2014 IEEE 33rd International Symposium on Reliable Distributed Systems (SRDS) (2014)
Oct. 6, 2014 to Oct. 9, 2014
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SRDS.2014.34
Very large scale distributed systems provide some of the most interesting research challenges while at the same time being increasingly required by nowadays applications. The escalation in the amount of connected devices and data being produced and exchanged, demands new data management systems. Although new data stores are continuously being proposed, they are not suitable for very large scale environments. The high levels of churn and constant dynamics found in very large scale systems demand robust, proactive and unstructured approaches to data management. In this paper we propose a novel data store solely based on epidemic (or gossip-based) protocols. It leverages the capacity of these protocols to provide data persistence guarantees even in highly dynamic, massive scale systems. We provide an open source prototype of the data store and correspondent evaluation.
Peer-to-peer computing, Protocols, Estimation, Algorithm design and analysis, Heuristic algorithms, Distributed databases, Convergence
F. Maia, M. Matos, R. Vilaca, J. Pereira, R. Oliveira and E. Riviere, "DATAFLASKS: Epidemic Store for Massive Scale Systems," 2014 IEEE 33rd International Symposium on Reliable Distributed Systems (SRDS), Nara, Japan, 2014, pp. 79-88.