Resource usage prediction of cloud workloads using deep bidirectional long short term memory networks

@article{Gupta2017ResourceUP,
  title={Resource usage prediction of cloud workloads using deep bidirectional long short term memory networks},
  author={Shaifu Gupta and Dileep Aroor Dinesh},
  journal={2017 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)},
  year={2017},
  pages={1-6}
}
Resource usage prediction is an important aspect for achieving optimal resource provisioning in cloud. The presence of long range dependence in cloud workloads makes conventional time series resource usage prediction models unsuitable for prediction. In this paper, we proposed to use multivariate long short term memory (LSTM) models for prediction of resource usage in cloud workloads. We analyze and compare the predictions of LSTM model and bidirectional LSTM model with fractional difference… CONTINUE READING

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