CSE 590Q Database Seminar

Fall 2006: Data Management Challenges for the World-Wide Sensor Web

Magdalena Balazinska
Dan Suciu

Mondays 3:30 - 4:30pm,
CSE 605 Database Lab

Seminar Description

Technical advances are making it possible to deploy increasingly large numbers of sensors to monitor the physical world. These deployments give rise to exciting new applications, but they also raise great data management challenges.

In this seminar, we will read papers presenting the main types of sensor deployments and application domains and the key data management challenges that need to be addressed to enable the "World-Wide Sensor Web".

This seminar is inspired by the UW MSR Institute on the World-Wide Sensor Web that took place in August 2006 in Blaine, WA. http://www.cs.washington.edu/mssi/2006/index.html


Day Topic(s) Presenter(s)
02 October Introduction and paper assignment Magda Balazinska
09 October

Sensor networks data management

In order for everyone to be on the same page, we will first review one of the main systems for query processing in sensor networks.

TinyDB: An Acquisitional Query Processing System for Sensor Networks.
Samuel Madden, Michael Franklin, Joseph Hellerstein, and Wei Hong. In TODS 30(1), 2005.

Additional references:

  • Main conference for research on sensor networks: Sensys
YongChul Kwon
16 October

Application domain 1: Scientific data management

Increasingly, scientists need to deploy and share common sensor infrastructures to monitor and study the physical world. We will discuss two short papers that present some of the challenges of scientific sensor data management.

Life Under your Feet: A Wireless Soil Ecology Sensor Network.
Razvan Musaloiu, Andreas Terzis, Katalin Szlavecz, Alex Szalay, Joshua Cogan, and Jim Gray. In EmNetS 2006. [Note that there is also an extended tech report version of this paper with a slightly different title].

Batch is Back: CasJobs, Serving Multi-TB Data on the Web .
William OMullane, Nolan Li, Maria Nieto-Santisteban, Alex Szalay, Ani Thakar, Jim Gray. In Proc. of the IEEE International Conference on Web Services (ICWS'05)

Additional references:

Nicholas Murphy
23 October

Application domain 2: Monitoring cities and homes

Different from scientific deployments are sensor networks designed to monitor humans in their daily activities. These networks can be deployed at the scale of a city or at the scale of individual homes.

CarTel: A Distributed Mobile Sensor Computing System.
Bret Hull, Vladimir Bychkovskiy, Kevin Chen, Michel Goraczko, Eugene Shih, Yang Zhang, Hari Balakrishnan, Samuel Madden. In Proc. of SenSys 2006.

An Assisted Living Oriented Information System Based on a Residential Wireless Sensor Network.
G. Virone, A. Wood, L. Selavo, Q. Cao, L. Fang, T. Doan, Z. He, R. Stoleru, S. Lin, and J.A. Stankovic. In Proc. of the 1st Distributed Diagnosis and Home Healthcare (D2H2) Conference.

Additional references:

Brian DeRenzi

30 October

27 October

Spatio-temporal data management

[Note: Rescheduled to Friday, October 27th at 2pm in CSE 605]

Sensor data requires powerful spatio-temporal data management capabilities. The spatio-temporal research area is quite wide. We will only discuss a specific example based on RFID data.

Temporal Management of RFID Data.
Fusheng Wang, Peiya Liu. VLDB 2005.

Evan Welbourne
06 November

Sensor data cleaning (RFID data)

An important challenge when dealing with sensor data is handling erroneous inputs due to noise and sensor failures. We start the discussion by examining how to clean data produced by an RFID infrastructure.

Declarative Support for Sensor Data Cleaning.
Shawn R. Jeffery, Gustavo Alonso, Michael J. Franklin, Wei Hong, Jennifer Widom. Pervasive 2006.

Additional references:

  • Adaptive Cleaning for RFID Data Streams. Shawn R. Jeffery, Minos Garofalakis, Michael J. Franklin. VLDB 2006
  • A Deferred Cleansing Method for RFID Data Analytics. Jun Rao, Sangeeta Doraiswamy, Hetal Thakkar, Latha S. Colby. VLDB 2006
Nodira Khoussainova
13 November

Model-based sensor data management

Continuing on the idea of noisy sensor data, we will discuss the use of correlations and models to handle uncertainty, missed reading, outliers, and more.

Using Probabilistic Models for Data Management in Acquisitional Environments.
Amol Deshpande, Carlos Guestrin, Samuel Madden. In Proceedings of CIDR, 2005.

Additional references:


Chris Re
Abhay Kumar Jha
20 November

Internet-scale infrastructures

We do not spend too much time on infrastructures because most of us studied them last Winter. Here are two good overview papers that we can use to discuss push-based vs pull-based infrastructures and their challenges.

Cache-and-Query for Wide Area Sensor Databases,
Amol Deshpande, Suman Nath, Phillip B. Gibbons, Srinivasan Seshan. ACM SIGMOD 2003.

The Design of the Borealis Stream Processing Engine.
Daniel J Abadi, Yanif Ahmad, Magdalena Balazinska, Ugur Cetintemel, Mitch Cherniack, Jeong-Hyon Hwang, Wolfgang Lindner, Anurag S Maskey, Alex,er Rasin, Esther Ryvkina, Nesime Tatbul, Ying Xing, and Stan Zdonik. CIDR 2005.

Stefan Ekerfelt
Hanna Filipsson
27 November

Data integration and lineage

The world-wide sensor web requires data integration across autonomous organizations. Data integration is one of the main database challenges today. There isn't any work done specifically on integrating sensor data. Instead, we will discuss the more general problem of scientific data integration.

Reconciling while Tolerating Disagreement in Collaborative Data Sharing
Nicholas Taylor, Zachary Ives. SIGMOD 2006

Additional references:

Mike Cafarella
Roxana Geambasu
04 December

Security and privacy

Finally, monitoring the physical world raises serious privacy and security issues.

RFID Security and Privacy: A Research Survey.
A. Juels. Condensed version to appear in 2006 in the IEEE Journal on Selected Areas in Communication.

Security and Privacy in Sensor Networks
Haowen Chan, Adrian Perrig.
IEEE Computer, 36(10), October 2003, pp 103-105

Nilesh Dalvi
Jeffrey Bigham

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Please feel free to send comments to nodira@cs.washington.edu or magda@cs.washington.edu