TY - GEN
T1 - Visualizing anomalies in sensor networks
AU - Liao, Qi
AU - Shi, Lei
AU - He, Yuan
AU - Li, Rui
AU - Su, Zhong
AU - Striegel, Aaron
AU - Liu, Yunhao
PY - 2011
Y1 - 2011
N2 - Diagnosing a large-scale sensor network is a crucial but challenging task due to the spatiotemporally dynamic network behaviors of sensor nodes. In this demo, we present Sensor Anomaly Visualization Engine (SAVE), an integrated system that tackles the sensor network diagnosis problem using both visualization and anomaly detection analytics to guide the user quickly and accurately diagnose sensor network failures. Temporal expansion model, correlation graphs and dynamic projection views are proposed to effectively interpret the topological, correlational and dimensional sensor data dynamics and their anomalies. Through a real-world large-scale wireless sensor network deployment (GreenOrbs), we demonstrate that SAVE is able to help better locate the problem and further identify the root cause of major sensor network failures.
AB - Diagnosing a large-scale sensor network is a crucial but challenging task due to the spatiotemporally dynamic network behaviors of sensor nodes. In this demo, we present Sensor Anomaly Visualization Engine (SAVE), an integrated system that tackles the sensor network diagnosis problem using both visualization and anomaly detection analytics to guide the user quickly and accurately diagnose sensor network failures. Temporal expansion model, correlation graphs and dynamic projection views are proposed to effectively interpret the topological, correlational and dimensional sensor data dynamics and their anomalies. Through a real-world large-scale wireless sensor network deployment (GreenOrbs), we demonstrate that SAVE is able to help better locate the problem and further identify the root cause of major sensor network failures.
KW - Anomaly detection and analysis
KW - Diagnosing
KW - Visualization
KW - Wireless sensor networks
UR - http://www.scopus.com/inward/record.url?scp=80053168891&partnerID=8YFLogxK
U2 - 10.1145/2018436.2018521
DO - 10.1145/2018436.2018521
M3 - Conference contribution
AN - SCOPUS:80053168891
SN - 9781450307970
T3 - Proceedings of the ACM SIGCOMM 2011 Conference, SIGCOMM'11
SP - 460
EP - 461
BT - Proceedings of the ACM SIGCOMM 2011 Conference, SIGCOMM'11
PB - Association for Computing Machinery
ER -