Queueing networks and Markov chains: modeling and performance evaluation with computer science applications
Dynamic Programming and Optimal Control, Two Volume Set
Dynamic Programming and Optimal Control, Two Volume Set
Replication Techniques in Distributed Systems
Replication Techniques in Distributed Systems
Simulation with Arena
Convex Optimization
Database Solutions: A Step by Step Guide to Building Databases (2nd Edition)
Database Solutions: A Step by Step Guide to Building Databases (2nd Edition)
Introduction to Discrete Event Systems
Introduction to Discrete Event Systems
Coverage in fault-tolerant control
Automatica (Journal of IFAC)
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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 systemfor 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.