A cross pruning framework for Top-k data collection in wireless sensor networks

Xingjie Liu*, Jianliang XU, Wang Chien Lee

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

23 Citations (Scopus)

Abstract

Energy conservation is a key issue for algorithm designs in wireless sensor networks. In this paper, we explore in-network aggregation techniques for answering top-k queries in wireless sensor networks. A top-κ query retrieves the κ data objects with the highest scores evaluated by a scoring function on interested features of sensor readings. Our study shows that existing techniques for processing top-κ query, e.g., Tiny AGgregation Service (TAG), are not energy efficient due to deficiencies in their routing structures and data aggregation mechanisms. To address these deficiencies, we propose to develop a new cross pruning (XP) aggregation framework for top-κ data collection in wireless sensor networks. The XP framework incorporates several novel ideas to facilitate efficient in-network aggregation and filtering, including 1) building a cluster-tree routing structure to aggregate more objects locally; 2) adopting a broadcastthen-filter approach for efficiently suppressing redundant data transmissions; and 3) providing a cross pruning technique to enhance in-network filtering effectiveness. An extensive set of experiments based on simulation has been conducted to evaluate the performance of TAG and the proposed XP framework. The experimental results validate our proposals and show that XP significantly outperforms TAG in energy cost.

Original languageEnglish
Title of host publicationMDM2010 - 11th International Conference on Mobile Data Management
Pages157-166
Number of pages10
DOIs
Publication statusPublished - 2010
Event11th IEEE International Conference on Mobile Data Management, MDM 2010 - Kansas City, MO, United States
Duration: 23 May 201026 May 2010

Publication series

NameProceedings - IEEE International Conference on Mobile Data Management
ISSN (Print)1551-6245

Conference

Conference11th IEEE International Conference on Mobile Data Management, MDM 2010
Country/TerritoryUnited States
CityKansas City, MO
Period23/05/1026/05/10

Scopus Subject Areas

  • Engineering(all)

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