Q-clouds: managing performance interference effects for QoS-aware clouds
By Ripal Nathuji, Aman Kansal, Alireza Ghaffarkhah. European Conference on Computer Systems, 2010
631 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems
View Paper: https://www.semanticscholar.org/paper/490d862480cf30949dce90e832aa292c498ac768
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
- David Lo
- Liqun Cheng
- Rama K. Govindaraju
- Yu Gan
- Yuan He
- Meghna Pancholi
In Information Systems
- Christina Delimitrou
- Liqun Cheng
- David Lo
- Rama K. Govindaraju
- Christos Kozyrakis
- Parthasarathy Ranganathan
- Yu Gan
- Yuan He
Citations in the corpus
- Heracles: Improving resource efficiency at scale (2015, background): “develop a feedback-based scheme that tunes resource assignment to mitigate interference for colocated VMs [58].”
- Paragon: QoS-aware scheduling for heterogeneous datacenters (2013, background): “Most previous schemes address this issue with detailed but offline application characterization or long-term monitoring and modeling approaches [25, 29, 36].”
- FIRM: An Intelligent Fine-Grained Resource Management Framework for SLO-Oriented Microservices (2020, background): “Examples include Borg [119], Mesos [43], Tarcil [28], Paragon [25], Quasar [26], Morpheus [54], DeepDive [73], and Q-clouds [71].”
- A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems (2016, background): “Accordingly, Q-Clouds was developed [8] that is a QoS-aware control framework that tunes resource allocations to mitigate performance interference effects.”
- Osmotic Computing: A New Paradigm for Edge/Cloud Integration (2016, background): “12 However, they consider only CPU-bound or compute-intensive applications.”
- Seer: Leveraging Big Data to Navigate the Complexity of Performance Debugging in Cloud Microservices (2019, background): “developed a feedback-based scheme that tunes resource assignments to mitigate memory interference [69].”
- Quasar: resource-efficient and QoS-aware cluster management (2014, background): “[45] developed a feedback-based scheme that tunes resource assignment to mitigate interference effects.”