Title :
DATAFLASKS: Epidemic Store for Massive Scale Systems
Author :
Maia, Francisco ; Matos, Miguel ; Vilaca, Ricardo ; Pereira, J. ; Oliveira, Renato ; Riviere, Etienne
Author_Institution :
High Assurance Software Lab., Univ. Minho, Braga, Portugal
Abstract :
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.
Keywords :
data handling; distributed processing; public domain software; DATAFLASKS; data management systems; data persistence guarantees; epidemic protocols; epidemic store; large scale systems; massive scale systems; nowadays applications; open source prototype; very large scale environments; Algorithm design and analysis; Convergence; Distributed databases; Estimation; Heuristic algorithms; Peer-to-peer computing; Protocols; Dependability; Distributed Systems; Epidemic Protocols; Large Scale Data Stores;
Conference_Titel :
Reliable Distributed Systems (SRDS), 2014 IEEE 33rd International Symposium on
Conference_Location :
Nara
DOI :
10.1109/SRDS.2014.34