Parallel biometrics computing using mobile agents

We present an efficient and effective approach to personal identification by parallel biometrics computing using mobile agents. To overcome the limitations of the existing password-based authentication services on the Internet, we integrate multiple personal features including fingerprints, palmprints, hand geometry and face into a hierarchical structure for fast and reliable personal identification and verification. To increase the speed and flexibility of the process, we use mobile agents as a navigational tool for parallel implementation in a distributed environment, which includes hierarchical biometric feature extraction, multiple feature integration, dynamic biometric data indexing and guided search. To solve the problems associated with bottlenecks and platform dependence, we apply a four-layered structural model and a three-dimensional operational model to achieve high performance. Instead of applying predefined task scheduling schemes to allocate the computing resources, we introduce a new online competitive algorithm to guide the dynamic allocation of mobile agents with greater flexibility. The experimental results demonstrate the feasibility and the potential of the proposed method.