28,349 research outputs found
A contextual semantic mediator for a distributed cooperative maintenance platform.
International audiencePlatforms expand maintenance systems from centralized systems into e-maintenance platforms integrating various cooperative distributed systems and maintenance applications. This phenomenon allowed an evolution in services offered to maintenance actors by integrating more intelligent applications, providing decision support and facilitating the access to needed data. To manage this evolution, e-maintenance platforms must respond to a great challenge which is ensuring an interoperable communication between its integrated systems. By combining different techniques used in previous works, we propose in this work a semantic mediator system ensuring a high level of interoperability between systems in the maintenance platform
Spectra: Robust Estimation of Distribution Functions in Networks
Distributed aggregation allows the derivation of a given global aggregate
property from many individual local values in nodes of an interconnected
network system. Simple aggregates such as minima/maxima, counts, sums and
averages have been thoroughly studied in the past and are important tools for
distributed algorithms and network coordination. Nonetheless, this kind of
aggregates may not be comprehensive enough to characterize biased data
distributions or when in presence of outliers, making the case for richer
estimates of the values on the network. This work presents Spectra, a
distributed algorithm for the estimation of distribution functions over large
scale networks. The estimate is available at all nodes and the technique
depicts important properties, namely: robust when exposed to high levels of
message loss, fast convergence speed and fine precision in the estimate. It can
also dynamically cope with changes of the sampled local property, not requiring
algorithm restarts, and is highly resilient to node churn. The proposed
approach is experimentally evaluated and contrasted to a competing state of the
art distribution aggregation technique.Comment: Full version of the paper published at 12th IFIP International
Conference on Distributed Applications and Interoperable Systems (DAIS),
Stockholm (Sweden), June 201
Making distributed computing infrastructures interoperable and accessible for e-scientists at the level of computational workflows
As distributed computing infrastructures evolve, and as their take up by user communities is growing, the importance of making different types of infrastructures based on a heterogeneous set of middleware interoperable is becoming crucial. This PhD submission, based on twenty scientific publications, presents a unique solution to the challenge of the seamless interoperation of distributed computing infrastructures at the level of workflows.
The submission investigates workflow level interoperation inside a particular workflow system (intra-workflow interoperation), and also between different workflow solutions (inter-workflow interoperation). In both cases the interoperation of workflow component execution and the feeding of data into these components workflow components are considered.
The invented and developed framework enables the execution of legacy applications and grid jobs and services on multiple grid systems, the feeding of data from heterogeneous file and data storage solutions to these workflow components, and the embedding of non-native workflows to a hosting meta-workflow. Moreover, the solution provides a high level user interface that enables e-scientist end-users to conveniently access the interoperable grid solutions without requiring them to study or understand the technical details of the underlying infrastructure. The candidate has also developed an application porting methodology that enables the systematic porting of applications to interoperable and interconnected grid infrastructures, and facilitates the exploitation of the above technical framework
Interoperable Systems: an introduction
This short chapter introduces interoperable systems and attempts to distinguish the principal
research strands in this area. It is not intended as a review. Significant review material is
integrated with each of the succeeding chapters. It is rather intended to whet the appetite for
what follows and to provide some initial conceptual orientation.
This book concerns the architecture, modelling and management of interoperable computing
systems. Our collective research agenda addresses all aspects of interoperable systems
development, including the business and industry requirements and environments for
distributed information services
A Tale of Two Data-Intensive Paradigms: Applications, Abstractions, and Architectures
Scientific problems that depend on processing large amounts of data require
overcoming challenges in multiple areas: managing large-scale data
distribution, co-placement and scheduling of data with compute resources, and
storing and transferring large volumes of data. We analyze the ecosystems of
the two prominent paradigms for data-intensive applications, hereafter referred
to as the high-performance computing and the Apache-Hadoop paradigm. We propose
a basis, common terminology and functional factors upon which to analyze the
two approaches of both paradigms. We discuss the concept of "Big Data Ogres"
and their facets as means of understanding and characterizing the most common
application workloads found across the two paradigms. We then discuss the
salient features of the two paradigms, and compare and contrast the two
approaches. Specifically, we examine common implementation/approaches of these
paradigms, shed light upon the reasons for their current "architecture" and
discuss some typical workloads that utilize them. In spite of the significant
software distinctions, we believe there is architectural similarity. We discuss
the potential integration of different implementations, across the different
levels and components. Our comparison progresses from a fully qualitative
examination of the two paradigms, to a semi-quantitative methodology. We use a
simple and broadly used Ogre (K-means clustering), characterize its performance
on a range of representative platforms, covering several implementations from
both paradigms. Our experiments provide an insight into the relative strengths
of the two paradigms. We propose that the set of Ogres will serve as a
benchmark to evaluate the two paradigms along different dimensions.Comment: 8 pages, 2 figure
Service-Oriented Architecture for Space Exploration Robotic Rover Systems
Currently, industrial sectors are transforming their business processes into
e-services and component-based architectures to build flexible, robust, and
scalable systems, and reduce integration-related maintenance and development
costs. Robotics is yet another promising and fast-growing industry that deals
with the creation of machines that operate in an autonomous fashion and serve
for various applications including space exploration, weaponry, laboratory
research, and manufacturing. It is in space exploration that the most common
type of robots is the planetary rover which moves across the surface of a
planet and conducts a thorough geological study of the celestial surface. This
type of rover system is still ad-hoc in that it incorporates its software into
its core hardware making the whole system cohesive, tightly-coupled, more
susceptible to shortcomings, less flexible, hard to be scaled and maintained,
and impossible to be adapted to other purposes. This paper proposes a
service-oriented architecture for space exploration robotic rover systems made
out of loosely-coupled and distributed web services. The proposed architecture
consists of three elementary tiers: the client tier that corresponds to the
actual rover; the server tier that corresponds to the web services; and the
middleware tier that corresponds to an Enterprise Service Bus which promotes
interoperability between the interconnected entities. The niche of this
architecture is that rover's software components are decoupled and isolated
from the rover's body and possibly deployed at a distant location. A
service-oriented architecture promotes integrate-ability, scalability,
reusability, maintainability, and interoperability for client-to-server
communication.Comment: LACSC - Lebanese Association for Computational Sciences,
http://www.lacsc.org/; International Journal of Science & Emerging
Technologies (IJSET), Vol. 3, No. 2, February 201
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