Fault-Tolerant Control of a Distributed Database System

Abstract

Optimal state information-based control policy for a distributed database system subject to server failures is considered. Fault-tolerance is made possible by the partitioned architecture of the system and data redundancy therein. Control actions include restoration of lost data sets in a single server using redundant data sets in the remaining servers, routing of queries to intact servers, or overhaul of the entire system for renewal. Control policies are determined by solving Markov decision problems with cost criteria that penalize system unavailability and slow query response. Steady-state system availability and expected query response time of the controlled database are evaluated with the Markov model of the database. Robustness is addressed by introducing additional states into the database model to account for control action delays and decision errors. A robust control policy is solved for the Markov decision problem described by the augmented state model.