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Adaptive cleaning for rfid data streams
, 2006
"... ABSTRACT To compensate for the inherent unreliability of RFID data streams, most RFID middleware systems employ a "smoothing filter", a sliding-window aggregate that interpolates for lost readings. In this paper, we propose SMURF, the first declarative, adaptive smoothing filter for RFID ..."
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Cited by 101 (0 self)
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ABSTRACT To compensate for the inherent unreliability of RFID data streams, most RFID middleware systems employ a "smoothing filter", a sliding-window aggregate that interpolates for lost readings. In this paper, we propose SMURF, the first declarative, adaptive smoothing filter for RFID data cleaning. SMURF models the unreliability of RFID readings by viewing RFID streams as a statistical sample of tags in the physical world, and exploits techniques grounded in sampling theory to drive its cleaning processes. Through the use of tools such as binomial sampling and π-estimators, SMURF continuously adapts the smoothing window size in a principled manner to provide accurate RFID data to applications.
Outlier-aware data aggregation in sensor networks
- In ICDE
, 2008
"... Abstract — In this paper we discuss a robust aggregation framework that can detect spurious measurements and refrain from incorporating them in the computed aggregate values. Our framework can consider different definitions of an outlier node, based on a specified minimum support. Our experimental e ..."
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Cited by 5 (1 self)
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Abstract — In this paper we discuss a robust aggregation framework that can detect spurious measurements and refrain from incorporating them in the computed aggregate values. Our framework can consider different definitions of an outlier node, based on a specified minimum support. Our experimental evaluation demonstrates the benefits of our approach. I.
RFID Data Management: Challenges and Opportunities
"... promises to revolutionize the way we track items in supply chain, retail store, and asset management applications. The size and different characteristics of RFID data pose many interesting challenges in the current data management systems. In this paper, we provide a brief overview of RFID technolog ..."
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promises to revolutionize the way we track items in supply chain, retail store, and asset management applications. The size and different characteristics of RFID data pose many interesting challenges in the current data management systems. In this paper, we provide a brief overview of RFID technology and highlight a few of the data management challenges that we believe are suitable topics for exploratory research. I.
DESIGN GUIDELINES FOR RFID-BASED APPLICATIONS IN MANUFACTURING
"... The RFID technology opens new opportunities to monitor and control manufacturing processes. Therefore more and more manufacturers consider the introduction of RFID in their production lines. However, RFID projects face various challenges when designing the software infrastructure. In this paper we p ..."
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The RFID technology opens new opportunities to monitor and control manufacturing processes. Therefore more and more manufacturers consider the introduction of RFID in their production lines. However, RFID projects face various challenges when designing the software infrastructure. In this paper we present design principles which guide application designers in developing and adapting RFID solutions for manufacturing environments. We have derived these design guidelines from a Product Line Analysis (PLA) based on several case studies that we have conducted at manufacturers. Here we systematically identify core assets of RFID applications in manufacturing. Based on the PLA we present a toolset of standard components and their variations along with guidelines for the application design. These guidelines cover processing paradigms for RFID data and heuristics for distributing data and logic in the IT system.
The VLDB Journal DOI 10.1007/s00778-011-0233-y REGULAR PAPER Distributed similarity estimation using derived dimensions
"... Abstract Computing the similarity between data objects is a fundamental operation for many distributed applications such as those on the World Wide Web, in Peer-to-Peer net-works, or even in Sensor Networks. In our work, we provide a framework based on Random Hyperplane Projection (RHP) that permits ..."
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Abstract Computing the similarity between data objects is a fundamental operation for many distributed applications such as those on the World Wide Web, in Peer-to-Peer net-works, or even in Sensor Networks. In our work, we provide a framework based on Random Hyperplane Projection (RHP) that permits continuous computation of similarity estimates (using the cosine similarity or the correlation coefficient as the preferred similarity metric) between data descriptions that are streamed from remote sites. These estimates are com-puted at a monitoring node, without the need for transmitting the actual data values. The original RHP framework is data agnostic and works for arbitrary data sets. However, data in most applications is not uniform. In our work, we first describe the shortcomings of the RHP scheme, in particular, its inefficiency to exploit evident skew in the underlying data distribution and then propose a novel framework that auto-matically detects correlations and computes an RHP embed-ding in the Hamming cube tailored to the provided data set using the idea of derived dimensions we first introduce. We further discuss extensions of our framework in order to cope with changes in the data distribution. In such cases, our tech-nique automatically reverts to the basic RHP model for data items that cannot be described accurately through the com-puted embedding. Our experimental evaluation using several real and synthetic data sets demonstrates that our proposed scheme outperforms the existing RHP algorithm and alterna-tive techniques that have been proposed, providing signifi-cantly more accurate similarity computations using the same number of bits.
Copyright © 2007 Inderscience Enterprises Ltd. Managing RFID data in supply chains
"... Abstract: The implementation of RFID leads to improved visibility in supply chains. However, as a consequence of the increased data collection and enhanced data granularity, supply chain participants have to deal with new data management challenges. In this paper, we give an overview of the current ..."
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Abstract: The implementation of RFID leads to improved visibility in supply chains. However, as a consequence of the increased data collection and enhanced data granularity, supply chain participants have to deal with new data management challenges. In this paper, we give an overview of the current challenges and solution proposals in the area of data collection and transformation, data organisation and data security. We also identify further research requirements.
