Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter
}
TY - CHAP
T1 - MPM
T2 - Map based Predictive Monitoring for Wireless Sensor Networks
AU - Ali, A.
AU - Khelil, A.
AU - Shaikh, F.K.
AU - Suri, Neeraj
PY - 2010
Y1 - 2010
N2 - We present the design of a Wireless Sensor Networks (WSN) level event prediction framework to monitor the network and its operational environment to support proactive self* actions. For example, by monitoring and subsequently predicting trends on network load or sensor nodes energy levels, theWSN can proactively initiate self-reconfiguration. We propose a Map based Predictive Monitoring (MPM) approach where a selected WSN attribute is first profiled as WSN maps, and based on the maps history, predicts future maps using time series modeling. The "attribute" maps are created using a gridding technique and predicted maps are used to detect events using our regioning algorithm. The proposed approach is also a general framework to cover multiple application domains. For proof of concept, we show MPM's enhanced ability to also accurately "predict" the network partitioning, accommodating parameters such as shape and location of the partition with a very high accuracy and efficiency. © Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering 2010.
AB - We present the design of a Wireless Sensor Networks (WSN) level event prediction framework to monitor the network and its operational environment to support proactive self* actions. For example, by monitoring and subsequently predicting trends on network load or sensor nodes energy levels, theWSN can proactively initiate self-reconfiguration. We propose a Map based Predictive Monitoring (MPM) approach where a selected WSN attribute is first profiled as WSN maps, and based on the maps history, predicts future maps using time series modeling. The "attribute" maps are created using a gridding technique and predicted maps are used to detect events using our regioning algorithm. The proposed approach is also a general framework to cover multiple application domains. For proof of concept, we show MPM's enhanced ability to also accurately "predict" the network partitioning, accommodating parameters such as shape and location of the partition with a very high accuracy and efficiency. © Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering 2010.
KW - Event prediction
KW - Predicitve Monitoring
KW - Time series analysis
KW - Wireless Sensor Networks
KW - Gridding
KW - Multiple applications
KW - Network load
KW - Network partitioning
KW - Operational environments
KW - Predictive monitoring
KW - Proof of concept
KW - Self reconfiguration
KW - Time series modeling
KW - Forecasting
KW - Sensor nodes
KW - Sensors
KW - Telecommunication equipment
KW - Time series
KW - Wireless networks
U2 - 10.1007/978-3-642-11482-3_6
DO - 10.1007/978-3-642-11482-3_6
M3 - Chapter
SN - 3642114814
SN - 9783642114816
VL - 23 LNICST
SP - 79
EP - 95
BT - Autonomic Computing and Communications Systems
PB - Springer
ER -