A Materialized View Approach to Support Aggregation Operations over Long Periods in Sensor Networks
The increasing interest on processing data created by
sensor networks has evolved into approaches to implement sensor
networks as databases. The aggregation operator, which calculates a
value from a large group of data such as computing averages or sums,
etc. is an essential function that needs to be provided when
implementing such sensor network databases. This work proposes to
add the DURING clause into TinySQL to calculate values during a
specific long period and suggests a way to implement the aggregation
service in sensor networks by applying materialized view and
incremental view maintenance techniques that is used in data
warehouses. In sensor networks, data values are passed from child
nodes to parent nodes and an aggregation value is computed at the root
node. As such root nodes need to be memory efficient and low
powered, it becomes a problem to recompute aggregate values from all
past and current data. Therefore, applying incremental view
maintenance techniques can reduce the memory consumption and
support fast computation of aggregate values.
[1] Y. Yao and J. Gehrke, "The Cougar approach to in-network query
processing in sensor networks," in Proc. ACM SIGMOD, 2002
[2] S.Madden, M. J. Franklin, J. M. Hellerstein, and W. Hong, "The design of
an acquisational query processor for sensor networks," ACM SIGMOD,
2003
[3] TinyDB, http://berkeley.intel-research.net/tinydb/
[4] Ashish Gupta and Inderpal Singh Mumick, "Maintenance of Materialized
View: Problems, Techniques, and Applications," IEEE Data Engineering
Bulletin, Special Issue on Materialized Views and Data Warehousing,
Vol. 18, No. 2, 1995
[5] Ki Yong Lee, Jin Hyun Son and Myoung Ho Kim, "Efficient Incremental
View Maintenance in Data Warehouses," ACM CIKM, 2001
[6] Samuel Madden, Michael J. Franklin, Joseph M. Hellerstein, and Wei
Hong, "TAG: a Tiny Aggregation Service for Ad-Hoc Sensor Networks,"
ACM SIGOPSI, Vol. 36, pp. 131-146, 2002
[7] Ramesh Govindan, Joseph M. Hellerstein, Wei Hong, Samuel Madden,
Michael Franklin, and Scott Shenker, "The Sensor Network as a
Database," Technical Rep ort 0-771, Compm2E Science Department
[8] Joseph M. Hellerstein, Peter J. Haas, and Helen J. Wang., "Online
Aggregation," ACM SIGMOD International Conference on Management
Data (ICDM), 1997
[9] Y.Zhuge, H. Garcia-Molina, J. Hammer, and J. Widom, "View
Maintenance in a warehousing environment," ACM SIGMOD, 1994
[10] Ashish Gupta, Inderpal Singh Mumick, V.S. Subrahmanian. ,
"Maintaining Views Incrementally," ACM SIGMOD Record, Vol. 22,
1993, p157-166
[11] Amit Manjhi, Suman Nath, Phillip B. Gibbons, "Tributaries and Deltas:
Efficient and Robust Aggregation in Sensor Network Streams," ACM
SIGMOD, 2005
[12] J. Considine, F.Li, G. Kollios, and J. Byers, "Approximate aggregation
techniques for sensor databases," IEEE ICDE, 2004
[1] Y. Yao and J. Gehrke, "The Cougar approach to in-network query
processing in sensor networks," in Proc. ACM SIGMOD, 2002
[2] S.Madden, M. J. Franklin, J. M. Hellerstein, and W. Hong, "The design of
an acquisational query processor for sensor networks," ACM SIGMOD,
2003
[3] TinyDB, http://berkeley.intel-research.net/tinydb/
[4] Ashish Gupta and Inderpal Singh Mumick, "Maintenance of Materialized
View: Problems, Techniques, and Applications," IEEE Data Engineering
Bulletin, Special Issue on Materialized Views and Data Warehousing,
Vol. 18, No. 2, 1995
[5] Ki Yong Lee, Jin Hyun Son and Myoung Ho Kim, "Efficient Incremental
View Maintenance in Data Warehouses," ACM CIKM, 2001
[6] Samuel Madden, Michael J. Franklin, Joseph M. Hellerstein, and Wei
Hong, "TAG: a Tiny Aggregation Service for Ad-Hoc Sensor Networks,"
ACM SIGOPSI, Vol. 36, pp. 131-146, 2002
[7] Ramesh Govindan, Joseph M. Hellerstein, Wei Hong, Samuel Madden,
Michael Franklin, and Scott Shenker, "The Sensor Network as a
Database," Technical Rep ort 0-771, Compm2E Science Department
[8] Joseph M. Hellerstein, Peter J. Haas, and Helen J. Wang., "Online
Aggregation," ACM SIGMOD International Conference on Management
Data (ICDM), 1997
[9] Y.Zhuge, H. Garcia-Molina, J. Hammer, and J. Widom, "View
Maintenance in a warehousing environment," ACM SIGMOD, 1994
[10] Ashish Gupta, Inderpal Singh Mumick, V.S. Subrahmanian. ,
"Maintaining Views Incrementally," ACM SIGMOD Record, Vol. 22,
1993, p157-166
[11] Amit Manjhi, Suman Nath, Phillip B. Gibbons, "Tributaries and Deltas:
Efficient and Robust Aggregation in Sensor Network Streams," ACM
SIGMOD, 2005
[12] J. Considine, F.Li, G. Kollios, and J. Byers, "Approximate aggregation
techniques for sensor databases," IEEE ICDE, 2004
@article{"International Journal of Information, Control and Computer Sciences:49339", author = "Minsoo Lee and Julee Choi and Sookyung Song", title = "A Materialized View Approach to Support Aggregation Operations over Long Periods in Sensor Networks", abstract = "The increasing interest on processing data created by
sensor networks has evolved into approaches to implement sensor
networks as databases. The aggregation operator, which calculates a
value from a large group of data such as computing averages or sums,
etc. is an essential function that needs to be provided when
implementing such sensor network databases. This work proposes to
add the DURING clause into TinySQL to calculate values during a
specific long period and suggests a way to implement the aggregation
service in sensor networks by applying materialized view and
incremental view maintenance techniques that is used in data
warehouses. In sensor networks, data values are passed from child
nodes to parent nodes and an aggregation value is computed at the root
node. As such root nodes need to be memory efficient and low
powered, it becomes a problem to recompute aggregate values from all
past and current data. Therefore, applying incremental view
maintenance techniques can reduce the memory consumption and
support fast computation of aggregate values.", keywords = "Aggregation, Incremental View Maintenance,Materialized view, Sensor Network.", volume = "2", number = "8", pages = "2562-5", }