A RESTful messaging system for asynchronous distributed processing

Ian Jacobi, Alexey Radul
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引用次数: 5

Abstract

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.
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用于异步分布式处理的RESTful消息传递系统
传统上,分布式计算问题的解决方法是将数据划分成足够小的块,以便由普通硬件处理。然而,在存在大量依赖关系或高维的情况下,例如在推理和专家系统中,这种划分是不可能的,这使得分布式系统不太容易处理此类问题。通过划分问题而不是数据,我们可以实现分布式计算的更通用的应用。划分问题而不是数据可能需要网络成员之间更紧密的通信,即使许多网络只能被认为是弱连接的。我们相信传播网络的去中心化实现可能会解决这个问题。通过对通过网络传输的数据合并设置一些约束,我们可以轻松地同步信息并实现最终的收敛,而无需实现序列化所需的机制。为此,我们提出了一种基于rest的消息传递机制的设计,该机制目前正在实现过程中,它允许创建分布式传播器网络,并使用在弱连接网络中最终实现知识聚合的机制。通过利用该机制的RESTful设计,我们还可以通过使用缓存来减少同步期间的带宽使用。
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