Abstract
Many enterprises rely on cloud infrastructure to host their critical applications (such as trading, banking transaction, airline reservation system, and credit card authorization). The unavailability of these applications may lead to severe consequences that go beyond the financial losses, reaching the cloud provider reputation too. However, to maintain high availability in a cloud data center is a difficult task due to its complexity. The power subsystem is crucial for the entire operation of the data center because it supplies power for all other subsystems, including IT components and cooling equipment. Some studies have already proposed models to evaluate the availability of the power subsystem, but none of them are based on standard redundancy models. Standards guide cloud providers regarding availability, points of failure, and watts per square foot based on components' redundancy. This paper proposes RBD and Petri Net models based on the TIA-942 standard to estimate the availability of the data center power subsystem and analyze how failures on power subsystem impact the availability of critical applications. These models are important to resource planning and decision making by the cloud providers, because they may identify which components they ought to invest in order to improve the availability level.
| Original language | English |
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| Title of host publication | 2017 13th International Conference on Network and Service Management, CNSM 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1-7 |
| Number of pages | 7 |
| ISBN (Electronic) | 9783901882982 |
| DOIs | |
| State | Published - Jul 1 2017 |
| Event | 13th International Conference on Network and Service Management, CNSM 2017 - Tokyo, Japan Duration: Nov 26 2017 → Nov 30 2017 |
Publication series
| Name | 2017 13th International Conference on Network and Service Management, CNSM 2017 |
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| Volume | 2018-January |
Conference
| Conference | 13th International Conference on Network and Service Management, CNSM 2017 |
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| Country/Territory | Japan |
| City | Tokyo |
| Period | 11/26/17 → 11/30/17 |
Funding
This work was supported by the RLAM Innovation Center, Ericsson Telecomunicac¸ões S.A., Brazil.