Journal
APPLIED SCIENCES-BASEL
Volume 7, Issue 11, Pages -Publisher
MDPI
DOI: 10.3390/app7111145
Keywords
macroscopic behavioral model; variance of fluctuation; behavioral monitoring; management of server systems; empirical study
Categories
Funding
- Japan Society for the Promotion of Science (JSPS) [16K00292]
- Grants-in-Aid for Scientific Research [16K00292] Funding Source: KAKEN
Ask authors/readers for more resources
Elasticity is one of the key features of cloud-hosted services built on virtualization technology. To utilize the elasticity of cloud environments, administrators should accurately capture the operational status of server systems, which changes constantly according to service requests incoming irregularly. However, it is difficult to detect and avoid in advance that operating services are falling into an undesirable state. In this paper, we focus on the management of server systems that include cloud systems, and propose a new method for detecting the sign of undesirable scenarios before the system becomes overloaded as a result of various causes. In this method, a measure that utilizes the fluctuation of the macroscopic operational state observed in the server system is introduced. The proposed measure has the property of drastically increasing before the server system is in an undesirable state. Using the proposed measure, we realize a function to detect that the server system is falling into an overload scenario, and we demonstrate its effectiveness through experiments.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available