1. Aggregate Query Processing in Cache- Aware Wireless Sensor Networks Khaled Ammar University of Alberta

2. Agenda Introduction Previous Work Contribution – Selection Process – Hot Area Conclusion Future Work References

3. 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.

4. 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.

5. Previous work Q R Q2’Q2’Q1’Q1’

6. Q2’Q2’Q1’Q1’ Ѳ1Ѳ1 Ѳ2Ѳ2

7. Q C Challenges for Aggregate functions None of cached data could be considered as Relevant queries.

8. Agenda Introduction Previous Work Contribution Conclusion Future Work References

9. Contribution Customize Selection Process criteria Special Handling for the Hot Area

10. 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.

11. Customize Selection Process criteria Proposed: – Cached queries should be fully bounded: Average  Sum and Count Sum + Count  Average Histogram  Count, Average, Sum, Max, Min Histogram – Accept cached queries not fully bounded if: Queries match Aggregate function = Max or Min Query answer belongs to the queried area

12. Customize Selection Process criteria Performance Evaluation

16. 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.

17. Special Handling for the Hot Area Which query is more useful for others

18. 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.

19. Thanks

20. 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. Back

21. Special Handling for the Hot Area Cost of Histogram vs. Row data [TAG02]