Using MPI (2nd ed.): portable parallel programming with the message-passing interface
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Multi-Objective Optimization Using Evolutionary Algorithms
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ACM SIGPLAN Notices
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The Grid 2: Blueprint for a New Computing Infrastructure
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MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
The cost of doing science on the cloud: the Montage example
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
EGEE - providing a production quality grid for e-science
LGDI '05 Proceedings of the 2005 IEEE International Symposium on Mass Storage Systems and Technology
Future Generation Computer Systems
Dynamic Provision of Computing Resources from Grid Infrastructures and Cloud Providers
GPC '09 Proceedings of the 2009 Workshops at the Grid and Pervasive Computing Conference
Cost-benefit analysis of Cloud Computing versus desktop grids
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Virtual Infrastructure Management in Private and Hybrid Clouds
IEEE Internet Computing
Multiobjective evolutionary algorithms on complex networks
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Elastic Site: Using Clouds to Elastically Extend Site Resources
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Exploring application and infrastructure adaptation on hybrid grid-cloud infrastructure
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
TeraGrid: a foundation for US cyberinfrastructure
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
ICA3PP'10 Proceedings of the 10th international conference on Algorithms and Architectures for Parallel Processing - Volume Part I
Cloud brokering mechanisms for optimized placement of virtual machines across multiple providers
Future Generation Computer Systems
The Aneka platform and QoS-driven resource provisioning for elastic applications on hybrid Clouds
Future Generation Computer Systems
Characterizing spot price dynamics in public cloud environments
Future Generation Computer Systems
Future Generation Computer Systems
Future Generation Computer Systems
Two levels autonomic resource management in virtualized IaaS
Future Generation Computer Systems
Internet of Things (IoT): A vision, architectural elements, and future directions
Future Generation Computer Systems
A family of heuristics for agent-based elastic Cloud bag-of-tasks concurrent scheduling
Future Generation Computer Systems
A web portal for management of aneka-based MultiCloud environments
AusPDC '13 Proceedings of the Eleventh Australasian Symposium on Parallel and Distributed Computing - Volume 140
Market mechanisms for managing datacenters with heterogeneous microarchitectures
ACM Transactions on Computer Systems (TOCS)
On the Performance-Cost Tradeoff for Workflow Scheduling in Hybrid Clouds
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
Accurate Resource Prediction for Hybrid IaaS Clouds Using Workload-Tailored Elastic Compute Units
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
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Scientific applications require large computing power, traditionally exceeding the amount that is available within the premises of a single institution. Therefore, clouds can be used to provide extra resources whenever required. For this vision to be achieved, however, requires both policies defining when and how cloud resources are allocated to applications and a platform implementing not only these policies but also the whole software stack supporting management of applications and resources. Aneka is a cloud application platform capable of provisioning resources obtained from a variety of sources, including private and public clouds, clusters, grids, and desktops grids. In this paper, we present Aneka's deadline-driven provisioning mechanism, which is responsible for supporting quality of service (QoS)-aware execution of scientific applications in hybrid clouds composed of resources obtained from a variety of sources. Experimental results evaluating such a mechanism show that Aneka is able to efficiently allocate resources from different sources in order to reduce application execution times.