Multi-dimensional Resource Allocation for Data-intensive Large-scale Cloud Applications

@inproceedings{Jrad2014MultidimensionalRA,
  title={Multi-dimensional Resource Allocation for Data-intensive Large-scale Cloud Applications},
  author={Foued Jrad and Jie Tao and Ivona Brandi{\'c} and Achim Streit},
  booktitle={International Conference on Cloud Computing and Services Science},
  year={2014}
}
Large scale applications are emerged as one of the important applications in distributed computing. Today, the economic and technical benefits offered by the Cloud computing technology encouraged many users to migrate their applications to Cloud. On the other hand, the variety of the existing Clouds requires them to make decisions about which providers to choose in order to achieve the expected performance and service quality while keeping the payment low. In this paper, we present a multi… 

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References

SHOWING 1-10 OF 21 REFERENCES

Managing Data-Intensive Workloads in a Cloud

A taxonomy is presented for workload management of data-intensive computing in the cloud and use the taxonomy to classify and evaluate current workload management mechanisms.

QoS-aware Deployment of Network of Virtual Appliances Across Multiple Clouds

Two different deployment approaches are proposed and compared: Forward-checking-based backtracking (FCBB) and genetic-based, which take into account Quality of Service (QoS) criteria such as reliability, data communication cost, and latency between multiple Clouds to choose the most appropriate combination of virtual machines and appliances.

A broker-based framework for multi-cloud workflows

A broker-based framework for running workflows in a multi-Cloud environment that allows an automatic selection of the target Clouds, a uniform access to the Clouds, and workflow data management with respect to user Service Level Agreement (SLA) requirements is presented.

BAR: An Efficient Data Locality Driven Task Scheduling Algorithm for Cloud Computing

A heuristic task scheduling algorithm called Balance-Reduce (BAR), in which an initial task allocation will be produced at first, then the job completion time can be reduced gradually by tuning the initial task allocated, by taking a global view.

CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms

The result of this case study proves that the federated Cloud computing model significantly improves the application QoS requirements under fluctuating resource and service demand patterns.

A Multi-objective Approach for Workflow Scheduling in Heterogeneous Environments

This paper proposes a general framework and heuristic algorithm for multi-objective static scheduling of scientific workflows in heterogeneous computing environments and demonstrates that the solutions generated by the algorithm are superior to user-defined constraints most of the time.

A data placement strategy in scientific cloud workflows

A utility-based approach for customised cloud service selection

This work developed a broker-based framework capable of automatically selecting cloud services based on user-defined requirement parameters and the service level agreement (SLA) attributes of the cloud providers.

Scheduling resources in multi-user, heterogeneous, computing environments with SmartNet

The SmartNet resource scheduling system is described and compared to two different resource allocation strategies: load balancing and user directed assignment, and results indicate that, for the computer environments simulated, SmartNet outperforms both load balancingand user directed assignments, based on the maximum time users must wait for their tasks to finish.

A Truthful Dynamic Workflow Scheduling Mechanism for Commercial Multicloud Environments

A pricing model and a truthful mechanism for scheduling single tasks considering two objectives: monetary cost and completion time are introduced and extended for dynamic scheduling of scientific workflows.