DocumentCode :
166679
Title :
KOALA-C: A task allocator for integrated multicluster and multicloud environments
Author :
Lipu Fei ; Ghit, Bogdan ; Iosup, Alexandru ; Epema, Dick
Author_Institution :
Delft Univ. of Technol., Delft, Netherlands
fYear :
2014
fDate :
22-26 Sept. 2014
Firstpage :
57
Lastpage :
65
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.
Keywords :
cloud computing; resource allocation; scheduling; workstation clusters; KOALA multicluster scheduler; KOALA-C; TAGS task assignment policy; distributed-server systems; integrated multicloud environments; integrated multicluster environments; public infrastructure-as-a-service clouds; resource capacity; resource utilization; scheduling frameworks; task allocator; Adaptation models; Cloud computing; Computational modeling; Computer architecture; Processor scheduling; Resource management; Runtime;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cluster Computing (CLUSTER), 2014 IEEE International Conference on
Conference_Location :
Madrid
Type :
conf
DOI :
10.1109/CLUSTER.2014.6968764
Filename :
6968764
Link To Document :
بازگشت