Facilitating Application-Aware Bandwidth Allocation in the Cloud with One-Step-Ahead Traffic Information
- Publisher:
- Institute of Electrical and Electronics Engineers
- Publication Type:
- Journal Article
- Citation:
- IEEE Transactions on Services Computing, 2020, 13, (2), pp. 381-394
- Issue Date:
- 2020-03-01
Closed Access
Filename | Description | Size | |||
---|---|---|---|---|---|
08734778.pdf | Published version | 2.71 MB |
Copyright Clearance Process
- Recently Added
- In Progress
- Closed Access
This item is closed access and not available.
© 2008-2012 IEEE. Bandwidth allocation to virtual machines (VMs) has a significant impact on the performance of communication-intensive big data applications hosted in VMs. It is crucial to accurately determine how much bandwidth to be reserved for VMs and when to adjust it. Past approaches typically resort to predicting the long-term network demands of applications for bandwidth allocation. However, lacking of prediction accuracy, these methods lead to the unpredictable application performance. Recently, it is conceded that the network demands of applications can only be accurately derived right before each of their execution phases. Hence, it is challenging to timely allocate the bandwidth to VMs with limited information. In this paper, we design and implement AppBag, an Application-aware Bandwidth guarantee framework, which allocates the accurate bandwidth to VMs with one-step-ahead traffic information. We propose an algorithm to allocate the bandwidth to VMs and map them onto feasible hosts. To reduce the overhead when adjusting the allocation, an efficient Lazy Migration (LM) algorithm is proposed with bounded performance. We conduct extensive evaluations using real-world applications, showing that AppBag can handle the bandwidth requests at run-time, while reducing the execution time of applications by 47.3 percent and the global traffic by 36.7 percent, compared to the state-of-the-art methods.
Please use this identifier to cite or link to this item: