CloudScale: elastic resource scaling for multi-tenant cloud systems
By Zhiming Shen, Sethuraman Subbiah, Xiaohui Gu, John Wilkes. ACM Symposium on Cloud Computing, 2011
696 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems
View Paper: https://www.semanticscholar.org/paper/7ba2566d50d33ecb2669e69dc66e0b182b965305
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Christina Delimitrou
- Christos Kozyrakis
- Rolf Stadler
- Brendan Jennings
- José Miguel-Alonso
- Tania Lorido-Botran
- José Antonio Lozano
- Yahya Al-Dhuraibi
In Information Systems
- Christina Delimitrou
- Christos Kozyrakis
- Rolf Stadler
- Brendan Jennings
- José Miguel-Alonso
- Tania Lorido-Botran
- José Antonio Lozano
- Yahya Al-Dhuraibi
Citations in the corpus
- Seer: Leveraging Big Data to Navigate the Complexity of Performance Debugging in Cloud Microservices (2019, methodology): “CloudScale [83], PRESS [48], AGILE [70] and the work by Gmach et al.”
- Resource Management in Clouds: Survey and Research Challenges (2015, background): “[197], where the use of online adaptive padding and reactive error correction to mitigate underestimation is described.”
- A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments (2014, methodology): “Some auto-scaling proposals use time series analysis techniques that deal with pattern identification, applied to the input workload [46, 47, 60, 95].”
- A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges (2017, background): “An alternative is to design upstream modules with a global view of the system (e.g., CloudScale [130]) so that they can check the components’ health and address their prospective scalability problems.”
- Quasar: resource-efficient and QoS-aware cluster management (2014, methodology): “CloudScale [56], PRESS [29], AGILE [46] and the work by Gmach et al.”
- CPI2: CPU performance isolation for shared compute clusters (2013, methodology): “PRESS and CloudScale [16, 34] use a combination of application-level signals and CPU usage data to identify and control usage-driven performance interference.”
- Elasticity in Cloud Computing: State of the Art and Research Challenges (2018, background): “many works [26], [116], [38], [125], [126] that only”