Deadline-Aware Deployment for Time Critical Applications in Clouds
| Authors | |
|---|---|
| Publication date | 2017 |
| Host editors |
|
| Book title | Euro-Par 2017: Parallel Processing |
| Book subtitle | 23rd International Conference on Parallel and Distributed Computing, Santiago de Compostela, Spain, August 28-September 1, 2017 : proceedings |
| ISBN |
|
| ISBN (electronic) |
|
| Series | Lecture Notes in Computer Science |
| Event | 23rd International Conference on Parallel and Distributed Computing |
| Pages (from-to) | 345-357 |
| Number of pages | 13 |
| Publisher | Cham: Springer |
| Organisations |
|
| Abstract |
Time critical applications are appealing to deploy in clouds due to the elasticity of cloud resources and their on-demand nature. However, support for deploying application components with strict deadlines on their deployment is lacking in current cloud providers. This is particularly important for adaptive applications that must automatically and seamlessly scale, migrate, or recover swiftly from failures. A common deployment procedure is to transmit application packages from the application provider to the cloud, and install the application there. Thus, users need to manually deploy their applications into clouds step by step with no guarantee regarding deadlines. In this work, we propose a Deadline-aware Deployment System (DDS) for time critical applications in clouds. DDS enables users to automatically deploy applications into clouds. We design bandwidth-aware EDF scheduling algorithms in DDS that minimize the number of deployments that miss their deadlines and maximize the utilization of network bandwidth. In the evaluation, we show that DDS leverages network bandwidth sufficiently, and significantly reduces the number of missed deadlines during deployment.
|
| Document type | Conference contribution |
| Language | English |
| Published at | https://doi.org/10.1007/978-3-319-64203-1_25 |
| Permalink to this page | |
