Proceedings of the 6th ACM International Workshop on Data Engineering for Wireless and Mobile Access 2007
DOI: 10.1145/1254850.1254854
|View full text |Cite
|
Sign up to set email alerts
|

Robust management of outliers in sensor network aggregate queries

Abstract: Sensor networks are increasingly applied for monitoring diverse environments and applications. Due to their unsupervised nature of operation and inexpensive hardware used, sensor nodes may furnish readings of rather poor quality. We thus need to devise techniques that can withstand "dirty" data during query processing. In this paper we introduce a robust aggregation framework that can detect and isolate spurious measurements from computed aggregate values. Such readings are not injected in the reported aggrega… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
25
0

Year Published

2009
2009
2011
2011

Publication Types

Select...
4
2
1

Relationship

2
5

Authors

Journals

citations
Cited by 15 publications
(25 citation statements)
references
References 30 publications
0
25
0
Order By: Relevance
“…In the context of streaming data, online filtering & smoothing of streaming tuples has become a hot topic [5][10] [11][15] [19]. Different from the focus of prior works on data accuracy and distribution estimation, our primary concern of cleaning streaming movement data is refining the data points that have substantial distortion of movement features for computing semantic trajectories 1 .…”
Section: Online Cleaningmentioning
confidence: 99%
See 2 more Smart Citations
“…In the context of streaming data, online filtering & smoothing of streaming tuples has become a hot topic [5][10] [11][15] [19]. Different from the focus of prior works on data accuracy and distribution estimation, our primary concern of cleaning streaming movement data is refining the data points that have substantial distortion of movement features for computing semantic trajectories 1 .…”
Section: Online Cleaningmentioning
confidence: 99%
“…The choice of scc is motivated by the fact that its stem, corr, possesses the ability to indicate the similarity of the trends that are profound in the examined vectors rather than relying on their absolute values [5][10][11] [19]. Hence, it provides an appropriate way to identify (dis)similar patterns in the complementary vectors and can be generalized in order to detect similar patterns between movement feature vectors in their entirety.…”
Section: Online Compressionmentioning
confidence: 99%
See 1 more Smart Citation
“…The authors [11] [24] propose an alternate reputation based approach which relies on reports from other nodes to detect anomalies. This method also reduces the chances of accepting and forwarding false data.…”
Section: Related Workmentioning
confidence: 99%
“…Our approach computes robust, or "meaningful", aggregates by identifying and excluding potentially "abnormal" readings. In our query processing model, introduced in our recent preliminary work [15], the sensor network propagates, in multiple hops towards the base station, the aggregate values, and also recognizes and reports a concise set of readings that are believed to be outliers, along with a set of characteristic values, i.e., witnesses, that have been used to derive the requested aggregates. In the current paper we build a comprehensive framework for identifying outliers and simultaneously computing in a resilient manner aggregate values in-network.…”
Section: Introductionmentioning
confidence: 99%