Exploiting virtual synchrony in distributed systems
SOSP '87 Proceedings of the eleventh ACM Symposium on Operating systems principles
IEEE Transactions on Computers
Scheduling real-time transactions: a performance evaluation
ACM Transactions on Database Systems (TODS)
Distributed and Parallel Databases - Special issue: Research topics in distributed and parallel databases
Real-time transaction scheduling in database systems
Information Systems
Time, clocks, and the ordering of events in a distributed system
Communications of the ACM
Checkpointing for Optimistic Concurrency Control Methods
IEEE Transactions on Knowledge and Data Engineering
Concurrency Control in Database Systems
IEEE Transactions on Knowledge and Data Engineering
A Priority Ceiling Protocol with Dynamic Adjustment of Serialization Order
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Detection of Global State Predicates
WDAG '91 Proceedings of the 5th International Workshop on Distributed Algorithms
A Causal-Phase Ordering Protocol with Multi-Initiators for Overlapped Broadcast
LCN '99 Proceedings of the 24th Annual IEEE Conference on Local Computer Networks
An Efficient Algorithm for Causal Message Logging
SRDS '98 Proceedings of the The 17th IEEE Symposium on Reliable Distributed Systems
Deadline-Constrained Causal Order
ISORC '00 Proceedings of the Third IEEE International Symposium on Object-Oriented Real-Time Distributed Computing
| Hi-index | 0.00 |
Real-time database applications are istributed in na-ture.Incorporating istributed data into a real-timedatabase framework incurs complexity associated withtransaction concurrency control and database recovery ina istributed context.This article presents an algorithmthat manages soft real-time transactions in a istributeddatabase.It uses a specific causal-ordering protocol toensure the precedence relationships between transactions.Our algorithm is based on a technique, which subdividestransactions into sets.Then the protocol virtually serializesthe executions on distributed servers by using causal phaseordering properties.Causal phases are created accordingto transactions conflicts that may occur between transac-tions sets.Transactions of the same phase are scheduledaccording to their criticality an transactions of two suc-cessive phases are ensured to commit in a causal partialorder.This strategy permits to reduce the execution time,allowing more transactions meeting their deadlines.