Lightweight Runtime Conflict Detection for CPU Efficient Transaction Processing

Abstract

High concurrency transaction processing systems deployed in distributed and cloud environments frequently suffer from performance degradation due to conflicts among simultaneous read and write operations. Conventional concurrency control techniques such as Two Phase Locking and Optimistic Concurrency Control introduce substantial runtime overhead under contention. Lock based approaches enforce mutual exclusion and force threads to wait for shared resources, resulting in blocking, frequent context switching, and inefficient processor utilization. As the number of concurrent transactions increases, these waiting periods accumulate and lead to excessive central processing unit usage with limited useful work performed. Optimistic methods attempt to reduce blocking but postpone conflict detection until the validation stage, which often causes repeated transaction aborts and re executions. These retries consume additional computation cycles and further increase processor load. In large scale clusters, such inefficiencies become more pronounced and directly affect system scalability. Empirical observations show that existing mechanisms consistently operate at high processor utilization levels ranging from seventy to eighty eight percent even under moderate workloads. Despite this high CPU usage, throughput improvements remain marginal and latency increases significantly, indicating poor resource efficiency. The combination of blocking synchronization, redundant retries, and late conflict detection results in wasted computation and underutilization of available hardware capacity. These limitations highlight the need for more efficient runtime mechanisms that can manage transactional conflicts while maintaining low CPU usage and better scalability in real time transaction processing environments.