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Optimization of data intensive applications is affected greatly by the nature of the platform, the distributed file system, the co-location of data and programs, and the proximity of resources. Data intensive applications running on a public cloud have been shown to exhibit degraded performance compared to a private cluster. This performance degradation is as a result of the inefficient resource allocation...
Today in the world of cloud and grid computing integration of data from heterogeneous databases is inevitable. Virtual Database Technology (VDB) is one of the effective solutions for integration of data from heterogeneous sources. This will become complex when size of the database is very large. MapReduce is a new framework specifically designed for processing huge datasets on distributed sources...
Much work is underway within the broad next generation technologies community on issues associated with the development of services to foster collaboration via the integration of distributed and heterogeneous data systems and technologies. Various technology-driven paradigms have emerged, including Web Services, Web 2.0, Pervasive, Grids and Cloud Computing. Recently, some new paradigms have emerged,...
The spatial data sharing mechanisms is important in the technical infrastructure of cloud computing or GRID computing, Many researchers have focused on the centralized resource pool and global-local two-layer model but little work considers the availability and practicability of universal discovery description and integration and mechanisms of supporting long transaction management. In this paper,...
This paper presents a model for smart grid data management based on specific characteristics of cloud computing, such as distributed data management for real-time data gathering, parallel processing for real-time information retrieval, and ubiquitous access. The appliance of the cloud computing model meets the requirements of data and computing intensive smart grid applications. We gathered these...
Recent development of eLearning Platforms, presentation technologies and user interaction methods has enabled the development of new, more complex and more efficient teaching materials for Earth Observation domain. However, the process of creating new learning resources is not a trivial task and most of the time technical knowledge is required for such an action. Furthermore, the data that is usually...
The spread of worldwide networks and the technological trend are feeding the progress of network and distributed computing in different directions (grid, cloud, autonomic, ubiquitous, pervasive, volunteer, etc). With regard to information, great amount of data widely (geographically) spread over the network require adequate management, to ensure availability for authorized users only, confidentiality...
MapReduce has emerged as an important data-parallel programming model for data-intensive computing - for Clouds and Grids. However most if not all implementations of MapReduce are coupled to a specific infrastructure. SAGA is a high-level programming interface which provides the ability to create distributed applications in an infrastructure independent way. In this paper, we show how MapReduce has...
Federated storage resources in geographically distributed environments are becoming viable platforms for data-intensive cloud and grid applications. To improve I/O performance in such environments, we propose a novel model-based I/O performance optimization algorithm for data-intensive applications running on a virtual cluster, which determines virtual machine (VM) migration strategies,i.e., when...
Digital preservation deals with the long-term storage, access, and maintenance of digital data objects. In order to prevent a loss of information, digital libraries and archives are increasingly faced with the need to electronically preserve vast amounts of data while having limited computational resources in-house. However, due to the potentially immense data sets and computationally intensive tasks...
In this paper we describe how the grid computing resource brokering approach, classically divided into matchmaking discovery and optimize selection, is applied to five dimensional environmental data distribution. This result is achieved thanks to the integration of a resource broker service we developed from scratch. This service implements the key feature of autonomic mapping of Globus toolkit index...
Cloud computing has become another buzzword after Web 2.0. However, there are dozens of different definitions for cloud computing and there seems to be no consensus on what a cloud is. On the other hand, cloud computing is not a completely new concept; it has intricate connection to the relatively new but thirteen-year established grid computing paradigm, and other relevant technologies such as utility...
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