Abstract: Many studies have shown that parallelization decreases efficiency [1], [2]. There are many reasons for these decrements. This paper investigates those which appear in the context of parallel data integration. Integration processes generally cannot be allocated to packages of identical size (i. e. tasks of identical complexity). The reason for this is unknown heterogeneous input data which result in variable task lengths. Process delay is defined by the slowest processing node. It leads to a detrimental effect on the total processing time. With a real world example, this study will show that while process delay does initially increase with the introduction of more nodes it ultimately decreases again after a certain point. The example will make use of the cloud computing platform Hadoop and be run inside Amazon-s EC2 compute cloud. A stochastic model will be set up which can explain this effect.
Abstract: This paper deals with the combination of OSGi and
cloud computing. Both technologies are mainly placed in the field of
distributed computing. Therefore, it is discussed how different
approaches from different institutions work. In addition, the
approaches are compared to each other.
Abstract: This paper presents the methodology from machine
learning approaches for short-term rain forecasting system. Decision
Tree, Artificial Neural Network (ANN), and Support Vector Machine
(SVM) were applied to develop classification and prediction models
for rainfall forecasts. The goals of this presentation are to
demonstrate (1) how feature selection can be used to identify the
relationships between rainfall occurrences and other weather
conditions and (2) what models can be developed and deployed for
predicting the accurate rainfall estimates to support the decisions to
launch the cloud seeding operations in the northeastern part of
Thailand. Datasets collected during 2004-2006 from the
Chalermprakiat Royal Rain Making Research Center at Hua Hin,
Prachuap Khiri khan, the Chalermprakiat Royal Rain Making
Research Center at Pimai, Nakhon Ratchasima and Thai
Meteorological Department (TMD). A total of 179 records with 57
features was merged and matched by unique date. There are three
main parts in this work. Firstly, a decision tree induction algorithm
(C4.5) was used to classify the rain status into either rain or no-rain.
The overall accuracy of classification tree achieves 94.41% with the
five-fold cross validation. The C4.5 algorithm was also used to
classify the rain amount into three classes as no-rain (0-0.1 mm.),
few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall
accuracy of classification tree achieves 62.57%. Secondly, an ANN
was applied to predict the rainfall amount and the root mean square
error (RMSE) were used to measure the training and testing errors of
the ANN. It is found that the ANN yields a lower RMSE at 0.171 for
daily rainfall estimates, when compared to next-day and next-2-day
estimation. Thirdly, the ANN and SVM techniques were also used to
classify the rain amount into three classes as no-rain, few-rain, and
moderate-rain as above. The results achieved in 68.15% and 69.10%
of overall accuracy of same-day prediction for the ANN and SVM
models, respectively. The obtained results illustrated the comparison
of the predictive power of different methods for rainfall estimation.
Abstract: The dramatic effect of information technology on
society is undeniable. In education, it is evident in the use of terms
like active learning, blended learning, electronic learning and mobile
learning (ubiquitous learning). This study explores the perceptions of
54 learners in a higher education institution regarding the use of
mobile devices in a third year module. Using semi-structured
interviews, it was found that mobile devices had a positive impact on
learner motivation, engagement and enjoyment. It also improved the
consistency of learning material, and the convenience and flexibility
(anywhere, anytime) of learning. User-interfacelimitation, bandwidth
and cognitive overload, however, were of concern. The use of cloud
based resources like Youtube and Google Docs, through mobile
devices, positively influenced learner perceptions, making them
prosumers (both consumers and producers) of education content.
Abstract: In recent years there has been renewal of interest in the
relation between Green IT and Cloud Computing. The growing use of
computers in cloud platform has caused marked energy consumption,
putting negative pressure on electricity cost of cloud data center. This
paper proposes an effective mechanism to reduce energy utilization in
cloud computing environments. We present initial work on the
integration of resource and power management that aims at reducing
power consumption. Our mechanism relies on recalling virtualization
services dynamically according to user-s virtualization request and
temporarily shutting down the physical machines after finish in order
to conserve energy. Given the estimated energy consumption, this
proposed effort has the potential to positively impact power
consumption. The results from the experiment concluded that energy
indeed can be saved by powering off the idling physical machines in
cloud platforms.
Abstract: Since Cloud environment has appeared as the most powerful
keyword in the computing industry, the growth in VDI (Virtual Desktop
Infrastructure) became remarkable in domestic market. In recent years, with the trend
that mobile devices such as smartphones and pads spread so rapidly, the strengths of
VDI that allows people to access and perform business on the move along with
companies' office needs expedite more rapid spread of VDI.
In this paper, mobile OTP (One-Time Password) authentication method is proposed
to secure mobile device portability through rapid and secure authentication using
mobile devices such as mobile phones or pads, which does not require additional
purchase or possession of OTP tokens of users. To facilitate diverse and wide use of
Services in the future, service should be continuous and stable, and above all, security
should be considered the most important to meet advanced portability and user
accessibility, the strengths of VDI.
Abstract: Scheduling of diversified service requests in
distributed computing is a critical design issue. Cloud is a type of
parallel and distributed system consisting of a collection of
interconnected and virtual computers. It is not only the clusters and
grid but also it comprises of next generation data centers. The paper
proposes an initial heuristic algorithm to apply modified ant colony
optimization approach for the diversified service allocation and
scheduling mechanism in cloud paradigm. The proposed optimization
method is aimed to minimize the scheduling throughput to service all
the diversified requests according to the different resource allocator
available under cloud computing environment.
Abstract: The main mission of Ezilla is to provide a friendly
interface to access the virtual machine and quickly deploy the high
performance computing environment. Ezilla has been developed by
Pervasive Computing Team at National Center for High-performance
Computing (NCHC). Ezilla integrates the Cloud middleware,
virtualization technology, and Web-based Operating System (WebOS)
to form a virtual computer in distributed computing environment. In
order to upgrade the dataset and speedup, we proposed the sensor
observation system to deal with a huge amount of data in the
Cassandra database. The sensor observation system is based on the
Ezilla to store sensor raw data into distributed database. We adopt the
Ezilla Cloud service to create virtual machines and login into virtual
machine to deploy the sensor observation system. Integrating the
sensor observation system with Ezilla is to quickly deploy experiment
environment and access a huge amount of data with distributed
database that support the replication mechanism to protect the data
security.
Abstract: There are many researches to detect collision between real object and virtual object in 3D space. In general, these techniques are need to huge computing power. So, many research and study are constructed by using cloud computing, network computing, and distribute computing. As a reason of these, this paper proposed a novel fast 3D collision detection algorithm between real and virtual object using 2D intersection area. Proposed algorithm uses 4 multiple cameras and coarse-and-fine method to improve accuracy and speed performance of collision detection. In the coarse step, this system examines the intersection area between real and virtual object silhouettes from all camera views. The result of this step is the index of virtual sensors which has a possibility of collision in 3D space. To decide collision accurately, at the fine step, this system examines the collision detection in 3D space by using the visual hull algorithm. Performance of the algorithm is verified by comparing with existing algorithm. We believe proposed algorithm help many other research, study and application fields such as HCI, augmented reality, intelligent space, and so on.
Abstract: With the development of Internet and databases application techniques, the demand that lots of databases in the Internet are permitted to remote query and access for authorized users becomes common, and the problem that how to protect the copyright of relational databases arises. This paper simply introduces the knowledge of cloud model firstly, includes cloud generators and similar cloud. And then combined with the property of the cloud, a method of protecting relational databases copyright with cloud watermark is proposed according to the idea of digital watermark and the property of relational databases. Meanwhile, the corresponding watermark algorithms such as cloud watermark embedding algorithm and detection algorithm are proposed. Then, some experiments are run and the results are analyzed to validate the correctness and feasibility of the watermark scheme. In the end, the foreground of watermarking relational database and its research direction are prospected.
Abstract: Security is an interesting and significance issue for
popular virtual platforms, such as virtualization cluster and cloud
platforms. Virtualization is the powerful technology for cloud
computing services, there are a lot of benefits by using virtual machine
tools which be called hypervisors, such as it can quickly deploy all
kinds of virtual Operating Systems in single platform, able to control
all virtual system resources effectively, cost down for system platform
deployment, ability of customization, high elasticity and high
reliability. However, some important security problems need to take
care and resolved in virtual platforms that include terrible viruses, evil
programs, illegal operations and intrusion behavior. In this paper, we
present useful Intrusion Detection Mechanism (IDM) software that not
only can auto to analyze all system-s operations with the accounting
journal database, but also is able to monitor the system-s state for
virtual platforms.
Abstract: The present study was designed to demonstrate the seasonal variations in physico-chemical parameters of fish farm at Govt. Nursery Unit, Muzaffargarh, Department of Fisheries Govt. of Punjab, Pakistan for a period of eight months from January to August 2008. Water samples were collected on fifteen days basis and have been analyzed for estimation of Air temperature, Water temperature, Light penetration, pH, Total dissolved oxygen, Clouds, Carbonates, Bicarbonates, Total carbonates, Total dissolved solids, Chlorides, Calcium and Hardness. Seasonal fluctuations were observed in all the physico-chemical parameters of fish farm. The overall physicochemical parameters of fish pond water remained within the tolerable range throughout the study period.
Abstract: Hazardous Material transportation by road is coupled
with inherent risk of accidents causing loss of lives, grievous injuries,
property losses and environmental damages. The most common type
of hazmat road accident happens to be the releases (78%) of
hazardous substances, followed by fires (28%), explosions (14%) and
vapour/ gas clouds (6 %.).
The paper is discussing initially the probable 'Impact Zones'
likely to be caused by one flammable (LPG) and one toxic (ethylene
oxide) chemicals being transported through a sizable segment of a
State Highway connecting three notified Industrial zones in Surat
district in Western India housing 26 MAH industrial units. Three
'hotspots' were identified along the highway segment depending on
the particular chemical traffic and the population distribution within
500 meters on either sides. The thermal radiation and explosion
overpressure have been calculated for LPG / Ethylene Oxide BLEVE
scenarios along with toxic release scenario for ethylene oxide.
Besides, the dispersion calculations for ethylene oxide toxic release
have been made for each 'hotspot' location and the impact zones
have been mapped for the LOC concentrations. Subsequently, the
maximum Initial Isolation and the protective zones were calculated
based on ERPG-3 and ERPG-2 values of ethylene oxide respectively
which are estimated taking the worst case scenario under worst
weather conditions. The data analysis will be helpful to the local
administration in capacity building with respect to rescue /
evacuation and medical preparedness and quantitative inputs to
augment the District Offsite Emergency Plan document.
Abstract: In this paper, cloud resource broker using goalbased
request in medical application is proposed. To handle recent
huge production of digital images and data in medical informatics
application, the cloud resource broker could be used by medical
practitioner for proper process in discovering and selecting correct
information and application. This paper summarizes several
reviewed articles to relate medical informatics application with
current broker technology and presents a research work in applying
goal-based request in cloud resource broker to optimize the use of
resources in cloud environment. The objective of proposing a new
kind of resource broker is to enhance the current resource
scheduling, discovery, and selection procedures. We believed that
it could help to maximize resources allocation in medical
informatics application.
Abstract: Nowadays, HPC, Grid and Cloud systems are evolving
very rapidly. However, the development of infrastructure solutions
related to HPC is lagging behind. While the existing infrastructure is
sufficient for simple cases, many computational problems have more
complex requirements.Such computational experiments use different
resources simultaneously to start a large number of computational
jobs.These resources are heterogeneous. They have different
purposes, architectures, performance and used software.Users need a
convenient tool that allows to describe and to run complex
computational experiments under conditions of HPC environment.
This paper introduces a modularworkflow system called SEGL
which makes it possible to run complex computational experiments
under conditions of a real HPC organization. The system can be used
in a great number of organizations, which provide HPC power.
Significant requirements to this system are high efficiency and
interoperability with the existing HPC infrastructure of the
organization without any changes.
Abstract: The Economic factors are leading to the rise of
infrastructures provides software and computing facilities as a
service, known as cloud services or cloud computing. Cloud services
can provide efficiencies for application providers, both by limiting
up-front capital expenses, and by reducing the cost of ownership over
time. Such services are made available in a data center, using shared
commodity hardware for computation and storage. There is a varied
set of cloud services available today, including application services
(salesforce.com), storage services (Amazon S3), compute services
(Google App Engine, Amazon EC2) and data services (Amazon
SimpleDB, Microsoft SQL Server Data Services, Google-s Data
store). These services represent a variety of reformations of data
management architectures, and more are on the horizon.
Abstract: Cloud computing is the innovative and leading
information technology model for enabling convenient, on-demand
network access to a shared pool of configurable computing resources
that can be rapidly provisioned and released with minimal
management effort. This paper presents our development on enabling
an individual user's desktop in a virtualized environment, which is
stored on a remote virtual machine rather than locally. We present the
initial work on the integration of virtual desktop and application
sharing with virtualization technology. Given the development of
remote desktop virtualization, this proposed effort has the potential to
positively provide an efficient, resilience and elastic environment for
online cloud service. Users no longer need to burden the cost of
software licenses and platform maintenances. Moreover, this
development also helps boost user productivity by promoting a
flexible model that lets users access their desktop environments from
virtually anywhere.
Abstract: Article presents the geometry and structure
reconstruction procedure of the aircraft model for flatter research
(based on the I22-IRYDA aircraft). For reconstruction the Reverse
Engineering techniques and advanced surface modeling CAD tools
are used. Authors discuss all stages of data acquisition process,
computation and analysis of measured data. For acquisition the three
dimensional structured light scanner was used. In the further sections,
details of reconstruction process are present. Geometry
reconstruction procedure transform measured input data (points
cloud) into the three dimensional parametric computer model
(NURBS solid model) which is compatible with CAD systems.
Parallel to the geometry of the aircraft, the internal structure
(structural model) are extracted and modeled. In last chapter the
evaluation of obtained models are discussed.
Abstract: This paper describes an automated event detection and location system for water distribution pipelines which is based upon low-cost sensor technology and signature analysis by an Artificial
Neural Network (ANN). The development of a low cost failure sensor which measures the opacity or cloudiness of the local water
flow has been designed, developed and validated, and an ANN based system is then described which uses time series data produced by
sensors to construct an empirical model for time series prediction and
classification of events. These two components have been installed,
tested and verified in an experimental site in a UK water distribution
system. Verification of the system has been achieved from a series of
simulated burst trials which have provided real data sets. It is concluded that the system has potential in water distribution network
management.
Abstract: Most paddy rice fields in East Asia are small parcels,
and the weather conditions during the growing season are usually
cloudy. FORMOSAT-2 multi-spectral images have an 8-meter
resolution and one-day recurrence, ideal for mapping paddy rice fields
in East Asia. To map rice fields, this study first determined the
transplanting and the most active tillering stages of paddy rice and
then used multi-temporal images to distinguish different growing
characteristics between paddy rice and other ground covers. The
unsupervised ISODATA (iterative self-organizing data analysis
techniques) and supervised maximum likelihood were both used to
discriminate paddy rice fields, with training areas automatically
derived from ten-year cultivation parcels in Taiwan. Besides original
bands in multi-spectral images, we also generated normalized
difference vegetation index and experimented with object-based
pre-classification and post-classification. This paper discusses results
of different image classification methods in an attempt to find a
precise and automatic solution to mapping paddy rice in Taiwan.