Approximation algorithms for bin packing: a survey
Approximation algorithms for NP-hard problems
IEEE Transactions on Parallel and Distributed Systems
Job Scheduling is More Important than Processor Allocation for Hypercube Computers
IEEE Transactions on Parallel and Distributed Systems
The ANL/IBM SP Scheduling System
IPPS '95 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Selective Reservation Strategies for Backfill Job Scheduling
JSSPP '02 Revised Papers from the 8th International Workshop on Job Scheduling Strategies for Parallel Processing
Self-Adaptive Scheduler Parameterization via Online Simulation
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Improving and Stabilizing Parallel Computer Performance Using Adaptive Backfilling
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Backfilling with lookahead to optimize the packing of parallel jobs
Journal of Parallel and Distributed Computing
Backfilling Using System-Generated Predictions Rather than User Runtime Estimates
IEEE Transactions on Parallel and Distributed Systems
The performance of bags-of-tasks in large-scale distributed systems
HPDC '08 Proceedings of the 17th international symposium on High performance distributed computing
DGSim: Comparing Grid Resource Management Architectures through Trace-Based Simulation
Euro-Par '08 Proceedings of the 14th international Euro-Par conference on Parallel Processing
Cross-disciplinary perspectives on meta-learning for algorithm selection
ACM Computing Surveys (CSUR)
IEEE Transactions on Parallel and Distributed Systems
Contextualization: Providing One-Click Virtual Clusters
ESCIENCE '08 Proceedings of the 2008 Fourth IEEE International Conference on eScience
Trace-based evaluation of job runtime and queue wait time predictions in grids
Proceedings of the 18th ACM international symposium on High performance distributed computing
Evaluating the cost-benefit of using cloud computing to extend the capacity of clusters
Proceedings of the 18th ACM international symposium on High performance distributed computing
SATzilla: portfolio-based algorithm selection for SAT
Journal of Artificial Intelligence Research
Evaluating the impact of inaccurate information in utility-based scheduling
Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis
On the Use of Machine Learning to Predict the Time and Resources Consumed by Applications
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Performance analysis of dynamic workflow scheduling in multicluster grids
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing
IEEE Transactions on Parallel and Distributed Systems
Cost-Wait Trade-Offs in Client-Side Resource Provisioning with Elastic Clouds
CLOUD '11 Proceedings of the 2011 IEEE 4th International Conference on Cloud Computing
Flexible resource allocation for reliable virtual cluster computing systems
Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
Auto-scaling to minimize cost and meet application deadlines in cloud workflows
Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
In Cloud, Can Scientific Communities Benefit from the Economies of Scale?
IEEE Transactions on Parallel and Distributed Systems
Parallel job scheduling — a status report
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
An Analysis of Provisioning and Allocation Policies for Infrastructure-as-a-Service Clouds
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
Comparison of Multiple Cloud Frameworks
CLOUD '12 Proceedings of the 2012 IEEE Fifth International Conference on Cloud Computing
A Performance Study on the VM Startup Time in the Cloud
CLOUD '12 Proceedings of the 2012 IEEE Fifth International Conference on Cloud Computing
Provisioning Policies for Elastic Computing Environments
IPDPSW '12 Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum
ExPERT: Pareto-Efficient Task Replication on Grids and a Cloud
IPDPS '12 Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium
Cost- and deadline-constrained provisioning for scientific workflow ensembles in IaaS clouds
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Stochastic Tail-Phase Optimization for Bag-of-Tasks Execution in Clouds
UCC '12 Proceedings of the 2012 IEEE/ACM Fifth International Conference on Utility and Cloud Computing
Free Elasticity and Free CPU Power for Scientific Workloads on IaaS Clouds
ICPADS '12 Proceedings of the 2012 IEEE 18th International Conference on Parallel and Distributed Systems
Scheduling jobs in the cloud using on-demand and reserved instances
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
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Long-term execution of scientific applications often leads to dynamic workloads and varying application requirements. When the execution uses resources provisioned from IaaS clouds, and thus consumption-related payment, efficient and online scheduling algorithms must be found. Portfolio scheduling, which selects dynamically a suitable policy from a broad portfolio, may provide a solution to this problem. However, selecting online the right policy from possibly tens of alternatives remains challenging. In this work, we introduce an abstract model to explore this selection problem. Based on the model, we present a comprehensive portfolio scheduler that includes tens of provisioning and allocation policies. We propose an algorithm that can enlarge the chance of selecting the best policy in limited time, possibly online. Through trace-based simulation, we evaluate various aspects of our portfolio scheduler, and find performance improvements from 7% to 100% in comparison with the best constituent policies and high improvement for bursty workloads.