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PTAOD: A Novel Framework For Supporting Approximate Outlier Detection over Streaming Data for Edge Computing

Zhu, Rui; Yu, Tiantian; Tan, Zhiyuan; Du, Wei; Zhao, Liang; Li, Jiajia; Xia, Xiufeng


Rui Zhu

Tiantian Yu

Wei Du

Liang Zhao

Jiajia Li

Xiufeng Xia


Outlier detection over sliding window is a fundamental problem in the domain of streaming data management, which has been studied over 10 years. The key of supporting outlier detection is to construct a neighbour-list for each object. It is used for predicting which objects may become outliers or are impossible to become outliers. However, existing work ignores the fact that, outliers amount is usually small. It is unnecessary to construct neighbour-list for all objects when they arrive in the window. It causes both high space and computational cost, can not efficiently work under edge computation environment. In this paper, we propose a novel framework named PTAOD (Probabilistic Threshold-based Approximate Outlier Detection). Firstly, we propose an algorithm for evaluating the probability of a newly arrived object becoming an outlier before it expires from the window, using evaluating result for avoiding unnecessary computational cost. In addition, we introduce a novel index namely ZHB-Tree (Z-order-based Hash BTree) to maintain streaming data. Last of all, we propose a novel algorithm to maintain candidate outliers. Theoretical analysis and extensive experimental results demonstrate the effectiveness of the proposed algorithms


Zhu, R., Yu, T., Tan, Z., Du, W., Zhao, L., Li, J., & Xia, X. (2020). PTAOD: A Novel Framework For Supporting Approximate Outlier Detection over Streaming Data for Edge Computing. IEEE Access, 8, 1475-1485.

Journal Article Type Article
Acceptance Date Dec 15, 2019
Online Publication Date Dec 24, 2019
Publication Date 2020
Deposit Date Dec 25, 2019
Publicly Available Date Jan 7, 2020
Journal IEEE Access
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 8
Pages 1475-1485
Keywords Data systems, Distributed computing, Data flow computing
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PTAOD: A Novel Framework For Supporting Approximate Outlier Detection Over Streaming Data For Edge Computing (20.3 Mb)

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This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see

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