Name
Abstract | ||
|---|---|---|
Task scheduling in cloud computing is an NP-complete problem. It concerns how to properly arrange task execution process using a set of necessary cloud resources. Existing works assume that tasks can be interrupted without any overhead, based on which task schedules can be optimized to achieve some objectives (e.g., maximize resource utilization). We observe that interrupting tasks, as well as subsequent task recovery process, will inevitably impose overheads in terms of consuming additional CPU time on corresponding physical machines. In addition, not all tasks can be interrupted. Those observations motivate us to consider a more general scenario where a job consists of both interruptible and non-interruptible tasks with specific deadline and resource requirements. Accordingly, we design algorithms to minimize task interruption overhead while ensuring task completion deadline. Specifically, we first formulate an Integer Linear Program (ILP) for offline optimization. A heuristic algorithm is then proposed for online task scheduling, and is compared with the optimal ILP solution. Numerical results confirm the correctness of our ILP and show the efficiency of the proposed heuristic. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/CSCWD.2019.8791871 | 2019 IEEE 23rd International Conference on Computer Supported Cooperative Work in Design (CSCWD) |
Keywords | DocType | ISBN |
Cloud computing,cloud container service,task scheduling,interruption overhead | Conference | 978-1-7281-0351-8 |
Citations | PageRank | References |
0 | 0.34 | 11 |
Authors | ||
3 | ||