High Throughput Protein Similarity Searches in the LIBI Grid Problem Solving Environment

Bioinformatics applications are naturally distributed, due to distribution of involved data sets, experimental data and biological databases. They require high computing power, owing to the large size of data sets and the complexity of basic computations, may access heterogeneous data, where heterogeneity is in data format, access policy, distribution, etc., and require a secure infrastructure, because they could access private data owned by different organizations. The Problem Solving Environment (PSE) is an approach and a technology that can fulfil such bioinformatics requirements. The PSE can be used for the definition and composition of complex applications, hiding programming and configuration details to the user that can concentrate only on the specific problem. Moreover, Grids can be used for building geographically distributed collaborative problem solving environments and Grid aware PSEs can search and use dispersed high performance computing, networking, and data resources. In this work, the PSE solution has been chosen as the integration platform of bioinformatics tools and data sources. In particular an experiment of multiple sequence alignment on large scale, supported by the LIBIPSE, is presented

Efficient replication of large volumes of data and maintaining data consistency by using P2P techniques in Desktop Grid

Desktop Grid is increasing in popularity because of relatively very low cost and good performance in institutions. Data-intensive applications require data management in scientific experiments conducted by researchers and scientists in Desktop Grid-based Distributed Computing Infrastructure (DCI). Some of these data-intensive applications deal with large volumes of data. Several solutions for data-intensive applications have been proposed for Desktop Grid (DG) but they are not efficient in handling large volumes of data. Data management in this environment deals with data access and integration, maintaining basic properties of databases, architecture for querying data, etc. Data in data-intensive applications has to be replicated in multiple nodes for improving data availability and reducing response time. Peer-to-Peer (P2P) is a well established technique for handling large volumes of data and is widely used on the internet. Its environment is similar to the environment of DG. The performance of existing P2P-based solution dealing with generic architecture for replicating large volumes of data is not efficient in DG-based DCI. Therefore, there is a need for a generic architecture for replicating large volumes of data efficiently by using P2P in BOINC based Desktop Grid. Present solutions for data-intensive applications mainly deal with read only data. New type of applications are emerging which deal large volumes of data and Read/Write of data. In emerging scientific experiments, some nodes of DG generate new snapshot of scientific data after regular intervals. This new snapshot of data is generated by updating some of the values of existing data fields. This updated data has to be synchronised in all DG nodes for maintaining data consistency. The performance of data management in DG can be improved by addressing efficient data replication and consistency. Therefore, there is need for algorithms which deal with data Read/Write consistency along with replication for large volumes of data in BOINC based Desktop Grid. The research is to identify efficient solutions for data replication in handling large volumes of data and maintaining Read/Write data consistency using Peer-to-Peer techniques in BOINC based Desktop Grid. This thesis presents the solutions that have been carried out to complete the research

The Grid Relational Catalog Project

Today many DataGrid applications need to manage and process a very large amount of data distributed across multiple grid nodes and stored into heterogeneous databases. Grids encourage and promote the publication, sharing and integration of scientifica data (distributed across several Virtual Organizations) in a more open manner than is currently the case, and many e-Science pojects have an urgent need to interconnect legacy and independently operated databases through a set os data access and integration services. The complexity of data management within a Computational Grid comes from the distribution, scale and heterogeneity of data sources. A set of dynamic and adaptive services could address specific issues related to automatic data management providing high performance and transparency as well as fully exploiting a grid infrastructure. These services should involved data migration and integration, discovery of data sources and so on, providing a transparent and dynamic layer of data virtualization. In this pape we introduce the Grid-DBMS concept, a framework for dynamic data management in a grid enviroment, highlighting its requirements, architecture, components and services. We also present an overview about the Grid Relational Catalog Project (GRelC) developed at the CACT/ISUFI of the University of Lecce, which represents a partial implementation of a Grid-DBMS for the Globus Community

The GRelC Library: A Basic Pillar in the Grid Relational Catalog Architecture

Today many data grid applications need to manage and process a very large amount of data distributed across multiple grid nodes and stored in relational databases. The Grid Relational Catalog Project (GRelC) developed at the CACT/ISUFI of the University of Lecce, represents an attempt to design and deploy a grid-DBMS for the Globus Community. In this paper, after defining the grid-DBMS concept, we describe the GRelC library which is layered on top of the Globus Toolkit. The user can build client applications on top of it that can easily get access to and interact with data resources

Early Experiences with the GRelC Library

Today many Data Grid applications need to manage and process a very large amount of data distributed across multiple grid nodes and stored in relational databases. The Grid Relational Catalog Project (GRelC) developed at the CACT/ISUFI of the University of Lecce, represents an attempt to design and deploy a Grid-DBMS for the Globus Community. In this paper, after defining the Grid-DBMS concept, we describe the GRelC library which is layered on top of the Globus Toolkit. The user can build client applications on top of it that can easily get access to and interact with data resources

The GRELC Project: Towards GRID-DBMS

Several Data Grid applications need to manage a lot of data distributed across heterogeneous and wide spreaded resources and stored in Relational Databases. RDBMSs (Relational Database Management Systems) are not grid enabled (with the notable exception of Oracle), so in order to provide security, transparency, robustness, efficiency and dynamic mechanisms in a Grid environment a new concept can be introduced: the Grid-DBMS. After defining it, we talk about an implementation built on top of the Globus Toolkit: the Grid Relational Catalog Project (GRelC) de veloped at the CACT/ISUFI Laboratory of the University of Lecce. Then we present the basic architecture discussing about its main features and components

Advanced Delivery Mechanisms in the GRelC Project

Today many Data Grid applications need to manage and process a very large amount of data distributed across multiple grid nodes. Several applications often access large databases (i.e. protein data banks, in the bioinformatics field) without any data access services taking into account characteristics of either applications or data types. Such applications could improve their performance and quality of results by using efficient, cross-DBMS, specialized and ad hoc implemented data access services. The Grid Relational Catalog Project (GRelC) developed at the CACT/ISUFI Laboratory of the University of Lecce provides a grid-enabled access service for relational and not relational repositories. In this paper we propose some advanced delivery mechanisms developed within the GRelC project, showing up experimental results related to an European testbed