अमूर्त

Data Mining for Data Cloud and Compute Cloud

Prof. Uzma Ali, Prof. Punam Khandar

Cloud computing is the use of computing resources (hardware and software) that are delivered as a service over a network (typically the Internet). The name comes from the use of a cloud-shaped symbol as an abstraction for the complex infrastructure it contains in system diagrams. Cloud computing entrusts remote services with a user's data, software and computation. A storage cloud provides storage services, while a compute cloud provides compute services. We describe the design of the Sector storage cloud and how it provides the storage services required by the Sphere compute cloud. A cloud can be a storage cloud that provides block or file based storage service or it can be a compute cloud that provides computational services. Moreover in this paper we have reviewed the design and implementation of sector storage cloud and sphere compute cloud. Sector is the distributed file system, while sphere is the parallel in-storage data processing framework that can be used to process data stored in sector. Sector and Sphere are designed for analyzing large data sets using computer clusters connected with wide area high performance networks (for example, 10+ Gb/s). We describe a distributed data mining application that we have developed using Sector and Sphere. Mining association rules is one of the most important aspects in data mining. Association rules are dependency rules which predict occurrence of an item based on occurrences of other items. Sector is the distributed file system, while sphere is the parallel in-storage data processing framework that can be used to process data stored in sector.

अस्वीकृति: इस सारांश का अनुवाद कृत्रिम बुद्धिमत्ता उपकरणों का उपयोग करके किया गया है और इसे अभी तक समीक्षा या सत्यापित नहीं किया गया है।

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