Work

Accelerating content-defined-chunking based data deduplication by exploiting parallelism

Year: 2019

Type: article

Source: Future Generation Computer Systems

DOI: 10.1016/j.future.2019.02.008

Authors: Wen Xia, Dan Feng, Hong Jiang, Yucheng Zhang, Victor Chang, Xiangyu Zou

Institutions: Harbin Institute of Technology, Peng Cheng Laboratory, Huazhong University of Science and Technology, The University of Texas at Arlington, Xi’an Jiaotong-Liverpool University

Language: English

Topic: Advanced Data Storage Technologies

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, U.S. Department of Defense, Hubei Provincial Department of Education, National Natural Science Foundation of China, National Key Research and Development Program of China

Awards: 基于深度学习的非结构化大数据分析算法研究, G158411212, G1799421016, G2184068523, G2352326796, G2413230818, G5539248298, G5771665477, SHF: Medium: WHOLEPRO: An Online, Holistic Job Scheduling and Resource Provisioning Framework for Datacenter Architectures and Applications, 可证明安全的程序混淆关键技术研究, XPS:FULL: MSLO-JS: Towards Multi-SLO-Guaranteed per-Job Scheduling in Datacenters

OpenAlex ID: W2935106878

FWCI: 2.643

Cites: 65

Cited by: 40

Related to: 10