OBAME: Optimized Bio-inspired Algorithm to Maximize Search Efficiency in P2P Databases

P2P databases are characterized by high site-failure rates, unpredictable network topology and complex management, due to the complete absence of a centralized controller. These characteristics have introduced novel challenges and research issues to the field. Among the most difficult challenges is the process of locating information among various participants in the network. This paper presents an original contribution by proposing an Optimized Bio-inspired Algorithm to maximize search efficiency in P2P databases (OBAME). Experimental results showed that OBAME outperformed Ant- and Bee- Inspired algorithms in terms of network traffic and query response time.