Agent-based platform to support the execution of parallel tasks

Research highlights? We present an agent-based architecture to execute parallel tasks in heterogeneous networks. ? It exploits state of the art agent mobility capabilities easing task management. ? Agents provide a high level of flexibility introducing a minimum overhead. ? The platform has been applied to execute a complex knowledge acquisition task. ? Its throughput scales linearly with regards to the available resources. Parallel computing has been radically evolving in the recent years from the supercomputer multi-processor centralised point of view to the modern distributed approaches such as grid computing. The availability of relatively obsolete or underused hardware and the increasing LAN and WAN interconnection speed have motivated the success of those new paradigms. In this paper, we propose the use of agent technology to improve the management, flexibility and reusability of grid-like parallel computing architectures. We present a general purpose agent-based architecture which is able to manage and execute independent parallel tasks through one or several heterogeneous computer networks - or even Internet nodes - exploiting state of the art agent mobility capabilities. A particular application of the proposed architecture to support the execution of a complex knowledge acquisition task is also introduced, showing a high scalability and a very low overhead.

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