Abstract. Scalability requirements for semantic stores lead to distributed hardware-independent solutions to handle and analyze massive amounts of semantic data. We use a different approach by imitating the behaviour of swarm individuals to achieve this scalability. We have implemented our concept of a Self-organized Semantic Storage Service (S4) and present preliminary evaluation results in order to investigate to what extent the performance of a distributed and swarm-based storage system is dependent on its configuration.
Abstract Cloud computing applications require a scalable, elastic and fault tol-erant storage system...
A huge increase in data storage and processing requirements has lead to Big Data, for which next gen...
Most of currently deployed Grid systems employ hierarchical or centralized approaches to simplify sy...
Abstract. The amount of data handled by semantic applications is expected to increase over a level m...
Scalable, adaptive and robust approaches to store and analyze the massive amounts of data expected f...
Traditional approaches for data storage and analysis are facing their limits when handling the enorm...
Swarm is a storage system that provides scalable, reli-able, and cost-effective data storage. Swarm ...
Abstract. This paper describes the design and implementation of a decentral-ized storage cluster for...
This paper describes the design and implementation of Sorrento – a self-organizing storage cluster b...
The Swarm storage system uses log-based striping to achieve high performance. Clients collect applic...
Cluster-based storage systems are popular for data-intensive ap-plications and it is desirable yet c...
Existing storage systems using hierarchical directory tree do not meet scalability and functionality...
This paper presents a distributed persistent object store designed to simplify scalable service in c...
It is widely believed that future computing environment will consist of logically connected but geog...
We discuss issues and technologies for implementing and applying distributed, high-performance stora...
Abstract Cloud computing applications require a scalable, elastic and fault tol-erant storage system...
A huge increase in data storage and processing requirements has lead to Big Data, for which next gen...
Most of currently deployed Grid systems employ hierarchical or centralized approaches to simplify sy...
Abstract. The amount of data handled by semantic applications is expected to increase over a level m...
Scalable, adaptive and robust approaches to store and analyze the massive amounts of data expected f...
Traditional approaches for data storage and analysis are facing their limits when handling the enorm...
Swarm is a storage system that provides scalable, reli-able, and cost-effective data storage. Swarm ...
Abstract. This paper describes the design and implementation of a decentral-ized storage cluster for...
This paper describes the design and implementation of Sorrento – a self-organizing storage cluster b...
The Swarm storage system uses log-based striping to achieve high performance. Clients collect applic...
Cluster-based storage systems are popular for data-intensive ap-plications and it is desirable yet c...
Existing storage systems using hierarchical directory tree do not meet scalability and functionality...
This paper presents a distributed persistent object store designed to simplify scalable service in c...
It is widely believed that future computing environment will consist of logically connected but geog...
We discuss issues and technologies for implementing and applying distributed, high-performance stora...
Abstract Cloud computing applications require a scalable, elastic and fault tol-erant storage system...
A huge increase in data storage and processing requirements has lead to Big Data, for which next gen...
Most of currently deployed Grid systems employ hierarchical or centralized approaches to simplify sy...