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- W3034307922 abstract "We have witnessed a surge in both the big data applications being hosted by an assortment of cloud vendors, and in the astronomical amount of data they produce and consume on a daily basis. Traditional cluster computing frameworks can hardly cope with the unprecedented data volume and the geo-distributed, cross-cloud data distribution due to their limited scalability and adaptability across the heterogeneous clouds. Moreover, running data-intensive applications across clouds at will is extremely cost-inefficient and likely to incur outrageous expenses. Hence, we introduce our cloud-agnostic system PIVOT with the novel cost-aware scheduling algorithm, which enables data-intensive applications to run and scale across clouds instantly in a cost-efficient manner. We evaluate our system and scheduling algorithm extensively with the Alibaba production cluster trace, as well as real-world big data applications on a 100-node deployment across 11 regions (31 availability zones) on AWS and GCP. The experimental results show that PIVOT achieves up to 90.8% saving in expense for VM subscription and 99.2% for egress network traffic compared to the state-of-the-art baselines. Notably, the cost-aware scheduling also achieves over 4x speedup in data transfers for data-intensive applications." @default.
- W3034307922 created "2020-06-19" @default.
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- W3034307922 date "2020-04-01" @default.
- W3034307922 modified "2023-09-25" @default.
- W3034307922 title "A Cloud-Agnostic Framework to Enable Cost-Aware Scheduling of Applications in a Multi-Cloud Environment" @default.
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- W3034307922 doi "https://doi.org/10.1109/noms47738.2020.9110325" @default.
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