oDASuANCO - Ant Colony Optimization based Data Allocation Strategy in Peer-to-Peer Distributed Databases

Data Allocation Problem (DAP) incorporates Allocation and Replication methodologies which are involved during the phase of Distributed Database design. Accessibility and availability are the thriving factors for better design of Distributed Databases. High degree of Accessibility and Availability are the outcomes of effective methodologies for Allocation and Replication. This paper proposes a methodology for Reallocation and Replication of fragments in Peer-to-Peer Distributed Database Systems (P2PDDBS) environment using Ant Colony Optimization (ACO) principle, namely, optimized Data Allocation Strategy using Ant Colony Optimization (oDASuANCO). ACO algorithm is a meta-heuristic, works with swarm intelligence technique. The experimental results show that ACO based reallocation and replication methodology improves the ratio of successful queries than the initial allocation of fragments.