With the introduction of gridcomputing, complexity of large scale distributed systems has become unmanageable because of the manual system adopted for the management these days. Due to dynamic nature of grid, manual ...
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ISBN:
(纸本)9781424455690
With the introduction of gridcomputing, complexity of large scale distributed systems has become unmanageable because of the manual system adopted for the management these days. Due to dynamic nature of grid, manual management techniques are time-consuming, in-secure and more prone to errors. This leads to new paradigm of self-management through autonomic computing to pervade over the old manual system to begin the next generation of gridcomputing. In this paper, we have discussed the basic concept of gridcomputing and the need for grid to be autonomic. A comparative analysis of different grid middleware has been provided to show the absence of autonomic behavior in current grid architecture. To conclude the discussion, we have mentioned the areas where research work has been lacking and what we believe the community should be considering.
cloudcomputing is a hot spot of current research, involving distributed storage and distributedcomputing and other aspects. In view of the requirements for massive data processing and analysis, this paper analyzed t...
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We consider geographically distributed datacenters forming a collectively managed cloudcomputing system, hosting multiple Service Oriented Architecture (SOA) based context aware applications, each subject to Service ...
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cloudcomputing is an integrated infrastructure for resource sharing andcomputing in distributed environment. In this paper, we propose an ontology management approach in cloudcomputing to provide a unique semantic ...
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The proceedings contain 105 papers. The topics discussed include: LEMO-MR: low overhead and elastic MapReduce implementation optimized for memory and CPU-intensive applications;LEEN: locality/fairness-aware key partit...
ISBN:
(纸本)9780769543024
The proceedings contain 105 papers. The topics discussed include: LEMO-MR: low overhead and elastic MapReduce implementation optimized for memory and CPU-intensive applications;LEEN: locality/fairness-aware key partitioning for MapReduce in the cloud;correlation based file prefetching approach for Hadoop;elasticLM: a novel approach for software licensing in distributedcomputing infrastructures;a mechanism of flexible memory exchange in cloudcomputing environments;fine-grained data access control systems with user accountability in cloudcomputing;a token-based access control system for RDF data in the clouds;performance analysis of high performance computing applications on the Amazon web services cloud;combining grid andcloud resources by use of middleware for SPMD applications;using global behavior modeling to improve QoS in cloud data storage services;and resource allocation with a budget constraint for computing independent tasks in the cloud.
cloudcomputing is an emerging computing paradigm. It aims to share data, caluations, and services transparently among users of a massive grid. It became a hot issue for its adavantage such as "reduce costs"...
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In this paper a novel parallel network traffic control mechanism for cloudcomputing is proposed based on the packet scheduler HTB (Hierarchical Token Buckets). The idea of bandwidth borrowing in HTB makes it suitable...
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This paper presents the various mechanisms for virtual machine image distribution within a large batch farm and between sites that offer cloudcomputing services. The work is presented within the context of the Large ...
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An optimal resource allocation is desired to increase the efficiency of systems processing business or scientific workflows. These systems include the processing of workflows in distributedcomputing environments such...
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cloudcomputing is emerging as a serious paradigm shift in the way we use computers. It relies on several technologies that are not new. However, the increasing availability of bandwidth allows new combinations and op...
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