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

Heba A. Kurid | Zendy; Thanaa S. Alnusairi | Zendy; Hajar S. Almujahed | Zendy

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

Author(s) -

Heba A. Kurid,

Thanaa S. Alnusairi,

Hajar S. Almujahed

Publication year - 2013

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2013.09.010

Subject(s) - computer science , field (mathematics) , process (computing) , network topology , algorithm , database , data mining , distributed computing , computer network , mathematics , pure mathematics , operating system

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

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