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Displaying 1-7 out of 7 total
On the Performance of Byzantine Fault-Tolerant MapReduce
IEEE Transactions on Dependable and Secure Computing
By Pedro Costa,Marcelo Pasin,Alysson Neves Bessani,Miguel P. Correia
Issue Date:September 2013
MapReduce is often used for critical data processing, e.g., in the context of scientific or financial simulation. However, there is evidence in the literature that there are arbitrary (or Byzantine) faults that may corrupt the results of MapReduce without ...
Byzantine Fault-Tolerant MapReduce: Faults are Not Just Crashes
Cloud Computing Technology and Science, IEEE International Conference on
By Pedro Costa,Marcelo Pasin,Alysson N. Bessani,Miguel Correia
Issue Date:December 2011
MapReduce is often used to run critical jobs such as scientific data analysis. However, evidence in the literature shows that arbitrary faults do occur and can probably corrupt the results of MapReduce jobs. MapReduce runtimes like Hadoop tolerate crash fa...
Optimizing Deadline-Driven Bulk Data Transfers in Overlay Networks
Computer Communications and Networks, International Conference on
By Andrei Agapi, Sebastien Soudan, Marcelo Pasin, Pascale Vicat-Blanc Primet, Thilo Kielmann
Issue Date:August 2009
No summary available.
Asynchronous Communication in Java over Infiniband and DECK
Computer Architecture and High Performance Computing, Symposium on
By Rodrigo Da Rosa Righi, Philippe O. A. Navaux, Marcia Cristina Cera, Marcelo Pasin
Issue Date:October 2005
Java is becoming an attractive and easy to use programming language. It provides two systems for distributed computing, RMI and sockets, which describe a synchronous communication over TCP/IP. These Java core features may not be the best choice for cluster...
On the Feasibility of Byzantine Fault-Tolerant MapReduce in Clouds-of-Clouds
2012 IEEE 31st International Symposium on Reliable Distributed Systems (SRDS)
By Miguel Correia,Pedro Costa,Marcelo Pasin,Alysson Bessani,Fernando Ramos,Paulo Verissimo
Issue Date:October 2012
MapReduce is a framework for processing large data sets largely used in cloud computing. MapReduce implementations like Hadoop can tolerate crashes and file corruptions, but there is evidence that general arbitrary faults do occur and can affect the correc...
StreamHub: a massively parallel architecture for high-performance content-based publish/subscribe
Found in: Proceedings of the 7th ACM international conference on Distributed event-based systems (DEBS '13)
By Christof Fetzer, Emanuel Onica, Etienne Rivière, Jean-François Pineau, Marcelo Pasin, Pascal Felber, Raphaël Barazzutti, Stefan Weigert
Issue Date:June 2013
By routing messages based on their content, publish/subscribe (pub/sub) systems remove the need to establish and maintain fixed communication channels. Pub/sub is a natural candidate for designing large-scale systems, composed of applications running in di...
Trustworthy and resilient monitoring system for cloud infrastructures
Found in: Proceedings of the Workshop on Posters and Demos Track (PDT '11)
By Antonio Casimiro, Diego Kreutz, Marcelo Pasin, Smruti Padhy
Issue Date:December 2011
Current monitoring systems for cloud infrastructures are based on local, centralized or hierarchical model approaches such as HP Openview and ArcSight. Additionally, they do not look deep into resilience and delivering trustworthy data of its own services ...
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