Synopsis diffusion for robust aggregation in sensor networks

Previous approaches for computing duplicate-sensitive aggregates in wireless sensor networks have used a tree topology, in order to conserve energy and to avoid double-counting sensor readings. However, a tree topology is not robust against node and communication failures, which are common in sensor networks. In this article, we present synopsis diffusion, a general framework for achieving significantly more accurate and reliable answers by combining energy-efficient multipath routing schemes with techniques that avoid double-counting. Synopsis diffusion avoids double-counting through the use of order- and duplicate-insensitive (ODI) synopses that compactly summarize intermediate results during in-network aggregation. We provide a surprisingly simple test that makes it easy to check the correctness of an ODI synopsis. We show that the properties of ODI synopses and synopsis diffusion create implicit acknowledgments of packet delivery. Such acknowledgments enable energy-efficient adaptation of message routes to dynamic message loss conditions, even in the presence of asymmetric links. Finally, we illustrate using extensive simulations the significant robustness, accuracy, and energy-efficiency improvements of synopsis diffusion over previous approaches.

[1]  Philippe Flajolet,et al.  Probabilistic Counting Algorithms for Data Base Applications , 1985, J. Comput. Syst. Sci..

[2]  Brian A. Davey,et al.  An Introduction to Lattices and Order , 1989 .

[3]  David A. Maltz,et al.  Dynamic Source Routing in Ad Hoc Wireless Networks , 1994, Mobidata.

[4]  Yossi Matias,et al.  DIMACS Series in Discrete Mathematicsand Theoretical Computer Science Synopsis Data Structures for Massive Data , 2007 .

[5]  Noga Alon,et al.  The Space Complexity of Approximating the Frequency Moments , 1999 .

[6]  Deborah Estrin,et al.  Directed diffusion: a scalable and robust communication paradigm for sensor networks , 2000, MobiCom '00.

[7]  Richard M. Karp,et al.  Randomized rumor spreading , 2000, Proceedings 41st Annual Symposium on Foundations of Computer Science.

[8]  Ravi Kumar,et al.  Sampling algorithms: lower bounds and applications , 2001, STOC '01.

[9]  Philippe Bonnet,et al.  Towards Sensor Database Systems , 2001, Mobile Data Management.

[10]  Kenneth P. Birman,et al.  A gossip protocol for subgroup multicast , 2001, Proceedings 21st International Conference on Distributed Computing Systems Workshops.

[11]  Deborah Estrin,et al.  Highly-resilient, energy-efficient multipath routing in wireless sensor networks , 2001, MOCO.

[12]  Indranil Gupta,et al.  Scalable fault-tolerant aggregation in large process groups , 2001, 2001 International Conference on Dependable Systems and Networks.

[13]  Srikanta Tirthapura,et al.  Estimating simple functions on the union of data streams , 2001, SPAA '01.

[14]  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 .

[15]  David E. Culler,et al.  Supporting aggregate queries over ad-hoc wireless sensor networks , 2002, Proceedings Fourth IEEE Workshop on Mobile Computing Systems and Applications.

[16]  Srikanta Tirthapura,et al.  Distributed Streams Algorithms for Sliding Windows , 2002, SPAA '02.

[17]  Christos Faloutsos,et al.  ANF: a fast and scalable tool for data mining in massive graphs , 2002, KDD.

[18]  Jennifer Widom,et al.  Models and issues in data stream systems , 2002, PODS.

[19]  S. Muthukrishnan,et al.  Data streams: algorithms and applications , 2005, SODA '03.

[20]  Ramesh Govindan,et al.  Understanding packet delivery performance in dense wireless sensor networks , 2003, SenSys '03.

[21]  David E. Culler,et al.  TOSSIM: accurate and scalable simulation of entire TinyOS applications , 2003, SenSys '03.

[22]  Deborah Estrin,et al.  Computing aggregates for monitoring wireless sensor networks , 2003, Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications, 2003..

[23]  John Heidemann,et al.  RMST: reliable data transport in sensor networks , 2003, Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications, 2003..

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

[25]  Robbert van Renesse,et al.  The power of epidemics: robust communication for large-scale distributed systems , 2003, CCRV.

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

[27]  Dawn Xiaodong Song,et al.  SIA: secure information aggregation in sensor networks , 2003, SenSys '03.

[28]  Amin Vahdat,et al.  Using Random Subsets to Build Scalable Network Services , 2003, USENIX Symposium on Internet Technologies and Systems.

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

[30]  Chieh-Yih Wan,et al.  Reliable Transport for Sensor Networks , 2004 .

[31]  Rajeev Motwani,et al.  The price of validity in dynamic networks , 2004, SIGMOD '04.

[32]  Chieh-Yih Wan,et al.  Reliable transport for sensor networks: PSFQ - Pump slowly fetch quickly paradigm , 2004 .

[33]  Jeffrey Considine,et al.  Spatio-temporal aggregation using sketches , 2004, Proceedings. 20th International Conference on Data Engineering.

[34]  Sujit Dey,et al.  Model based error correction for wireless sensor networks , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..

[35]  Johannes Gehrke,et al.  Query Processing in Sensor Networks , 2003, CIDR.

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

[37]  Graham Cormode,et al.  Holistic aggregates in a networked world: distributed tracking of approximate quantiles , 2005, SIGMOD '05.

[38]  Suman Nath,et al.  Tributaries and deltas: efficient and robust aggregation in sensor network streams , 2005, SIGMOD '05.

[39]  David E. Culler,et al.  A unifying link abstraction for wireless sensor networks , 2005, SenSys '05.

[40]  Srinivasan Seshan,et al.  Exploiting redundancy for robust sensing , 2005 .

[41]  Stephen P. Boyd,et al.  Gossip algorithms: design, analysis and applications , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[42]  Graham Cormode,et al.  An improved data stream summary: the count-min sketch and its applications , 2004, J. Algorithms.

[43]  Dongyan Xu,et al.  Robust computation of aggregates in wireless sensor networks: distributed randomized algorithms and analysis , 2005 .

[44]  Beng Chin Ooi,et al.  Multiple aggregations over data streams , 2005, SIGMOD '05.

[45]  A. Dimakis,et al.  Geographic gossip: efficient aggregation for sensor networks , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.