Profit-driven scheduling for cloud services with data access awareness
Journal of Parallel and Distributed Computing
How to price shared optimizations in the cloud
Proceedings of the VLDB Endowment
VM: placement in non-Homogeneous Iaas-clouds
ICSOC'11 Proceedings of the 9th international conference on Service-Oriented Computing
TIRAMOLA: elastic nosql provisioning through a cloud management platform
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Estimating resource costs of data-intensive workloads in public clouds
Proceedings of the 10th International Workshop on Middleware for Grids, Clouds and e-Science
Provisioning data analytic workloads in a cloud
Future Generation Computer Systems
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Modern frameworks, such as Hadoop, combined with abundance of computing resources from the cloud, offer a significant opportunity to address long standing challenges in distributed processing. Infrastructure-as-a-Service clouds reduce the investment cost of renting a large data center while distributed processing frameworks are capable of efficiently harvesting the rented physical resources. Yet, the performance users get out of these resources varies greatly because the cloud hardware is shared by all users. The value for money cloud consumers achieve renders resource sharing policies a key player in both cloud performance and user satisfaction. In this paper, we employ microeconomics to direct the allotment of cloud resources for consumption in highly scalable master-worker virtual infrastructures. Our approach is developed on two premises: the cloud-consumer always has a budget and cloud physical resources are limited. Using our approach, the cloud administration is able to maximize per-user financial profit. We show that there is an equilibrium point at which our method achieves resource sharing proportional to each user's budget. Ultimately, this approach allows us to answer the question of how many resources a consumer should request from the seemingly endless pool provided by the cloud.