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Hashing Based Data Distribution in Heterogeneous Storage
Conference proceeding

Hashing Based Data Distribution in Heterogeneous Storage

Lin Su, Weiping Wang and Yong Chen
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings
IEEE International Conference on Big Data and Cloud Computing (BdCloud), 19 (New York, New York, USA, 09/30/2021–10/03/2021)
01/01/2021
DOI: 10.1109/ISPA-BDCloud-SocialCom-SustainCom52081.2021.00095

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Abstract

Conference Title: 2021 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom) Conference Start Date: 2021, Sept. 30 Conference End Date: 2021, Oct. 3 Conference Location: New York City, NY, USAStorage systems are important infrastructures of cloud computing in data centers. They demand the efficiency to distribute data and provide high I/O performance. The consistent hashing algorithm is widely used in modern storage systems due to its decentralized design, scalability, and adaptability to node changes. However, it lacks efficiency in a heterogeneous environment. In this study, we propose a Dynamically Attributed Consistent Hashing (DACH), to overcome this deficiency. DACH manages heterogeneous storage resources on consistent hashing ring and maintains multiple, dynamic attributes for nodes to characterize their distinct features. It places data on the ring and selects nodes with a balanced, weighted data distribution algorithm by taking full advantage of node attributes. By considering attribute variation, such as remaining capacity and workload changes, DACH can further optimize data layout. Extensive evaluation results show that, by well exploiting storage heterogeneity, DACH achieves adaptive and efficient data distribution for heterogeneous storage systems.
Big Data Cloud Computing Data centers Distributed processing Hash based algorithms Heterogeneity Nodes Storage systems

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