Abstract
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.
Highlights
The maturation of the recent cloud-computing paradigm has enabled the construction of flexible network services that are not bound to hardware construction
Experiment 3 In Experiment 3, the observed throughput (OT) of the server system when recovering from the overloaded state to the In Experiment 3, the OT of the server system when recovering from the overloaded state to the normal state was measured and the variance of the fluctuation of the OT was calculated
We verified the behavioral property of the variance of the fluctuation of the transfer rate when the load verified the behavioral property of the variance of the fluctuation of the transfer rate when the load decreased and the server system recovered from the overloaded state to the normal state
Summary
The maturation of the recent cloud-computing paradigm has enabled the construction of flexible network services that are not bound to hardware construction. Elasticity is the ability to change the size of network services flexibly as necessary. 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. When the degradation of the QoS of operating services is detected, it can be assumed that the system is overloaded, and a control operation for resolving the fault should be applied. Such changes in the QoS are detected only after a scenario in which a problem in the server system has already occurred, such as overload, resource exhaustion, or failure. To realize stable and continuous service operation, new approaches for detecting that the system is falling
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