Production matching for large learning systems
Production matching for large learning systems
Managing update conflicts in Bayou, a weakly connected replicated storage system
SOSP '95 Proceedings of the fifteenth ACM symposium on Operating systems principles
SETI@home: an experiment in public-resource computing
Communications of the ACM
Architectural styles and the design of network-based software architectures
Architectural styles and the design of network-based software architectures
Extending the Representational State Transfer (REST) Architectural Style for Decentralized Systems
Proceedings of the 26th International Conference on Software Engineering
BOINC: A System for Public-Resource Computing and Storage
GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Scalable Distributed Reasoning Using MapReduce
ISWC '09 Proceedings of the 8th International Semantic Web Conference
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Traditionally, distributed computing problems have been solved by partitioning data into chunks small enough to be handled by commodity hardware. However, such partitioning is not possible in cases where there are a high number of dependencies or high dimensionality, such as in reasoning and expert systems, rendering such problems less tractable for distributed systems. By instead partitioning the problem, rather than the data, we can achieve a more general application of distributed computing. Partitioning the problem rather than the data may require tighter communication between members of the network, even though many networks can only be assumed to be weakly-connected. We believe that a decentralized implementation of propagator networks may resolve the problem. By placing several constraints on the merging of data transmitted over the network, we can easily synchronize information and achieve eventual convergence without implementing mechanisms needed for serialization. To this end, we present the design of a RESTful messaging mechanism, currently in the process of being implemented, that allows distributed propagator networks to be created, using mechanisms that result in eventual convergence of knowledge across a weakly-connected network. By utilizing a RESTful design of the mechanism, we can also achieve a reduction of bandwidth usage during synchronization through the use of caching.