Abstract: In recent years, real-time spatial applications, like
location-aware services and traffic monitoring, have become more
and more important. Such applications result dynamic environments
where data as well as queries are continuously moving. As a result,
there is a tremendous amount of real-time spatial data generated
every day. The growth of the data volume seems to outspeed the
advance of our computing infrastructure. For instance, in real-time
spatial Big Data, users expect to receive the results of each query
within a short time period without holding in account the load
of the system. But with a huge amount of real-time spatial data
generated, the system performance degrades rapidly especially in
overload situations. To solve this problem, we propose the use of
data partitioning as an optimization technique. Traditional horizontal
and vertical partitioning can increase the performance of the system
and simplify data management. But they remain insufficient for
real-time spatial Big data; they can’t deal with real-time and
stream queries efficiently. Thus, in this paper, we propose a novel
data partitioning approach for real-time spatial Big data named
VPA-RTSBD (Vertical Partitioning Approach for Real-Time Spatial
Big data). This contribution is an implementation of the Matching
algorithm for traditional vertical partitioning. We find, firstly, the
optimal attribute sequence by the use of Matching algorithm. Then,
we propose a new cost model used for database partitioning, for
keeping the data amount of each partition more balanced limit and
for providing a parallel execution guarantees for the most frequent
queries. VPA-RTSBD aims to obtain a real-time partitioning scheme
and deals with stream data. It improves the performance of query
execution by maximizing the degree of parallel execution. This affects
QoS (Quality Of Service) improvement in real-time spatial Big Data
especially with a huge volume of stream data. The performance of
our contribution is evaluated via simulation experiments. The results
show that the proposed algorithm is both efficient and scalable, and
that it outperforms comparable algorithms.
Abstract: Automated Optical Inspection (AOI) Systems are commonly used on Printed Circuit Boards (PCB) manufacturing. The use of this technology has been proven as highly efficient for process improvements and quality achievements. The correct extraction of the component for posterior analysis is a critical step of the AOI process. Nowadays, the Pattern Matching Algorithm is commonly used, although this algorithm requires extensive calculations and is time consuming. This paper will present an improved algorithm for the component localization process, with the capability of implementation in a parallel execution system.
Abstract: Cryptographic algorithms play a crucial role in the
information society by providing protection from unauthorized
access to sensitive data. It is clear that information technology will
become increasingly pervasive, Hence we can expect the emergence
of ubiquitous or pervasive computing, ambient intelligence. These
new environments and applications will present new security
challenges, and there is no doubt that cryptographic algorithms and
protocols will form a part of the solution. The efficiency of a public
key cryptosystem is mainly measured in computational overheads,
key size and bandwidth. In particular the RSA algorithm is used in
many applications for providing the security. Although the security
of RSA is beyond doubt, the evolution in computing power has
caused a growth in the necessary key length. The fact that most chips
on smart cards can-t process key extending 1024 bit shows that there
is need for alternative. NTRU is such an alternative and it is a
collection of mathematical algorithm based on manipulating lists of
very small integers and polynomials. This allows NTRU to high
speeds with the use of minimal computing power. NTRU (Nth degree
Truncated Polynomial Ring Unit) is the first secure public key
cryptosystem not based on factorization or discrete logarithm
problem. This means that given sufficient computational resources
and time, an adversary, should not be able to break the key. The
multi-party communication and requirement of optimal resource
utilization necessitated the need for the present day demand of
applications that need security enforcement technique .and can be
enhanced with high-end computing. This has promoted us to develop
high-performance NTRU schemes using approaches such as the use
of high-end computing hardware. Peer-to-peer (P2P) or enterprise
grids are proven as one of the approaches for developing high-end
computing systems. By utilizing them one can improve the
performance of NTRU through parallel execution. In this paper we
propose and develop an application for NTRU using enterprise grid
middleware called Alchemi. An analysis and comparison of its
performance for various text files is presented.