The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 02, 2020

Filed:

Apr. 17, 2018
Applicant:

Kangwon National University University-industry Cooperation Foundation, Gangwon-do, KR;

Inventors:

Ha Jin Kim, Gangwon-do, KR;

Myeong Seon Gil, Gangwon-do, KR;

Yang Sae Moon, Gangwon-do, KR;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 12/28 (2006.01); H04L 12/807 (2013.01); H04L 12/879 (2013.01); G06F 7/58 (2006.01); G06F 17/18 (2006.01); G06F 16/2455 (2019.01); H04L 12/26 (2006.01);
U.S. Cl.
CPC ...
H04L 47/27 (2013.01); G06F 7/58 (2013.01); G06F 16/24568 (2019.01); G06F 17/18 (2013.01); H04L 43/00 (2013.01); H04L 49/901 (2013.01);
Abstract

Disclosed is a variable-size sampling method under a data-streaming environment, including: calculating a maximum window size that satisfies a lower limitation of a predetermined uniformity confidence level at all times; inputting a data stream to be sampled; comparing a data stream length input until a current time point with the maximum window size; inspecting a sample size and a sampling fraction if the maximum window size is larger than the data stream length; performing sampling by generating a slot to increase the sample size if the current sample size is smaller than a predetermined percentage (P %) of the data stream; and directly performing sampling without generating a slot if the current sample size is equal to or larger than the predetermined percentage (P %) of the data stream. As a result, degradation of uniformity confidence during variable-size sampling under a real-time streaming environment can be prevented to improve sampling performance.


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