REPLICATION STRATEGIES BASED ON MARKOV CHAIN MONTE CARLO AND OPTIMIZATION ON CLOUD APPLICATIONS

摘要

This work positioned a dynamic replication strategy capable of meeting tenant availability and performance criteria concomitantly. The Monte Carlo BAT Optimization MCBO model is a strategy geared towards calculating the optimal path to update distributed replicas on cloud sustaining high data availability. In general, replica creation is prompted in two circumstances: a specific number of replicas is not achieved or in case of unsatisfactory response time objective. Following this, it is necessary for the replication process to be successful in order to design the MCBO model for determine optimal path. Data replication and query scheduling were combined for ensuring the replica placement in a load-balancing manner while handling tenant budget. The experimental outcomes revealed significant improvement for the availability and performance following the use of the model.