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Aggregate Query Processing in Cache-Aware Wireless Sensor Networks
Khaled AmmarUniversity of Alberta
Agenda
• Introduction • Previous Work• Contribution– Selection Process– Hot Area
• Conclusion• Future Work• References
Introduction
• Wireless Sensor Network (WSN) is important to enable users query the physical world.
• Energy consumption is the main challenge.
• Spatial queries query sensor information with in a defined area.
• Multi user and Multiple queries are expected.
Previous work
Q
C
[CACHE-10] M.A. Nascimento, R. Alencar, and A. Brayner. Optimizing query processing in cache-aware wireless sensor networks. Proc. of SSDBM Journal, pages 60-77, 2010.
Customize Selection Process criteria
• In the previous approach [CACHE-10]:– All queries assumed to be row data queries.– Aggregation extension: (Native Approach)• Cached queries should be fully bounded• The Requested and the cached query should be the
same Aggregate function
[CACHE-10] M.A. Nascimento, R. Alencar, and A. Brayner. Optimizing query processing in cache-aware wireless sensor networks. Proc. of SSDBM Journal, pages 60-77, 2010.
Customize Selection Process criteria
• Proposed:– Cached queries should be fully bounded:• Average Sum and Count• Sum + Count Average• Histogram Count, Average, Sum, Max, Min
– Accept cached queries not fully bounded if:• Queries match• Aggregate function = Max or Min• Query answer belongs to the queried area
Special Handling for the Hot Area
• Definition: Hot Area is an area in the monitored field with high frequent queries.
• Any monitored field, usually have a specific group of areas with high importance. – Examples: Gates, Server rooms,
• Searching for a Hot area is out of our scope.
Conclusion
• Existing Cache-Aware WSN can save about 5% of the queries cost.
• Proposed new rules for relevant query increase the percentage to about 15%
• Histogram was shown to be very helpful to all other aggregates.
• Relaxing the condition of bounded queries is more important than relaxing the condition of queries matching .
Histogram for Exact queries
• Histogram provides approximate answers only• Recently, we proposed HIU [HIU-11]:– Cheaper than TAG, use around 1/3 of TAG’s cost.– Can compute exact answers as well as approximate.– It has an extension to answer a Median query [RBM-11]
[HIU-11] Khaled Ammar and Mario A. Nascimento. Histogram and other aggregate queries in wireless sensor networks. Proc. of SSDBM Journal, page (to appear), 2011.
[RBM-11] K. Ammar, M.A. Nascimento, and J. Niedermayer. An adaptive refinement-based algorithm for median queries in wireless sensor networks. In Proc. of MobiDE, page (to appear), 2011.
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