Agent-Based Distributed Parallel Processing
نویسنده
چکیده
Traditional solutions to large-scale signal processing involve massive supercomputers consisting of multiple processors. Data is processed in a pipelined fashion that can incorporate multiple machines and numerous computing stages. The limitations to this approach include flexibility, scalability, cost and fault tolerance. Our research is focused on a new approach to signal processing that utilizes a computing cluster; a network of small personal computers connected via a high speed network medium. In this system, a processing task is partitioned and divided among a family of lightweight agents. These agents are distributed throughout the cluster and compete for computing resources. This approach to signal processing is advantageous in that the system operates as an autonomous entity. Agents execute as a collaborative team, working around node failures and system bottlenecks. Additional computing resources can be added and exploited dynamically, enhancing both the flexibility and scalability of the system.
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