MapReduce Performance In Federated Cloud Computing Environments
Abstract
Large scale scientific and engineering applications, and cloud auditing generate huge amounts of data. MapReduce framework coupled with cloud computing is emerging as the viable solution for distributed big data processing. Specifically, if data is generated from distributed sources and computation is also distributed then multiple clouds need to be set up to minimize data transfer, which introduces us to federated distributed or multi-domain clouds. In addition to security concerns of general clouds, distributed clouds expose new challenges to the performance of cloud based applications including cloud auditing and analysis. This book chapter focuses on a method to deploy distributed clouds and evaluates the performance of various cloud based applications over distributed clouds. It also proposes a method to optimize the performance of cloud based applications over high speed networks.
Recommended Citation
P. Kondikoppa et al., "MapReduce Performance In Federated Cloud Computing Environments," High Performance Cloud Auditing and Applications, vol. 9781461432968, pp. 301 - 322, Springer, Nov 2014.
The definitive version is available at https://doi.org/10.1007/978-1-4614-3296-8_12
Department(s)
Computer Science
International Standard Book Number (ISBN)
978-146143296-8;978-146143295-1
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Springer, All rights reserved.
Publication Date
01 Nov 2014
