Collection trees for event-monitoring queries

In this paper we present algorithms for building and maintaining efficient collection trees that provide the conduit to disseminate data required for processing monitoring queries in a wireless sensor network. While prior techniques base their operation on the assumption that the sensor nodes that collect data relevant to a specified query need to include their measurements in the query result at every query epoch, in many event monitoring applications such an assumption is not valid. We introduce and formalize the notion of event monitoring queries and demonstrate that they can capture a large class of monitoring applications. We then show techniques which, using a small set of intuitive statistics, can compute collection trees that minimize important resources such as the number of messages exchanged among the nodes or the overall energy consumption. Our experiments demonstrate that our techniques can organize the data collection process while utilizing significantly lower resources than prior approaches.

[1]  Alex Delis,et al.  Another Outlier Bites the Dust: Computing Meaningful Aggregates in Sensor Networks , 2009, 2009 IEEE 25th International Conference on Data Engineering.

[2]  Gustavo Alonso,et al.  Declarative Support for Sensor Data Cleaning , 2006, Pervasive.

[3]  Wei Hong,et al.  The design of an acquisitional query processor for sensor networks , 2003, SIGMOD '03.

[4]  Daniel J. Abadi,et al.  REED: Robust, Efficient Filtering and Event Detection in Sensor Networks , 2005, VLDB.

[5]  Yong Yao,et al.  The cougar approach to in-network query processing in sensor networks , 2002, SGMD.

[6]  Minos N. Garofalakis,et al.  Adaptive cleaning for RFID data streams , 2006, VLDB.

[7]  Wei Hong,et al.  Proceedings of the 5th Symposium on Operating Systems Design and Implementation Tag: a Tiny Aggregation Service for Ad-hoc Sensor Networks , 2022 .

[8]  Jeffrey Considine,et al.  Approximate aggregation techniques for sensor databases , 2004, Proceedings. 20th International Conference on Data Engineering.

[9]  Yannis Kotidis.  Processing proximity queries in sensor networks , 2006, DMSN '06.

[10]  Rajmohan Rajaraman,et al.  The Cougar Project: a work-in-progress report , 2003, SGMD.

[11]  Rajmohan Rajaraman,et al.  Multi-query Optimization for Sensor Networks , 2005, DCOSS.

[12]  Deborah Estrin,et al.  ASCENT: Adaptive Self-Configuring sEnsor Networks Topologies , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[13]  Johannes Gehrke,et al.  Gossip-based computation of aggregate information , 2003, 44th Annual IEEE Symposium on Foundations of Computer Science, 2003. Proceedings..

[14]  Ramesh Govindan,et al.  The impact of spatial correlation on routing with compression in wireless sensor networks , 2008, TOSN.

[15]  Michael F. Worboys,et al.  Monitoring dynamic spatial fields using responsive geosensor networks , 2005, GIS '05.

[16]  Mohamed A. Sharaf,et al.  Balancing energy efficiency and quality of aggregate data in sensor networks , 2004, The VLDB Journal.

[17]  Leandros Tassiulas,et al.  Energy conserving routing in wireless ad-hoc networks , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[18]  Deborah Estrin,et al.  Impact of network density on data aggregation in wireless sensor networks , 2002, Proceedings 22nd International Conference on Distributed Computing Systems.

[19]  Wei Hong,et al.  Model-Driven Data Acquisition in Sensor Networks , 2004, VLDB.

[20]  Mani Srivastava,et al.  Energy-aware wireless microsensor networks , 2002, IEEE Signal Process. Mag..

[21]  Jennifer Widom,et al.  Offering a Precision-Performance Tradeoff for Aggregation Queries over Replicated Data , 2000, VLDB.

[22]  Satish Kumar,et al.  Next century challenges: scalable coordination in sensor networks , 1999, MobiCom.

[23]  Yannis Theodoridis,et al.  TACO: tunable approximate computation of outliers in wireless sensor networks , 2010, SIGMOD Conference.

[24]  Dimitrios Gunopulos,et al.  Online outlier detection in sensor data using non-parametric models , 2006, VLDB.

[25]  Prasant Mohapatra,et al.  Medium access control in wireless sensor networks , 2007, Comput. Networks.

[26]  M -.  Estimating Aggregates on a Peer-to-Peer Network , 2003 .

[27]  Yunhao Liu,et al.  Contour map matching for event detection in sensor networks , 2006, SIGMOD Conference.

[28]  Alex Delis,et al.  Robust management of outliers in sensor network aggregate queries , 2007, MobiDE '07.

[29]  Andreas Pitsillides,et al.  The MicroPulse Framework for Adaptive Waking Windows in Sensor Networks , 2007, 2007 International Conference on Mobile Data Management.

[30]  Julius T. Tou,et al.  Information Systems , 1973, GI Jahrestagung.

[31]  Nick Roussopoulos,et al.  Hierarchical In-Network Data Aggregation with Quality Guarantees , 2004, EDBT.

[32]  S. M. Heemstra de Groot,et al.  Power-aware routing in mobile ad hoc networks , 1998, MobiCom '98.

[33]  Nick Roussopoulos,et al.  Dissemination of compressed historical information in sensor networks , 2007, The VLDB Journal.

[34]  Yannis Kotidis,et al.  Snapshot queries: towards data-centric sensor networks , 2005, 21st International Conference on Data Engineering (ICDE'05).

[35]  Jun Yang,et al.  Constraint chaining: on energy-efficient continuous monitoring in sensor networks , 2006, SIGMOD Conference.

[36]  Jie Gao,et al.  Sparse Data Aggregation in Sensor Networks , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.