Cloud infrastructure-as-a-service (IaaS) users require stable performance for their applications so that the Quality of Service (QoS) constraints are satisfied. However, they generally experience performance variability, primarily due to multi-tenancy. Such variability may lead to QoS violations for the deployed applications. Existing cloud infrastructure solutions offered by cloud providers (CPs) do not have facilities to detect such violations. Hence, cloud users need to take responsibility for monitoring the performance of their applications in order to detect application-specific QoS violations. In this paper, we propose a novel algorithm for detecting QoS violation for media streaming applications. The algorithm compares the cumulative value of the expected streamed data against the cumulative value of the measured streamed data. Based on this comparison, the algorithm may raise QoS violation alarms. We evaluate the algorithm by deploying a media streaming application in a lab-based cloud setup. Experimental results demonstrate the correctness of the proposed algorithm.
|Name||2018 IEEE International Conference on Autonomic Computing (ICAC)|
|Conference||15th IEEE International Conference on Autonomic Computing (ICAC)|
|Period||03/09/2018 → 07/09/2018|
- Cloud Computing,
- Cloud Monitoring
- QoS Vi- olation Detection
- Media Streaming Application