upon near-optimal hosts while virtual machine
checkpoints are distributed in a P2P fashion to other members of the ad hoc
cloud. Virtual machines found to be non-operational are restored elsewhere ensuring
the continuity of cloud jobs.
In this thesis we investigate the feasibility, reliability and performance of ad hoc
cloud computing infrastructures. We firstly show that the combination of both volunteer
computing and virtualization is the backbone of the ad hoc cloud. We outline the
process of virtualizing the volunteer system BOINC to create V-BOINC. V-BOINC
distributes virtual machines to volunteer hosts allowing volunteer applications to be
executed in the sandbox environment to solve many of the downfalls of BOINC; this
however also provides the basis for an ad hoc cloud computing platform to be developed.
We detail the challenges of transforming V-BOINC into an ad hoc cloud and outline
the transformational process and integrated extensions. These include a BOINC job
submission system, cloud job and virtual machine restoration schedulers and a periodic
P2P checkpoint distribution component. Furthermore, as current monitoring tools are
unable to cope with the dynamic nature of ad hoc clouds, a dynamic infrastructure
monitoring and management tool called the Cloudlet Control Monitoring System is
developed and presented.
We evaluate each of our individual contributions as well as the reliability, performance
and overheads associated with an ad hoc cloud deployed on a realistically
simulated unreliable infrastructure. We conclude that the ad hoc cloud is not only a
feasible concept but also a viable computational alternative that offers high levels of
reliability and can at least offer reasonable performance, which at times may exceed
the performance of a commercial cloud infrastructure
Proceedings of the Second International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2015) Krakow, Poland
Proceedings of: Second International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2015). Krakow (Poland), September 10-11, 2015
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