Data Allocation in Distributed Database based on CSO

Distributed databases (DDBs) provide smart processing of large databases, the problems fragmentation and allocation are vital design in addition to centralized design. The majority performance degradation DDBs is due communication cost by query remote access retrieval data. This can be optimized through an efficient data approach that will flexible a low accessible sites. In this paper, novel high designed using Chicken Swarm Optimization (CSO) algorithm. Data problem (DAP) NP-Hard modelled as optimization problem. proposed initially characterizes DAP into optimal choosing appropriate minimal provoking sites for fragments. Then CSO algorithm optimally chooses each fragments without creating much overhead route diversions. enhances overall distributed database subsequently ensures quality replication. experimental results illustrate based intelligent fragment has better than most existing approaches thus signifies impact DDBs.