| Full text | |
| Author(s): |
Lago, Daniel G.
[1, 2]
;
da Silva, Rodrigo A. C.
[2]
;
Madeira, Edmundo R. M.
[2]
;
da Fonseca, Nelson L. S.
[2]
;
Medhi, Deep
[3]
Total Authors: 5
|
| Affiliation: | [1] Fed Ctr Technol Educ Minas Gerais, Av Imigrantes 1000, BR-37022560 Varginha, MG - Brazil
[2] Univ Estadual Campinas, Av Albert Einstein 1251, BR-13083852 Campinas, SP - Brazil
[3] Univ Missouri, 5100 Rockhill Rd, Kansas City, MO 64110 - USA
Total Affiliations: 3
|
| Document type: | Journal article |
| Source: | SIMULATION MODELLING PRACTICE AND THEORY; v. 110, JUL 2021. |
| Web of Science Citations: | 1 |
| Abstract | |
One of the significant limitations in the evaluation of hybrid clouds is the difficulty in validating new solutions by their deployment in real systems since replication of tests on large environments is usually highly expensive. To overcome these limitations, simulators have become popular for conducting preliminary tests. However, there is still a lack of simulation tools with easy-to-use code that allows handling diverse cloud scenarios and the simulation of energy consumption of all devices (hosts, switches, routers, and storage). To fill this gap, the simulator SinergyCloud has been developed to evaluate data centers in hybrid clouds. SinergyCloud allows evaluating diverse cloud scenarios, including energy consumption, workflow makespan, the completion time of tasks, and migrations of virtual machines, with a fine granularity of abstraction. SinergyCloud can handle the simulation of hybrid clouds with multiple data centers composed of hundreds of thousands of devices. Moreover, it is a Java based, event-driven, and packet-level simulator, having a less steep learning curve than do other simulators. To show the feasibility of SinergyCloud, we performed accuracy and scalability analyses. Metrics values obtained by another simulator had less than 1% difference compared to SinergyCloud, demonstrating its accuracy. In terms of scalability, a scenario with 10,000 hosts was simulated in about 7 h using a typical personal computer. A comprehensive analysis of algorithms for the scheduling of virtual machines in a hybrid cloud is also presented, showing how to perform various evaluations. (AU) | |
| FAPESP's process: | 15/24494-8 - Communications and processing of big data in cloud and fog computing |
| Grantee: | Nelson Luis Saldanha da Fonseca |
| Support Opportunities: | Research Projects - Thematic Grants |