Crayons: An Azure Cloud Based Parallel System for GIS Overlay Operations

Dinesh Agarwal
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引用次数: 8

Abstract

Processing of extremely large polygonal (vector-based) spatial datasets has been a long-standing research challenge for scientists in the Geographic Information Systems and Science (GIS) community. Surprisingly, it is not for the lack of individual parallel algorithm; we discovered that the irregular and data intensive nature of the underlying processing is the main reason for the meager amount of work by way of system design and implementation. Furthermore, of all the systems reported in the literature, very few deal with the complexities of vector-based datasets and none, including commercial systems, on the cloud platform. We have designed and implemented an open-architecture-based system named Crayons for Windows Azure cloud platform using state-of-the-art techniques. We have implemented three different architectures of Crayons with different load balancing schemes. Crayons scales well for sufficiently large data sets, achieving end-to-end absolute speedup of over 28-fold employing 100 Azure processors. For smaller and more irregular workload, it still yields over 10-fold speedup.
蜡笔:一个基于Azure云的GIS叠加操作并行系统
超大多边形(矢量)空间数据集的处理一直是地理信息系统与科学(GIS)界科学家长期面临的研究挑战。令人惊讶的是,这并不是因为缺乏单独的并行算法;我们发现,底层处理的不规则性和数据密集性是系统设计和实现方面工作量不足的主要原因。此外,在文献中报道的所有系统中,很少有系统处理基于向量的数据集的复杂性,而且没有一个系统(包括商业系统)在云平台上。我们使用最先进的技术为Windows Azure云平台设计并实现了一个基于开放架构的系统Crayons。我们用不同的负载均衡方案实现了蜡笔的三种不同架构。Crayons可以很好地扩展到足够大的数据集,使用100个Azure处理器可以实现超过28倍的端到端绝对加速。对于更小和更不规则的工作负载,它仍然可以产生超过10倍的加速。
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