Energy-efficient data organization and query processing in sensor networks

Recent sensor networks research has produced a class of data storage and query processing techniques called data-centric storage that leverages locality-preserving distributed indexes to efficiently answer multi-dimensional range and range-aggregate queries. These distributed indexes offer a rich design space of a) logical decompositions of sensor relation schema into indexes, as well as b) physical mappings of these indexes onto sensors. In this paper, we explore this space for energy-efficient data organizations (logical and physical mappings of tuples and attributes to sensor nodes) and devise purely local query optimization techniques for processing queries that span such decomposed relations.

[1]  Rajeev Motwani,et al.  Random sampling for histogram construction: how much is enough? , 1998, SIGMOD '98.

[2]  Brad Karp,et al.  Greedy Perimeter Stateless Routing for Wireless Networks , 2000 .

[3]  Joseph M. Hellerstein,et al.  Eddies: continuously adaptive query processing , 2000, SIGMOD '00.

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

[5]  S. B. Yao,et al.  Optimization Algorithms for Distributed Queries , 1986, IEEE Transactions on Software Engineering.

[6]  Young-Jin Kim,et al.  Multi-dimensional range queries in sensor networks , 2003, SenSys '03.

[7]  Deborah Estrin,et al.  GHT: a geographic hash table for data-centric storage , 2002, WSNA '02.

[8]  Deborah Estrin,et al.  DIFS: a distributed index for features in sensor networks , 2003, Ad Hoc Networks.

[9]  Forouzan Golshani,et al.  Proceedings of the Eighth International Conference on Data Engineering , 1992 .

[10]  David J. DeWitt,et al.  Tuple Routing Strategies for Distributed Eddies , 2003, VLDB.

[11]  Samuel Madden,et al.  TAG: a Tiny Aggregation Tree for ad-hoc sensor networks , 2002, OSDI 2002.

[12]  Luis Gravano,et al.  STHoles: a multidimensional workload-aware histogram , 2001, SIGMOD '01.

[13]  Torsten Suel,et al.  Optimal Histograms with Quality Guarantees , 1998, VLDB.

[14]  David E. Culler,et al.  The nesC language: A holistic approach to networked embedded systems , 2003, PLDI.

[15]  Deborah Estrin,et al.  Dimensions: why do we need a new data handling architecture for sensor networks? , 2003, CCRV.

[16]  Deborah Estrin,et al.  Data-centric storage in sensornets , 2003, CCRV.

[17]  J. Elson,et al.  Fine-grained network time synchronization using reference broadcasts , 2002, OSDI '02.

[18]  Brad Karp,et al.  GPSR : Greedy Perimeter Stateless Routing for Wireless , 2000, MobiCom 2000.

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

[20]  Arbee L. P. Chen,et al.  Improvement Algorithms for Semijoin Query Processing Programs in Distributed Database Systems , 1984, IEEE Transactions on Computers.

[21]  Beng Chin Ooi,et al.  Global optimization of histograms , 2001, SIGMOD '01.

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

[23]  Eugene Wong,et al.  Query processing in a system for distributed databases (SDD-1) , 1981, TODS.

[24]  Scott Shenker,et al.  Querying the Internet with PIER , 2003, VLDB.

[25]  John Anderson,et al.  Wireless sensor networks for habitat monitoring , 2002, WSNA '02.

[26]  David E. Culler,et al.  System architecture directions for networked sensors , 2000, SIGP.

[27]  Frederick Reiss,et al.  TelegraphCQ: continuous dataflow processing , 2003, SIGMOD '03.

[28]  Donald Kossmann,et al.  The state of the art in distributed query processing , 2000, CSUR.

[29]  Nimrod Megiddo,et al.  Range queries in OLAP data cubes , 1997, SIGMOD '97.

[30]  Jennifer Widom,et al.  Query Processing, Resource Management, and Approximation ina Data Stream Management System , 2002 .

[31]  Yannis E. Ioannidis,et al.  Selectivity Estimation Without the Attribute Value Independence Assumption , 1997, VLDB.