A functional flow framework for cloud computing
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.
| Autor principal: | |
|---|---|
| Altres autors: | |
| Format: | Thesis |
| Idioma: | eng |
| Publicat: |
Massachusetts Institute of Technology
2013
|
| Matèries: | |
| Accés en línia: | http://hdl.handle.net/1721.1/77453 |
| _version_ | 1826203045525979136 |
|---|---|
| author | Zhang, Amy Xian. |
| author2 | Muriel Médard. |
| author_facet | Muriel Médard. Zhang, Amy Xian. |
| author_sort | Zhang, Amy Xian. |
| collection | MIT |
| description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012. |
| first_indexed | 2024-09-23T12:30:31Z |
| format | Thesis |
| id | mit-1721.1/77453 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T12:30:31Z |
| publishDate | 2013 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/774532020-03-31T18:21:21Z A functional flow framework for cloud computing Zhang, Amy Xian. Muriel Médard. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Electrical Engineering and Computer Science. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012. Cataloged from PDF version of thesis. Includes bibliographical references (p. 53). This thesis covers a basic framework to calculate the maximum computation rate of a set of functions over a network. These functions are broken down into a series of computations, which are distributed among nodes of the network, with the output sent to the terminal node. We analyze two models with different types of computation costs, a linear computation cost model and a maximum computation cost model. We show how computation distribution through the given network changes with different types of computation and communication limitations. This framework can also be used in cloud design, where a network of given complexity is designed to maximize computation rate for a given set of functions. We provide a greedy algorithm that provides one solution to this problem, and create simulations for each framework, and analyze the results. by Amy Zhang. M.Eng. 2013-03-01T15:06:45Z 2013-03-01T15:06:45Z 2012 2012 Thesis http://hdl.handle.net/1721.1/77453 826647936 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 53 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Zhang, Amy Xian. A functional flow framework for cloud computing |
| title | A functional flow framework for cloud computing |
| title_full | A functional flow framework for cloud computing |
| title_fullStr | A functional flow framework for cloud computing |
| title_full_unstemmed | A functional flow framework for cloud computing |
| title_short | A functional flow framework for cloud computing |
| title_sort | functional flow framework for cloud computing |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/77453 |
| work_keys_str_mv | AT zhangamyxian afunctionalflowframeworkforcloudcomputing AT zhangamyxian functionalflowframeworkforcloudcomputing |