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Distributed Linear Programming and Resource Management for Data Mining in Distributed Environments

机译:分布式环境中数据挖掘的分布式线性规划和资源管理

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摘要

Advances in computing and communication has resulted in very large scale distributed environments in recent years. They are capable of storing large volumes of data and often have multiple compute nodes. However, the inherent heterogeneity of data components, the dynamic nature of distributed systems, the need for information synchronization and data fusion over a network and security and access control issues makes the problem of resource management and monitoring a tremendous challenge. In particular, centralized algorithms for management of resources and data may not be sufficient to manage complex distributed systems. In this paper, we present a distributed algorithm for resource and data management which builds on the traditional simplex algorithm used for solving linear optimization problems. Our distributed algorithm is an exact one meaning its results are identical if run in a centralized setting. We provide extensive analytical results and experiments on simulated data to demonstrate the performance of our algorithm.
机译:近年来,计算和通信的进步导致了非常大规模的分布式环境。它们能够存储大量数据,并且通常具有多个计算节点。但是,数据组件固有的异构性,分布式系统的动态特性,通过网络进行信息同步和数据融合的需求以及安全性和访问控制问题,使得资源管理和监视问题面临巨大挑战。特别是,用于资源和数据管理的集中式算法可能不足以管理复杂的分布式系统。在本文中,我们提出了一种用于资源和数据管理的分布式算法,该算法建立在用于解决线性优化问题的传统单纯形算法的基础上。我们的分布式算法是一种精确的算法,这意味着如果在集中式设置中运行,其结果是相同的。我们提供了广泛的分析结果和对模拟数据的实验,以证明我们算法的性能。

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