Virtual Full Replication by Adaptive Segmentation

We propose Virtual Full Replication by Adaptive segmentation (ViFuR-A), and evaluate its ability to maintain scalability in a replicated real-time database. With full replication and eventual consistency, transaction timeliness becomes independent of network delays for all transactions. However, full replication does not scale well, since all updates must be replicated to all nodes, also when data is needed only at a subset of the nodes. With Virtual Full Replication that adapts to actual data needs, resource usage can be bounded and the database can be made scalable. We propose a scheme for adaptive segmentation that detects new data needs and adapts replication. The scheme includes an architecture, a scalable protocol and a replicated directory service that together maintains scalability. We show that adaptive segmentation bounds the required storage at a significantly lower level compared to static segmentation, for a typical workload where the data needs change repeatedly. Adapta...

• Type: Conference
• Year: 2007
• Where: RTCSA
• Authors: Gunnar Mathiason, Sten F. Andler, Sang Hyuk Son
• Keywords: Adaptive Segmentation, Data Needs, Real-Time Computing, RTCSA 2007, Virtual Full Replication