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Desktop Grids have been used intensively to deploy applications at low cost. Applications types are classified into high throughput computing and high throughput data management. Desktop Grids such as Condor, BOINC, XtremWeb and Our Grid provide a wide range of high throughput computing systems. on the other hand, several data management systems such as Bit dew, GatorShare, Stork, Grid FTP, have been...
In order to process service failure quickly, a new failure recovery for service supporting context persistence named G-FRF is given, which is based on the existing failure recovery frameworks for Web Services. Failure recovery requirements of manager job services in grid computing are taken into account in the framework. during normal execution, service state is monitored and context is saved. When...
Fault tolerance is an important issue in service oriented architectures like Grid and Cloud systems, where many and heterogeneous machines are used. In this paper we present a flexible failure handling framework which extends a service-oriented architecture for Distributed Data Mining previously proposed, addressing the requirements for handling fault tolerance in service-oriented Grids. In particular,...
Aggregating the capacity and bandwidth of the commodity disks in the nodes of a cluster provides cost effective and high performance storage systems. Nevertheless, this strategy could be a feasible approach only if the mean time to failure of disks and nodes is faced. The number of failures increases with the nodes and it is especially important in parallel file systems, like PVFS, because having...
How to federate the machines of all Boinc, Condor and XtremWeb projects? If you believe in volunteer computing and want to share more than one project then BonjourGrid may help. In previous works, we proposed a novel approach, called BonjourGrid, to orchestrate multiple instances of Institutional Desktop Grid middleware. It is our way to remove the risk of bottleneck and failure, and to guarantee...
Real time application with replicated data in grid environment has received particular attention for providing efficient access, fault tolerance and enhance the performance of the system. This paper presents the new failure semantic to manage neighbour replication data in distributed environment. The failure semantic classes include the transaction abort and system failures. We address how to build...
Efficient management of massive data sets is a key aspect in typical grid and e-science applications. To this end, the benefits of employing database technologies in such applications has been identified since the early days of grid computing, which aims at enabling coordinated resource sharing,knowledge generation and problem solving in dynamic,multi-institutional virtual organizations through a...
The management of the large scale heterogeneous resources is a critical issue in grid computing. The resource management system (RMS) is an essential component of grids. To ensure the QoS of the upper layer service, it raises high requirement for the performance, fault-tolerance and scalability of RMS. In this paper, we study three typical structures of RMS, including centralized, hierarchical and...
The virtual infrastructure has become more and more popular in the grid and cloud computing. With the aggrandizement scale, the management of the resources in virtual infrastructure faces a great technical challenge. To support the upper services effectively, it raises higher requirements for the performance, fault-tolerance and scalability of virtual infrastructure management systems. In this paper,...
The understanding of H diffusion in materials is pivotal to designing suitable processes. Though a nudged elastic band (NEB)+molecular dynamics (MD)/quantum mechanics (QM) algorithm has been developed to simulate H diffusion in materials by our group, it is often not computationally feasible for large-scale models on a conventional single system. We thus gridify the NEB+MD/QM algorithm on the top...
There exists numerous Grid middleware to develop and execute programs on the computational Grid, but they still require intensive work from their users. BitDew is made to facilitate the usage of large scale Grid with dynamic, heterogeneous, volatile and highly distributed computing resources for applications that require a huge amount of data processing. Data-intensive applications form an important...
Desktop Grids use the computing, network and storage resources from idle desktop PC's distributed over multiple-LAN's or the Internet to compute a large variety of resource-demanding distributed applications. While these applications need to access, compute, store and circulate large volumes of data, little attention has been paid to data management in such large-scale, dynamic, heterogeneous, volatile...
Grid Computing is an effective computing paradigm widely used in solving complex problems. There are a variety of existing grid middleware systems which support operation of grid infrastructures, including CNGrid GOS, EGEE gLite, Globus Toolkit, and OSG Condor etc. These grid infrastructures focus on encapsulating underlying computing and storage resources and providing necessary basic services such...
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