A causal-phase protocol to order soft real-time transactions in a distributed database

Real-time database applications are distributed in nature. Incorporating distributed data into a real-time database framework incurs complexity associated with transaction concurrency control and database recovery in a distributed context. This article presents an algorithm that manages soft real-time transactions in a distributed database. It uses a specific causal-ordering protocol to ensure the precedence relationships between transactions. Our algorithm is based on a technique which subdivides transactions into sets. Then the protocol virtually serializes the executions on distributed servers by using causal phase ordering properties. Causal phases are created according to transaction conflicts that may occur between transaction sets. Transactions of the same phase are scheduled according to their criticality and transactions of two successive phases are ensured to commit in a causal partial order This strategy permits us to reduce the execution time, allowing more transactions to meet their deadlines.