ConClass: A Framework for Real-Time Distributed Knowledge-Based Processing
IEEE Transactions on Knowledge and Data Engineering
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We developed a problem solving framework called ConClass capable of classifying continuous real-time problems dynamically and concurrently on a distributed system. ConClass provides an efficient development environment for describing and decomposing a classification problem and synthesizing solutions. In ConClass, designed concurrency of decomposed subproblems effectively corresponds to the actual distributed computation components. This scheme is useful for designing and implementing efficient distributed processing, making it easier to anticipate and evaluate the system behavior. ConClass system has an object replication feature in order to prevent a particular object from being overloaded. An efficient execution mechanism is implemented without using schedulers or synchronization schemes liable to be bottlenecks. In order to deal with an indeterminate amount of problem data, ConClass dynamically creates object networks to justify hypothesized solutions and thus achieves a dynamic load distribution. We confirmed the efficiency of parallel distributed processing and load balancing of ConClass with an experimental application.