Serverless network file systems
ACM Transactions on Computer Systems (TOCS) - Special issue on operating system principles
Adaptive, multiresolution visualization of large data sets using a distributed memory octree
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
High Performance Cluster Computing: Architectures and Systems
High Performance Cluster Computing: Architectures and Systems
The Master-Slave Paradigm with Heterogeneous Processors
CLUSTER '01 Proceedings of the 3rd IEEE International Conference on Cluster Computing
A New MultiAgent Based Architecture for High Performance I/O in Clusters
ICPPW '01 Proceedings of the 2001 International Conference on Parallel Processing Workshops
PVFS: a parallel file system for linux clusters
ALS'00 Proceedings of the 4th annual Linux Showcase & Conference - Volume 4
Improving GridFTP transfers by means of a multiagent parallel file system
Multiagent and Grid Systems - Grid Computing, high performance and distributed applications
An agent architecture for managing data resources in a grid environment
Future Generation Computer Systems
A parallel data storage interface to GridFTP
ODBASE'06/OTM'06 Proceedings of the 2006 Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, DOA, GADA, and ODBASE - Volume Part II
An autonomic framework for enhancing the quality of data grid services
Future Generation Computer Systems
Future Generation Computer Systems
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The use of parallel file systems constitutes a high-performance solution to the problem known as I/O crisis in parallel or distributed environments. In the last years, clusters have become one of the most cheap and flexible frameworks for the deployment of parallel and distributed applications. Both parallel file systems and clusters have been successfully used in several scenarios, where it is possible to share and access data in an efficient way. In fact, clusters provide a huge number of advantages to this kind of systems, the wide availability of tools integrated with them being one of the most important. Nevertheless, clusters and, in general, high-availability distributed systems are characterized to be dynamically modified. Operations such as the addition or elimination of nodes are typical in a cluster environment. Therefore, it is necessary to use new approaches for the dynamic reconfiguration of the nodes that belong to a cluster. This paper describes a mathematical formalism for achieving high-performance and dynamic reconfiguration of data-based clusters with service maintenance.