Data sweeper: A proactive filtering framework for error-bounded sensor data collection

Dan Wang, Jiangchuan Liu, Jianliang Xu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

In this paper, we develop a novel framework that attempts to reduce network traffic for error-bounded data collection in wireless sensor networks. In many sensor applications, it is acceptable that the monitoring results evaluated based on collected data might deviate from the exact results; as long as the error is bounded by a certain threshold. One well-known technique for error-bounded data collection is data filtering, which explores temporal data correlation to suppress data updates. A concrete scheme was proposed in [1]. The data collection is divided in rounds. A filter is installed on each node and the total filter size is constrained by the user-specified error budget. Intuitively, if the data change from the last update report is smaller than the filter size, the current update is suppressed, i.e., not to report to the base station. To adapt to system dynamics, the sizes of all filters are periodically shrunk and the left-over budget is re-allocated to the node with the highest load. Many follow up studies can be found [2][3].
Original languageEnglish
Title of host publication2010 IEEE 18th International Workshop on Quality of Service, IWQoS 2010
DOIs
Publication statusPublished - 20 Sep 2010
Event2010 IEEE 18th International Workshop on Quality of Service, IWQoS 2010 - Beijing, China
Duration: 16 Jun 201018 Jun 2010

Conference

Conference2010 IEEE 18th International Workshop on Quality of Service, IWQoS 2010
Country/TerritoryChina
CityBeijing
Period16/06/1018/06/10

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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