Distributed Spatial Skyline Query Processing in Wireless Sensor Networks ⋆

Spatial skyline queries can be used in wireless sensor networks for collaborative positioning of multiple objects. However, designing a distributed spatial skyline algorithm in resource constrained wireless environments introduces several research challenges: how to distribute the computation of distances to multiple events in order to compute the skylines efficiently, accurately, quickly, progressively, and concurrently while dealing with the network and event dynamics. We address these challenges by designing, implementing, and extensively evaluating the Distributed Spatial Skyline (DSS) algorithm. DSS is the first distributed algorithm to compute spatial skylines. In a network of 554 nodes, DSS reduces the communication overhead by up to 91% over a centralized algorithm.

[1]  D. Agrawal,et al.  Efficient Skyline Computation over Ad-hoc Aggregations , 2008 .

[2]  Cyrus Shahabi,et al.  The spatial skyline queries , 2006, VLDB.

[3]  Peter Desnoyers,et al.  Exact distributed Voronoi cell computation in sensor networks , 2007, IPSN.

[4]  Young-Jin Kim,et al.  Geographic routing made practical , 2005, NSDI.

[5]  Jian Pei,et al.  SUBSKY: Efficient Computation of Skylines in Subspaces , 2006, 22nd International Conference on Data Engineering (ICDE'06).

[6]  Bin Jiang,et al.  Probabilistic Skylines on Uncertain Data , 2007, VLDB.

[7]  Hua Lu,et al.  Parallel Distributed Processing of Constrained Skyline Queries by Filtering , 2008, 2008 IEEE 24th International Conference on Data Engineering.

[8]  Shuigeng Zhou,et al.  Towards Energy-Efficient Skyline Monitoring in Wireless Sensor Networks , 2007, EWSN.

[9]  Christos Doulkeridis,et al.  SKYPEER: Efficient Subspace Skyline Computation over Distributed Data , 2007, 2007 IEEE 23rd International Conference on Data Engineering.

[10]  Mohamed F. Mokbel,et al.  Skyline Query Processing for Incomplete Data , 2008, 2008 IEEE 24th International Conference on Data Engineering.

[11]  Anthony K. H. Tung,et al.  Categorical skylines for streaming data , 2008, SIGMOD Conference.

[12]  Xuemin Lin,et al.  Selecting Stars: The k Most Representative Skyline Operator , 2007, 2007 IEEE 23rd International Conference on Data Engineering.

[13]  Cyrus Shahabi,et al.  Poster abstract: A distributed algorithm to compute spatial skyline in wireless sensor networks , 2009, 2009 International Conference on Information Processing in Sensor Networks.

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

[15]  Xiang Lian,et al.  Monochromatic and bichromatic reverse skyline search over uncertain databases , 2008, SIGMOD Conference.

[16]  Deborah Estrin,et al.  Data-Centric Storage in Sensornets with GHT, a Geographic Hash Table , 2003, Mob. Networks Appl..

[17]  Beng Chin Ooi,et al.  Skyline Queries Against Mobile Lightweight Devices in MANETs , 2006, 22nd International Conference on Data Engineering (ICDE'06).

[18]  Matt Welsh,et al.  Programming Sensor Networks Using Abstract Regions , 2004, NSDI.

[19]  Wolf-Tilo Balke,et al.  Efficient Distributed Skylining for Web Information Systems , 2004, EDBT.

[20]  Jignesh M. Patel,et al.  Efficient Skyline Computation over Low-Cardinality Domains , 2007, VLDB.

[21]  Ben Y. Zhao,et al.  Parallelizing Skyline Queries for Scalable Distribution , 2006, EDBT.

[22]  Anthony K. H. Tung,et al.  Finding k-dominant skylines in high dimensional space , 2006, SIGMOD Conference.

[23]  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 .