Host load prediction with long short-term memory in cloud computing.
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| Title: | Host load prediction with long short-term memory in cloud computing. |
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| Authors: | Song, Binbin1, Yu, Yao1, Zhou, Yu1, Wang, Ziqiang1, Du, Sidan1 |
| Source: | Journal of Supercomputing. Dec2018, Vol. 74 Issue 12, p6554-6568. 15p. |
| Subjects: | Workload of computer networks, Cloud computing, Prediction models, Data distribution, Network performance |
| Abstract: | Host load prediction is significant for improving resource allocation and utilization in cloud computing. Due to the higher variance than that in a grid, accurate prediction remains a challenge in the cloud system. In this paper, we apply a concise yet adaptive and powerful model called long short-term memory to predict the mean load over consecutive future time intervals and actual load multi-step-ahead. Two real-world load traces were used to evaluate the performance. One is the load trace in the Google data center, and the other is that in a traditional distributed system. The experiment results show that our proposed method achieves state-of-the-art performance with higher accuracy in both datasets. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Host load prediction is significant for improving resource allocation and utilization in cloud computing. Due to the higher variance than that in a grid, accurate prediction remains a challenge in the cloud system. In this paper, we apply a concise yet adaptive and powerful model called long short-term memory to predict the mean load over consecutive future time intervals and actual load multi-step-ahead. Two real-world load traces were used to evaluate the performance. One is the load trace in the Google data center, and the other is that in a traditional distributed system. The experiment results show that our proposed method achieves state-of-the-art performance with higher accuracy in both datasets. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 09208542 |
| DOI: | 10.1007/s11227-017-2044-4 |
