dc.contributor.author |
Mershad, Khaleel |
|
dc.contributor.author |
Kaitoua, Abdul Rahman |
|
dc.contributor.author |
Artail, Hassan |
|
dc.contributor.author |
Saghir, Mazen A.R. |
|
dc.contributor.author |
Hajj, Hazem |
|
dc.date.accessioned |
2024-03-06T13:34:09Z |
|
dc.date.available |
2024-03-06T13:34:09Z |
|
dc.date.copyright |
2013 |
en_US |
dc.date.issued |
2013-11-07 |
|
dc.identifier.isbn |
9780769550244 |
en_US |
dc.identifier.uri |
http://hdl.handle.net/10725/15384 |
|
dc.description.abstract |
Cloud computing is increasingly becoming a desirable and foundational element in international enterprise computing. There are many companies which design, develop, and offer cloud technologies. However, cloud providers are still like lone islands. While current cloud computing models have provided significant benefits of maximizing the use of resources within a cloud, the current solutions still face many challenges including the lack of cross-leverage of available resources across clouds, the need to move data between clouds in some cases, and the lack of a global efficient cooperation between clouds. In [1], we addressed some of these challenges by providing an approach that enables various cloud providers to cooperate in order to execute, together, common requests. In this paper, we illustrate several enhancements to our work in [1] which focus on integrating hardware acceleration with the cloud services. We extend the Hadoop framework by adding provisions for hardware acceleration with Field Programmable Gate Arrays (FPGAs) within the cloud, for multi-cloud interaction, and for global cloud management. Hardware acceleration is used to offload computations when needed or as a service within the clouds. It can provide additional sources of revenues, reduced operating costs, and increased resource utilization. We derive a mathematical model for evaluating the performance of the most important entity in our system under various conditions. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
IEEE |
en_US |
dc.subject |
Web services--Congresses |
en_US |
dc.subject |
Cloud computing--Congresses |
en_US |
dc.title |
A Framework for Multi-cloud Cooperation with Hardware Reconfiguration Support |
en_US |
dc.type |
Conference Paper / Proceeding |
en_US |
dc.author.school |
SAS |
en_US |
dc.author.idnumber |
202203388 |
en_US |
dc.author.department |
Computer Science And Mathematics |
en_US |
dc.publication.place |
Los Alamitos, Calif. |
en_US |
dc.keywords |
Cloud computing |
en_US |
dc.keywords |
Hardware acceleration |
en_US |
dc.keywords |
Multi-cloud network |
en_US |
dc.keywords |
Clouds collaboration |
en_US |
dc.keywords |
Hadoop |
en_US |
dc.keywords |
FPGA |
en_US |
dc.description.bibliographiccitations |
Includes bibliographical references. |
en_US |
dc.identifier.doi |
https://doi.org/10.1109/SERVICES.2013.12 |
en_US |
dc.identifier.ctation |
Mershad, K., Kaitoua, A. R., Artail, H., Saghir, M. A., & Hajj, H. (2013, June). A framework for multi-cloud cooperation with hardware reconfiguration support. In 2013 IEEE Ninth World Congress on Services (pp. 52-59). IEEE. |
en_US |
dc.author.email |
khaleel.mershad@lau.edu.lb |
en_US |
dc.conference.date |
28 June 2013 - 03 July 2013 |
en_US |
dc.conference.pages |
52-59 |
en_US |
dc.conference.place |
Santa Clara, CA, USA |
en_US |
dc.conference.title |
2013 IEEE Ninth World Congress on Services |
en_US |
dc.identifier.tou |
http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php |
en_US |
dc.identifier.url |
https://ieeexplore.ieee.org/abstract/document/6655675 |
en_US |
dc.orcid.id |
https://orcid.org/0000-0003-3786-5529 |
en_US |
dc.publication.date |
2013 |
en_US |
dc.author.affiliation |
Lebanese American University |
en_US |