|Authors||N. Mohebi and F. Zahid|
|Title||Towards Realistic Simulations of Arbitrary Cross-Cloud Workloads|
|Project(s)||MELODIC: Multi-cloud Execution-ware for Large-scale Optimised Data-Intensive Computing|
|Publication Type||Proceedings, refereed|
|Year of Publication||2019|
|Conference Name||The International Workshop on Recent Advances for Multi-Clouds and Mobile Edge Computing (M2EC) held in conjunction with 33rd International Conference on Advanced Information Networking and Applications (AINA 2019)|
Over the last few years, Cloud computing has established itself as a popular computing paradigm. Thanks to the ease of deployments, elastic resource provisioning, high-availability, and an attractive pay-as-you-go economic model, clouds offer significant advantages over traditional cluster computing architectures. More recently, Multi-Cloud solutions have also been explored to take advantage of the most suitable public cloud offerings as well as to tackle vendor lock-in.
The research undertakings in cloud often require designing new algorithms, techniques, and solutions requiring large-scale cloud deployments for comprehensive evaluation. Simulations make a powerful and cost-effective tool for testing, evaluation, and repeated experimentation for new cloud algorithms. Unfortunately, even though cloud federation and hybrid cloud simulations are explored in the literature, Cross-Cloud simulations are still largely an unsupported feature in most popular cloud simulation frameworks. In this paper, we present a Cross-Cloud simulation framework, which makes it possible to test scheduling and reasoning algorithms on Cross-Cloud deployments with arbitrary workload. The support of Cross-Cloud simulations, where individual application components are allowed to be deployed on different cloud platforms, can be a valuable asset in selecting appropriate mixture of cloud services for the applications. We also implement a Cross-Cloud aware reasoner using our Cross-Cloud simulation framework. Simulations using both simple applications and complex multi-stage workflows show that the Cross-Cloud aware reasoner can substantially save cloud usage costs for most multi-component cloud applications.