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The improvement of file access performance is a great challenge in real-time cloud services. In this paper, we analyze preconditions of dealing with this problem considering the aspects of requirements, hardware, software, and network environments in the cloud. Then we describe the design and implementation of a novel distributed layered cache system built on the top of the Hadoop Distributed File...
The data-intensive scientific applications running on high-end computing system depend on parallel file systems for high-speed data input/output. In most parallel file systems, a file is partitioned into multiple subfiles with a view to allowing it to be accessed concurrently. An important factor in the file partition is the stripe size. However, while working well for certain applications, most existing...
Workload consolidation, sharing physicalresources among multiple workloads, is a promisingtechnique to save cost and energy in cluster computingsystems. This paper highlights a number of challengesassociated with workload consolidation for Hadoop, as oneof the current state-of-the-art data-intensive clustercomputing systems. Through a systematic step-by-stepprocedure, we investigate challenges for...
Creating backup copies is the most commonly used technique to protect from data loss. In order to increase reliability, doing routinely backup is a best practice. Such backup activities will create multiple redundant data streams which is not economic to be directly stored on disk. Similarly, enterprise archival systems usually deal with redundant data, which needs to be stored for later accessing...
Compared with the traditional computing models such as grid computing and cluster computing, a key advantage of Cloud computing is that it provides a practical business model for customers to use remote resources. However, it is challenging for Cloud providers to allocate the pooled computing resources dynamically among the differentiated customers so as to maximize their revenue. It is not an easy...
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