Research Article
A Log-Based Anomaly Detection Method with Efficient Neighbor Searching and Automatic K Neighbor Selection
Algorithm 2
The neighbor searching algorithm of MVP-tree.
| | Require: The sample to be detected , the distance threshold r | | | Ensure: The nearest sample | | (1) | function QueryTree | | (2) | Compute , | | (3) | ifthen return | | (4) | end if | | (5) | ifthen return | | (6) | end if | | (7) | For the leaf tree nodes, goto (8), for the intermediate tree nodes, goto (16) | | (8) | fordo | | (9) | if and then | | (10) | if, then | | (11) | ifthen return | | (12) | end if | | (13) | end if | | (14) | end if | | (15) | end for | | (16) | ifthen | | (17) | | | (18) | end if | | (19) | ifthen | | (20) | | | (21) | end if | | (22) | ifthen | | (23) | ifthen | | (24) | , goto (23) for recursion | | (25) | end if | | (26) | ifthen | | (27) | , goto (26) for recursion | | (28) | end if | | (29) | end if | | (30) | ifthen | | (31) | ifthen | | (32) | , goto (31) for recursion | | (33) | end if | | (34) | ifthen | | (35) | , goto (34) for recursion | | (36) | end if | | (37) | end if | | (38) | end function |
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