A New Data Placement Approach for Heterogeneous Ceph Storage System
- 2 Downloads
In the condition of heterogeneous Ceph storage cluster, the data distribution is imbalanced due to the pseudo-randomness of the CRUSH algorithm. In addition, the CRUSH algorithm only considers the nodes storage capacity to determine data storage location without considering the different ability of nodes in data processing, which will reduce the performance of cluster. A new data placement approach for heterogeneous Ceph storage system is proposed to solve these two problems. This proposed approach first adopts a multiple attribute decision-making model integrating the factors of storage capacity, CPU performance, memory size of each node, and then the probability weight of each heterogeneous node is determined by solving the proposed model to balance the data distribution. The result of series real-scene experiments shows that the proposed approach can not only improve the reading and writing performance and the fault tolerance but also make the data distribution more balanced.
KeywordsCeph Heterogeneous storage CRUSH Load balancing
The work presented in this paper has been supported by Special Program of Guangxi Science and Technology Base and Talents (2018AD19048) and Dean Project of Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education (CRKL150109).
- 1.Ren, J.S., Wang, J.L., Cheng, X., et al.: Provable multi copy dynamic data possession in cloud storage. J. Xidian Univ. 44(6), 156–161 (2017)Google Scholar
- 2.Toosi, A.N., Buyya, R.: A fuzzy logic-based controller for cost and energy efficient load balancing in geo-distributed data centers. In: Proceedings of 2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing, pp. 186–194 (2016)Google Scholar
- 3.Huang, W.H., Ma, Z., Dai, X.F., et al.: A load-balancing Algorithm for weighted fuzzy clustering. J. Xidian Univ. 44(2), 127–132 (2017)Google Scholar
- 4.Han, Y.J., Lee, K., Park, S.Y.: A dynamic message-aware communication scheduler for Ceph storage system. In: Proceedings of the 2016 IEEE 1st International Workshops on Foundations and Applications of Self-Systems, pp. 60–65 (2016)Google Scholar
- 5.Sha, H., Liang, Y., Jiang, W.W., et al.: Optimizing data placement of map reduce on Ceph based framework under load-balancing constraint. In: Proceedings of the IEEE International Conference on Parallel and Distributed Systems, pp. 585–592 (2017)Google Scholar
- 6.Meyer, S., Morrison, J.P.: Supporting heterogeneous pools in a single Ceph storage cluster. In: Proceedings of the 17th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, pp. 352–359 (2016)Google Scholar
- 7.Cheng, W., Chiang, C., Yang, C., et al.: The implementation of supporting uniform data distribution with software-defined storage service on heterogeneous cloud storage. In: Proceedings of the 2016 IEEE 22nd International Conference on Parallel and Distributed Systems, pp. 610–615 (2017)Google Scholar