1. Wireless Sensor Networks In-Network Relational Databases Jocelyn Botello

2. Botello 2April 9, 2008EEL 6897: Prof. Boloni Overview Introduction Sensor Database System Projects –TinyDB –Cougar Maximum Performance –Efficiency –Optimization

3. Botello 3April 9, 2008EEL 6897: Prof. Boloni Introduction Minimization Goal: –Network Traffic –Amount of Transmitted Data Maximization Goal: –Computing Capacity –Power Acquire Data for Unlimited Time

4. Botello 4April 9, 2008EEL 6897: Prof. Boloni Sensor Database System Access data with no previous knowledge Three-Layer Reference Model Relational Model –Sensor Data: Time Series –Stored Data: Relations

5. Botello 5April 9, 2008EEL 6897: Prof. Boloni TinyDB from Berkley Query Processor Multiple Query Concurrency Tree Routing

6. Botello 6April 9, 2008EEL 6897: Prof. Boloni TinyDB from Berkley Event- Based Queries Actuation Queries Lifetime- Based Queries Monitoring Queries Network Health Queries Exploratory Queries Aggregation Queries

7. Botello 7April 9, 2008EEL 6897: Prof. Boloni Cougar from Cornell Sensors –Abstract Data Type Functions –In-Network Processing –Gateway Node Query Proxy –Small Database Component

8. Botello 8April 9, 2008EEL 6897: Prof. Boloni Efficiency Communication Failure Reliable Data –Uncertainty of Data –Security of Data Network’s Power Life

9. Botello 9April 9, 2008EEL 6897: Prof. Boloni Communication Failure Sensors Physically Dependable –Outside Factors Keep Data Alive –Back-Up –Accessibility, Availability

10. Botello 10April 9, 2008EEL 6897: Prof. Boloni Reliable Data: Uncertainty Level of Accuracy Vs Cost of Computation Desired Accuracy Probabilistic Threshold Query

11. Botello 11April 9, 2008EEL 6897: Prof. Boloni Reliable Data: Security Network Specific –Level of Security –Access Points/Rights Affects of Aggregation Dynamic Level of Security Vs Access Time

12. Botello 12April 9, 2008EEL 6897: Prof. Boloni Optimization Data Space Management Queries Aggregation

13. Botello 13April 9, 2008EEL 6897: Prof. Boloni Data Space Management Storage Nodes –Minimize Traffic & Retrieve Time Switch Roles –Busy Region –Power Life

14. Botello 14April 9, 2008EEL 6897: Prof. Boloni Queries Independent, Dynamic Irrelevant Factors –Power Management –Time Synchronization –Data Processing –Data Collection Maintaining Power Life Multiple, Nested Queries

15. Botello 15April 9, 2008EEL 6897: Prof. Boloni Aggregation Partial/Total Aggregation Selective Data Spatial Aggregation –Spatial Moving Average –Voroni Diagram –Triangular Irregular Network

16. Botello 16April 9, 2008EEL 6897: Prof. Boloni Conclusion Maximum Performance –Efficiency Reliable Data Vs Communication Failure –Optimization Queries Aggregation –Minimize Network Traffic –Conservation of Power

17. Botello 17April 9, 2008EEL 6897: Prof. Boloni Future Work Power Management Data Management Data Collection Data Processing –Query Processing Network Design

18. Botello 18April 9, 2008EEL 6897: Prof. Boloni References [1] P. S. Philippe Bonnet, Johannes Gehrke, “Towards sensor database systems,” ACM, vol. 1987, pp. 3–14, 2001. [2] Y. Yao and J. Gehrke, “The cougar approach to in- network query processing in sensor networks,” ACM SIGMOD Record, vol. 31, no. 3, pp. 9–18, September 2002. [3] Q. Luo and H. Wu, “System design issues in sensor databases,” in Proc. ACM SIGMOD International Conference on Management of Data, June 2007, pp. 1182–1185. [4] Zechinelli-Martini, Jose-Luis, and I. Elias-Morales, “Modelling and querying sensor databases,” in Proc. IEEE 8th Mexican International Conference on Current Trends in Computer Science, September 2007, pp. 138–148. [5] S. R. Madden, M. J. Franklin, J. M. Hellerstein, and W. Hong, “Tinydb: An acquisitional query procesing system for sensor networks,” ACM Transactions on Database System, vol. 30, no. 1, pp. 122–173, March 2006. [6] T. Apaydin, S. Vural, and P. Sinha, “On improving data accessibility in storage based sensor networks,” in Proc. IEEE International Conference on Mobile Adhoc and Sensor System(MASS ’07), October 2007, pp. 1–9. [7] R. Cheng and S. Prabhakar, “Managing uncertainty in sensor databases,” SIGMOD Record, vol. 32, no. 4, pp. 41–46, 2003. [8] B. Thuraisingham, “Secure sensor information management and mining,” IEEE Signal Processing Magazine, vol. 3, pp. 14–19, May 2004. [9] R. Tamishetty, L. H. Ngoh, and P. H. Keng, “Query-based wireless sensor storage management for real-time applications,” in Proc. IEEE International Conference on Industrial Informatics 2006, August 2006, pp. 166– 170. [10] S. M. Michael J. Franklin, Joseph M. Hellerstein, “Thinking big about tiny databases,” Bulletin of IEEE Computer Society Technical Committee on Data Engineering, September 2007. [11] Q. Ren and Q. Liang, “Query processing optimization through sample size and monitoring coverage controlling in wireless sensor networks,” IEEE CNF, vol. 3, pp. 830–834, September 2006. [12] Q. Ren and Q. Lian, “A quality-guaranteed and energy-efficient query processing algorithm for sensor networks,” in Proc. IEEE Wireless Communications and Networking Conference 2006 (WCNC2006), April 2006, pp. 47–62. [13] L. Q. Zhuang, J. B. Zhang, D. H. Zhang, and Y. Z. Zhao, “Data management for wireless sensor networks: Research issues and challenges,” in Proc. IEEE 2006 International Conference on Wireless Communication, Networking and Mobile Computing, September 2005, pp. 1–5. [14] G. K. J. B. Jeffrey Considine, Feifei Li, “Approximate aggregation techniques for sensor databases,” in Proc. IEEE 20th International Conference on Data Engineering (ICDE’04), April 2004, pp. 449–460. [15] P. Flajolet and G. N. Martin, “Probablistic counting algorithms for data base applications,” Journal of Computer and System Sciences. [16] M. Sharifzadeh and C. Shababi, “Supporting spatial aggregation in sensor network databases,” in Proc. 12th Annual ACM international workshop on Geographic Information Systems, 2004, pp.166– 175.