Scaling and Scheduling to Maximize Application Performance within Budget Constraints in Cloud Workflows

@article{Mao2013ScalingAS,
  title={Scaling and Scheduling to Maximize Application Performance within Budget Constraints in Cloud Workflows},
  author={Ming Mao and Marty Humphrey},
  journal={2013 IEEE 27th International Symposium on Parallel and Distributed Processing},
  year={2013},
  pages={67-78}
}
  • Ming MaoM. Humphrey
  • Published 20 May 2013
  • Computer Science
  • 2013 IEEE 27th International Symposium on Parallel and Distributed Processing
It remains a challenge to provision resources in the cloud such that performance is maximized and financial cost is minimized. A fixed budget can be used to rent a wide variety of resource configurations for varying durations. The two steps - resource acquisition and scheduling/allocation - are dependent on each other and are particularly difficult when considering complex resource usage such as workflows, where task precedence need to be preserved and the budget constraint is assigned for the… 

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References

SHOWING 1-10 OF 24 REFERENCES

Auto-scaling to minimize cost and meet application deadlines in cloud workflows

  • Ming MaoM. Humphrey
  • Computer Science
    2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC)
  • 2011
This paper presents an approach whereby the basic computing elements are virtual machines (VMs) of various sizes/costs, jobs are specified as workflows, users specify performance requirements by assigning (soft) deadlines to jobs, and the goal is to ensure all jobs are finished within their deadlines at minimum financial cost.

Cost- and deadline-constrained provisioning for scientific workflow ensembles in IaaS clouds

It is found that the key factor determining the performance of an algorithm is its ability to decide which workflows in an ensemble to admit or reject for execution, and an admission procedure based on workflow structure and estimates of task runtimes can significantly improve the quality of solutions.

Cloud auto-scaling with deadline and budget constraints

This paper presents a cloud auto-scaling mechanism to automatically scale computing instances based on workload information and performance desire, and demonstrates that it can meet user specified performance goal with less cost.

Bag-of-Tasks Scheduling under Budget Constraints

  • Ana OprescuT. Kielmann
  • Computer Science
    2010 IEEE Second International Conference on Cloud Computing Technology and Science
  • 2010
The results show that BaTS is able to schedule within a user-defined budget (if such a schedule is possible at all), and significant cost savings can be achieved when comparing to a cost-oblivious round-robin scheduler.

Schedule optimization for data processing flows on the cloud

This paper studies scheduling of dataflows that involve arbitrary data processing operators in the context of three different problems and presents an approximate optimization framework to address them that uses resource elasticity in the cloud.

Cost-Optimal Scheduling in Hybrid IaaS Clouds for Deadline Constrained Workloads

This work analyzes and proposes a binary integer program formulation of the scheduling problem and finds that this approach results in a tractable solution for scheduling applications in the public cloud, but that the same method becomes much less feasible in a hybrid cloud setting due to very high solve time variances.

Scheduling Workflows with Budget Constraints

This paper considers a basic model for workflow applications modelled as Directed Acyclic Graphs (DAGs) and investigates heuristics that allow to schedule the nodes of the DAG (or tasks of a workflow) onto resources in a way that satisfies a budget constraint and is still optimized for overall time.

Cost-based scheduling of scientific workflow applications on utility grids

  • Jia YuR. BuyyaC. Tham
  • Computer Science
    First International Conference on e-Science and Grid Computing (e-Science'05)
  • 2005
This paper proposes a cost-based workflow scheduling algorithm that minimizes execution cost while meeting the deadline for delivering results and attempts to optimally solve the task scheduling problem in branches with several sequential tasks by modeling the branch as a Markov decision process and using the value iteration method.

A Multiple QoS Constrained Scheduling Strategy of Multiple Workflows for Cloud Computing

This paper introduces a Multiple QoS Constrained Scheduling Strategy of Multi-Workflows (MQMW) which can schedule multiple workflows which are started at any time and the QoS requirements are taken into account.

SLA-Based Resource Allocation for Software as a Service Provider (SaaS) in Cloud Computing Environments

  • Linlin WuS. GargR. Buyya
  • Computer Science
    2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
  • 2011
This paper proposes resource allocation algorithms for SaaS providers who want to minimize infrastructure cost and SLA violations, designed in a way to ensure that Saas providers are able to manage the dynamic change of customers, mapping customer requests to infrastructure level parameters and handling heterogeneity of Virtual Machines.