The Anonymization Protection Algorithm Based on Fuzzy Clustering for the Ego of Data in the Internet of Things

Algorithm 2

Sampling time clustering algorithm.

  Input: ′, TST and ;

  Output: Substgrp; % the set of equivalent class

  BEGIN

 (1) Substgrp = ;

 (2) FOR each r in ′

 (3)  ;

 (4)  if then

 (5) Substgrp =

 % The set of equivalence classes with sampling interval of is

obtained. denotes the data subset whose intercept is , namely, an

equivalent class. The function of is that the number of the th equivalent class

would be counted out. denotes the th subset, namely, the

th equivalent class. It is asked that the data for each equivalence class contains at least 2 nodes.

The function of is that the number of th equivalent class. In this

paper, .

represents that the union of all subsets, namely the union of all equivalence classes. The

function is that total number of equivalence classes whose intercept is is

calculated. The maximum number of records would be covered in an equivalence class. We should

choose the set of equivalence classes which can cover the maximum number of records.

 (6)  ENDIF

 (7) ENDFOR

 END