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Facilitating Application-Aware Bandwidth Allocation in the Cloud with One-Step-Ahead Traffic Information

Journal Article


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Abstract


  • 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% and the global traffic by 36.7%, compared to the state-of-the-art methods.

Authors


  •   Shen, Dian (external author)
  •   Luo, Junzhou (external author)
  •   Dong, Fang (external author)
  •   Jin, Jiahui (external author)
  •   Zhang, Junxue (external author)
  •   Shen, Jun

Publication Date


  • 2019

Citation


  • Shen, D., Luo, J., Dong, F., Jin, J., Zhang, J. & Shen, J. (2019). Facilitating Application-Aware Bandwidth Allocation in the Cloud with One-Step-Ahead Traffic Information. IEEE Transactions on Services Computing, online first

Ro Full-text Url


  • https://ro.uow.edu.au/cgi/viewcontent.cgi?article=4745&context=eispapers1

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/3719

Volume


  • online first

Place Of Publication


  • United States

Abstract


  • 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% and the global traffic by 36.7%, compared to the state-of-the-art methods.

Authors


  •   Shen, Dian (external author)
  •   Luo, Junzhou (external author)
  •   Dong, Fang (external author)
  •   Jin, Jiahui (external author)
  •   Zhang, Junxue (external author)
  •   Shen, Jun

Publication Date


  • 2019

Citation


  • Shen, D., Luo, J., Dong, F., Jin, J., Zhang, J. & Shen, J. (2019). Facilitating Application-Aware Bandwidth Allocation in the Cloud with One-Step-Ahead Traffic Information. IEEE Transactions on Services Computing, online first

Ro Full-text Url


  • https://ro.uow.edu.au/cgi/viewcontent.cgi?article=4745&context=eispapers1

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/3719

Volume


  • online first

Place Of Publication


  • United States