Abstract
Companies, scientific communities, and individual scientists with varying requirements for their compute-intensive applications may want to use public Infrastructure-as-a-Service clouds to increase the capacity of the resources they have access to. To enable such access, resource managers that currently act as gateways to clusters may also do so for clouds, but for this they require new architectures and scheduling frameworks. In this paper, we present the design and implementation of KOALA-C, which is an extension of the KOALA multicluster scheduler to multicloud environments. KOALA-C enables uniform management across multicluster and multicloud environments by provisioning resources from both infrastructures and grouping them into clusters of resources called sites. KOALA-C incorporates a comprehensive list of policies for scheduling jobs across multiple (sets of) sites, including both traditional policies and two new policies inspired by the well-known TAGS task assignment policy in distributed-server systems. Finally, we evaluate KOALA-C through realistic simulations and real-world experiments, and show that the new architecture and in particular its new policies show promise in achieving good job slowdown with high resource utilization.
| Original language | English |
|---|---|
| Title of host publication | 2014 IEEE International Conference on Cluster Computing, CLUSTER 2014, Madrid, Spain, September 22-26, 2014 |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. |
| Pages | 57-65 |
| Number of pages | 9 |
| ISBN (Electronic) | 9781479955480 |
| DOIs | |
| Publication status | Published - 26 Nov 2014 |
| Externally published | Yes |
| Event | 16th IEEE International Conference on Cluster Computing, CLUSTER 2014 - Madrid, Spain Duration: 22 Sept 2014 → 26 Sept 2014 |
Conference
| Conference | 16th IEEE International Conference on Cluster Computing, CLUSTER 2014 |
|---|---|
| Country/Territory | Spain |
| City | Madrid |
| Period | 22/09/14 → 26/09/14 |
Keywords
- Runtime
- Cloud computing
- Resource management
- Processor scheduling
- Computer architecture
- Computational modeling
- Adaptation models