A Novel Replication Technique for Implementing Fault-Tolerant Parallel Software

1998 ◽  
pp. 373-384
Author(s):  
Adel Cherif ◽  
Masato Suzuki ◽  
Takuya Katayama
Keyword(s):  
Fault Tolerant ◽  
Parallel Software ◽  
Replication Technique

Session D2: Fault tolerant parallel software

1991 ◽  
Vol 32 (1-5) ◽  
pp. 373-380 ◽  
Author(s):  
Geoffrey F. Carpenter ◽  
Andrew M. Tyrrell
Keyword(s):  
Fault Tolerant ◽  
Parallel Software

Session D2: Fault tolerant parallel software

1991 ◽  
Vol 32 (1-5) ◽  
pp. 365-372 ◽  
Author(s):  
Andrea Clematis ◽  
Vittoria Gianuzzi
Keyword(s):  
Fault Tolerant ◽  
Parallel Software

Session D2: Fault tolerant parallel software

1991 ◽  
Vol 32 (1-5) ◽  
pp. 357 ◽  
Author(s):  
Mario Dal Cin
Keyword(s):  
Fault Tolerant ◽  
Parallel Software

scholarly journals A Robust Distributed Clustering of Large Data Sets on a Grid of Commodity Machines

Data ◽  
2021 ◽  
Vol 6 (7) ◽  
pp. 73
Author(s):  
Salah Taamneh ◽  
Mo’taz Al-Hami ◽  
Hani Bani-Salameh ◽  
Alaa E. Abdallah
Keyword(s):  
Fault Tolerant ◽  
Clustering Algorithms ◽  
Large Data ◽  
High Rate ◽  
Data Sets ◽  
Distributed Clustering ◽  
Actor Model ◽  
Concurrency Model ◽  
Continuous Progress ◽  
Replication Technique

Distributed clustering algorithms have proven to be effective in dramatically reducing execution time. However, distributed environments are characterized by a high rate of failure. Nodes can easily become unreachable. Furthermore, it is not guaranteed that messages are delivered to their destination. As a result, fault tolerance mechanisms are of paramount importance to achieve resiliency and guarantee continuous progress. In this paper, a fault-tolerant distributed k-means algorithm is proposed on a grid of commodity machines. Machines in such an environment are connected in a peer-to-peer fashion and managed by a gossip protocol with the actor model used as the concurrency model. The fact that no synchronization is needed makes it a good fit for parallel processing. Using the passive replication technique for the leader node and the active replication technique for the workers, the system exhibited robustness against failures. The results showed that the distributed k-means algorithm with no fault-tolerant mechanisms achieved up to a 34% improvement over the Hadoop-based k-means algorithm, while the robust one achieved up to a 12% improvement. The experiments also showed that the overhead, using such techniques, was negligible. Moreover, the results indicated that losing up to 10% of the messages had no real impact on the overall performance.

A portable fault-tolerant parallel software MPEG-1 encoder

1996 ◽  
Vol 2 (3) ◽  
pp. 183-197 ◽  
Author(s):  
Iskender Agi ◽  
R. Jagannathan
Keyword(s):  
Fault Tolerant ◽  
Parallel Software
Sign in / Sign up

Export Citation Format

Share Document