Concurrency Control with Timestamp and Recovery Using Passive Replication

Efficient concurrency control and robust recovery mechanisms are essential for ensuring consistency and availability in group work data-sharing systems. This paper introduces a novel approach combining timestamp-based concurrency control and passive replication to address the challenges of concurrent transaction management and system failure recovery. The timestamp-based method enforces a strict ordering of transactions, preventing conflicts and ensuring consistency across shared data. Passive replication enhances fault tolerance by maintaining synchronized backup copies, enabling efficient recovery with minimal system overhead. Unlike active replication, the proposed method reduces network and processing costs while maintaining high availability and reliability. Experimental results demonstrate that the approach significantly improves system performance by minimizing transaction conflicts, ensuring data integrity, and providing fast recovery during failures. This solution is particularly effective in distributed environments, supporting scalable and reliable collaboration in group work scenarios. This paper presents the implementation and evaluation of a concurrency control mechanism using timestamps combined with a recovery strategy based on passive replication in distributed databases. The proposed method ensures serializability by ordering transactions according to their timestamp, thereby minimizing conflicts and avoiding deadlocks. Recovery is achieved through passive replication, where secondary replicas maintain the latest committed state, enabling seamless failover during failures. Experimental results demonstrate an average transaction time of 150 ms, a 95% conflict resolution success rate, and a failover time of 50 ms. The approach exhibits improved throughput and fault tolerance, making it a viable solution for distributed systems requiring high consistency and availability.