近年來無線感測網路由於的它潛在的應用價值，使它受到許多的重視，許多研究著重於使無線感測網路節省能源來達到長時間部署的目的。在於這些研究當中，網路內資料聚集技術被認為是一個能夠有效減少資料傳輸次數，節省傳輸耗能的方法。在這篇論文中，我們為以群集為基礎架構的無線感測網路提出了一個有效的演算法來建造以及維護資料匯集的結構，在我們的架構當中，我們主要的想法是將空間上相關聯性高的感測器分配到同一個高空間關聯性的群組中，為每個高關聯性群組選擇出一個代表性的點，以這代表點的讀數作為參照，利用資料裡時間以及空間上的相關聯性，為資料匯集減少其所需要的傳輸次數，並且使用線性預測的技術來減少縮減傳輸次數所會造成的誤差，這些高關聯性的群組會隨著感測器之間關係的變動而更新。我們也設計了一個簡單的演算法來避免不必要的群組更新，以減少更新所帶來的額外的維護花費。在實驗中，我們使用真實環境當中所量測得到的資料組來測試我們的匯集架構，實驗的結果顯示我們的架構可以節省下大量的傳輸次數，並且不會為最終的匯集值帶來過大的誤差。結果顯示合適的將感測器以資料裡空間的關係性分成不同群組，並且同時應用上時間裡關聯性的匯集架構將會比現有只單獨使用空間或時間關聯性的匯集架構表現地更好。

[1] Mainwaring A., Culler D., Polastre J., Szewczyk R., and Anderson J., “Wireless Sensor Networks for Habitat Monitoring”, ACM International Workshop on Wireless Sensor Networks and Applications, pp. 88-97, September 2002.
[2] Srivastava M., Muntz R., and Potkonjak M., “Smart Kindergargen: sensor-based wireless networks for smart developmental problem-solving environments,” Proceedings of the ACM SIGMOBILE 7th Annual International Conference on Mobile Computing and Networking, pp.132-138, July 2001.
[3] Intanagonwiwat C., Govindan R., and Estrin D., “Directed Diffusion: A Scalable and Robust Communication Paradigm for Sensor Networks,” ACM/IEEE Proceedings of the 6th Annual International Conference on Mobile Computing and Networking, pp. 56-57, August 2000.
[4] Lindsey S., and Raghavendra C. S., “PEGASIS: Power-Efficient Gathering in Sensor Information Systems,” IEEE Proceedings of the Aerospace Conference, Vol. 3, pp. 1125-1130, March 2002.
[5] Karp B., and Kung, H. T., “GPSR: greedy perimeter stateless routing for wireless networks”, Proceedings of the 6th Annual International Conference on Mobile Computing and Networking, pp. 243-254, August 2000.
[6] Lee, M., Wong, V. W. S., “LPT for data aggregation in wireless sensor networks,” IEEE Global Communications Conference, Vol. 5, pp. 2969-2974, December 2005.
[7] Tulone D., and Madden. S., “An Energy-Efficient Querying Framework in Sensor Networks for Detecting Node Similarities,” Proceedings of the 9th ACM international symposium on Modeling analysis and simulation of wireless and mobile systems, pp. 291-300, October 2006.
[8] Santini S., and Romer K., “An Adaptive Strategy for Quality-Based Data Reduction in Wireless Sensor Networks,” Proceedings of the 3rd International Conference on Networked Sensing Systems, pp. 29-36, June 2006.
[9] Shnayder V., Hempstead M., Chen B., Allen W., and Welsh M., “Simulating the power consumption of large-scale sensor network applications,” Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems, pp. 188-200, November 2004.
[10] Pottie G. J., and Kaiser W. J., “Wireless Integrated Network Sensors,” Communication of the ACM, Vol. 43, pp. 51-58, May 2000.
[11] Heinzelman W., Chandrakasan A., and Balakrishnan H., “Energy-Efficient Communication Protocol for Wireless Microsensor Networks,” Proceeding of 33rd International Conference on System Sciences, Hawaii, Vol.2, pp. 908-918, January 2000.
[12] Heinzelman W., Chandrakasan A., and Balakrishnan H., “An Application-Specific Protocol Architecture for Wireless Microsensor Networks,” IEEE Transactions on Wireless Communications, Vol. 1, pp. 660-670, October 2002.
[13] Younis O., and Sonia F., “HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks,” IEEE Transactions on Mobile Computing, Vol. 4, pp. 366-379, October-December 2004.
[14] Manjeshwar A., and Agrawal D. P., “TEEN: A Routing Protocol for Enhanced Efficiency in Wireless Sensor Networks”, 15th Proceedings of International Parallel and Distributed Processing Symposium, pp. 2009-2015, April 2001.
[15] Manjeshwar A., and Agrawal D. P., “APTEEN: A Hybrid Protocol for Efficient Routing and Comprehensive Information Retrieval in Wireless Sensor Networks,” Proceedings of International Parallel and Distributed Processing Symposium, pp. 195-202, April 2002.
[16] Madden S. R., Franklin M. J., and Hong, W., “TAG: a Tiny AGgregation Service for Ad-Hoc Sensor Network,” 5th Annual Symposium on Operating Systems Design and Implementation, December 2002.
[17] Sharaf M. A., Beaver J., Labrinidis A., “Balancing Energy Efficiency and Quality of Aggregate Data in Sensor Networks,” The International Journal on Very Large Data Bases, Vol. 13, pp. 384-403, December 2004.
[18] Deligiannakis A., Kotidis Y., and Roussopoulos N., “Hierarchical In-Network Data Aggregation with Quality Guarantees,” Proceeding of International Conference on Extending Database Technology, pp. 658-675, 2004.
[19] S. Yoon, and C. Shahabi, “Exploiting Spatial Correlation Towards an Energy Efficient Clustered AGgregation Technique (CAG),” IEEE Conference on Communications, Vol. 5, pp. 3307-3313, May 2005.
[20] Yoon, S., and Shahabi, C., ”The Clustered AGgregation (CAG) Technique Leveraging Spatial and Temporal Correlation in Wireless Sensor Networks,” ACM Transactions on Sensor Networks, Vol. 3, No. 1, March 2007.
[21] Fan, K.-W., Liu, S., P. Sinha, “On the Potential of Structure-Free Data Aggregation in Sensor Networks,” 25th IEEE Proceedings of International Conference on Computer Communications, pp 1-12, April 2006.
[22] Fan, K.-W., Liu, S., P. Sinha, “Scalable data aggregation for dynamic events in sensor networks,” Proceedings of the 4th International Conference on Embedded Networked Sensor System, pp 181-194, November 2006.
[23] Gupta H., Navda V., Das S., and Chowdhary V., “Efficient Gathering of Correlated Data in Sensor Networks,” ACM Transaction on Sensor Networks, Vol. 4, No. 4, January 2008.
[24] Kotidis Y., “Snapshot Queries: Towards Data-Centric Sensor Networks”, 21st International Conference on Data Engineering, pp. 131-142, April 2005.
[25] Arici T., Gedik B., and Altunbasak Y., Liu, L., “PINCO: A Pipelined In-Network compression scheme for data collection in wireless sensor networks”, Proceedings of the 12th International Conference on Computer Communications and Networks, pp. 539-544, October 2003.
[26] Intel Lab Data, http://berkeley.intel-research.net/labdata