Online Transaction Processing(OLTP)gets support from data partitioning to achieve better performance and scalability.The primary objective of database and application developers is to provide scalable and reliable dat...Online Transaction Processing(OLTP)gets support from data partitioning to achieve better performance and scalability.The primary objective of database and application developers is to provide scalable and reliable database systems.This research presents a novel method for data partitioning and load balancing for scalable transactions.Data is efficiently partitioned using the hybrid graph partitioning method.Optimized load balancing(OLB)approach is applied to calculate the weight factor,average workload,and partition efficiency.The presented approach is appropriate for various online data transaction applications.The quality of the proposed approach is examined using OLTP database benchmark.The performance of the proposed methodology significantly outperformed with respect to metrics like throughput,response time,and CPU utilization.展开更多
文摘Online Transaction Processing(OLTP)gets support from data partitioning to achieve better performance and scalability.The primary objective of database and application developers is to provide scalable and reliable database systems.This research presents a novel method for data partitioning and load balancing for scalable transactions.Data is efficiently partitioned using the hybrid graph partitioning method.Optimized load balancing(OLB)approach is applied to calculate the weight factor,average workload,and partition efficiency.The presented approach is appropriate for various online data transaction applications.The quality of the proposed approach is examined using OLTP database benchmark.The performance of the proposed methodology significantly outperformed with respect to metrics like throughput,response time,and CPU utilization.
