Name
Abstract | ||
|---|---|---|
The P2P-based system for the distributed computing of statistics called DuDE is presented. High scalability and failure resilience features of P2P are exploited to achieve a high-performance distributed system, which avoids the bottlenecks of a centralized computing system. To ensure high data availability, a sophisticated algorithm for distributed data storage is integrated. Furthermore, an algorithm for global peer discovery is presented, which allows for finding all data assigned to peers without the need for a central instance. For the realization of DuDE, common working stages of distributed computing are extended to enable a highly scalable computing system based on P2P technology. Generated results from a test system show a nearly perfect linear speedup for distributed computing as well as high processor and memory relief compared to a centralized solution. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/LCN.2011.6115162 | LCN |
Keywords | Field | DocType |
data handling,mathematics computing,peer-to-peer computing,statistics,DuDE system,P2P environment,centralized computing system,data availability,distributed computing system,distributed data storage,peer discovery,peer-to-peer system,statistics computing,DHT,Distributed Computing,Distributed Storing,Kademlia,P2P | Computer science,Distributed data store,Computer network,Distributed design patterns,Distributed algorithm,Centralized computing,Distributed database,Kademlia,Scalability,Distributed computing,Speedup | Conference |
ISSN | Citations | PageRank |
0742-1303 | 2 | 0.40 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jan Skodzik | 1 | 18 | 5.22 |
| Peter Danielis | 2 | 42 | 13.13 |
| Vlado Altmann | 3 | 17 | 4.16 |
| Jens Rohrbeck | 4 | 2 | 0.74 |
| Dirk Timmermann | 5 | 846 | 101.52 |
| Thomas Bahls | 6 | 2 | 0.74 |
| Daniel Duchow | 7 | 2 | 0.40 |