会议论文

Tian, WL

英文

IEEE International Conference on Performance, Computing, and Communications

1097-2641

2022

2022-November

374-379

IEEE International Performance, Computing, and Communications Conference (IPCCC)

IEEE International Performance Computing and Communications Conference (IPCCC)

NOV 11-13, 2022

Austin, TX

[Li, Baisong;Tian, Wenlong;Fu, Zhongming;Ye, Xuming;Duan, Renjiao;Li, Yusheng] Univ South China, Sch Comp Sci & Technol, Hengyang, Peoples R China.^[Tian, Wenlong] Nanyang Technol Univ, Sch Phys & Math Sci, Singapore, Singapore.^[Tian, Wenlong;Fu, Zhongming] Hunan Prov Base Sci & Technol Innovat Cooperat, Hengyang, Peoples R China.^[Li, Ruixuan] Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan, Peoples R China.^[Xiao, Weijun] Virginia Commonwealth Univ, Elect & Comp Engn, Richmond, VA USA.^[Xu, Zhiyong] Suffolk Univ, Math & Comp Sci Dept, Boston, MA USA.^[Xu, Zhiyong] Chinese Acad Sci, Shenzhen Inst Adv Technol, Beijing, Peoples R China.

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

978-1-6654-8018-5

10.1109/IPCCC55026.2022.9894349

State Scholarship Fund of China; National Natural Science Foundation of China [U1836204]; Natural Science Foundation of Hunan Province of China [2021JJ40468, 2022JJ30495]; National Training Program of Innovation and Entrepreneurship for Undergraduates [202110555052, S202110555215]

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Recently, cloud storage has been widely used in our daily life. And there are lots of redundancy among these outsourced data. Conventional deduplication technology efficiently splits these data at the chunk level and removes the duplicate chunks to save the network bandwidth and improve the cloud storage utility. But it ignores the redundancy among similar chunks. Resemblance detection has recently become a hot issue with detecting these redundant parts among similar data. CARD, the state-of-the-art work, can efficiently and effectively remove ...