隨著感測器網路之應用日益複雜，在感測器網路系統中的節點經常需要彼此合作以完成一件工作。對一個節點而言有時合作的對象並非事先指定或已知的，凡是符合條件的節點皆可作為合作對象，去搜尋這些符合條件的節點的行為即稱為”資源尋找”

資源可定義為一個節點可分享的任何事物 – 儲存空間、資料、硬體裝置等等。在傳統的方法中，我們使用完整的資源訊息去判斷一個節點是否符合條件，但在一個無線感測器網路中這麼做非常不經濟，因為傳遞完整的資源訊息會消耗大量電力及儲存空間。另一種選擇則是將資源訊息總結在一起。雖然總結過的資源訊息較不精確，但它卻能為我們省下網路頻寬以及儲存空間。

在這篇論文中，我們將使用一個被廣泛使用的資源總結技巧 – Bloom選濾器 - 設計一個適用於無線感測器網路環境的資源尋找方法，並藉由實驗證明我們所提出之資源尋找方法的高效率。

With the increasing complexity of sensor network applications, nodes in a sensor network system usually have to cooperate with each other to complete a task. Sometimes, a node have to cooperate with another which is not predefined or well known, the only condition of its cooperators is that the nodes match a specific condition. The action to find out where these matching nodes are is called “resource discovery”.

Resource can be anything a node would like to share – storage, data, devices, etc. Traditionally, we use exact information of resources to determine whether a node matches the condition, but in a wireless sensor network this is very costly since propagating exact resource information consumes lot of power and storage. Instead, we may summarize the information together. Though summarized information is less deterministic, it costs less bandwidth and storage, too.

In this thesis, we would like to design a resource discovery algorithm suitable for wireless sensor network environment using a popular resource summary technique called “Bloom filter”, and prove our proposed scheme to be efficient through simulation.

[1] Arturo Crespo, Hector Garcia-Molina, “Routing Indices For Peer-to-Peer Systems”, Proceedings of the 22nd International Conference on Distributed Computing Systems(ICDCS’02), 2002 IEEE.
[2] Burton Bloom, “Space/Time Trade-offs in Hash Coding with Allowable Errors”,
Communications of the ACM Volume 13 / Number 7, page 422-426, July, 1970.
[3] James K. Mullin, “Optimal Semijoins for Distributed Database Systems”, IEEE Transactions on Software Engineering, Volume 16/Number 5, May, 1990.
[4] Sean C. Rhea, John Kubiatowicz, “Probabilistic Location and Routing”, Proceedings of the 21st Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '02), June 2002.
[5] William Acosta, Surendar Chandra, “Unstructured Peer-to-Peer Networks – Next Generation of Performance and Reliability”, Proceedings of the 24st Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '05).
[6] An-Hsun Cheng, Yuh-Jzer Joung, “Probabilistic File Indexing and Searching in Unstructure Peer-to-Peer Networks”, IEEE International Symposium on Cluster Computing and the Grid, 2004.
[7] Li Fan, Pei Cao, Jussara Almeida, Andrei Z. Broder, “Summary Cache: A Scalable Wide-Area Web Cache Shring Protocol”, IEEE/ACM Transactions on Networking, Volume 8, June 2000.
[8] Abhishek Kumar, Jun(Jim) Xu, Ellen W. Zegura, “Efficient and Scalable Query Routing for Unstructured Peer-to-Peer Networks”, Proceedings of the 24st Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM '05).
[9] Crossbow Technology, “MICA data sheet”, http://www.xbow.com/Products/ Product_ pdf_files/Wireless_pdf/MICA.pdf.
[10] Xin Liu, Qingfeng Huang, Ying Zhang, “Combs, Needles, Haystacks: Balancing Push and Pull for Discovery in Large-Scale Sensor Networks”, ACM SenSys04, Nov. 2004.
[11] Serguei Osokine, "Search Optimization in the Distributed Networks", http://www.grouter.net/gnutella/search.htm, December 2002.
[12] Stanley Milgram, “The Small World Problem”, Psychology Today 1, 61, 1967.
[13] Jon Kleinberg, “The Small-World Phenomenon: An Algorithmic Perspective”, Proceedings of the 32nd annual ACM symposium on the theory of computing, pp. 163-. 170.
[14] Danyu Zhu and Matt Mutka, “Sharing Presence Information and Message Notification in an Ad Hoc Network”, IEEE PerCom03.
[15] Xiang Ji, Hongyuan Zha. “Robust Sensor Localization Algorithm in WirelessAd-hoc Sensor Networks”, Proceedings of the Twelfth International Conference on Computer Communications and Networks (ICCCN 03), pp.527-532, 2003.
[16] Dragos Niculescu,Badri Nath, “Ad Hoc Positioning System (APS)”, Proceedings of Joint Conference of the IEEE Computer and Communications Societies (INFOCOM), 2003
[17] Nirupama Bulusu, John Heidemann, Deborah Estrin, “GPS-less Low Cost Outdoor Localization For Very Small Devices”, IEEE Personal Communications Magazine, Vol. 7, No. 5, pp. 28-34. October, 2000.
[18] Tian He, Chengdu Huang, Brian M. Blum, John A. Stankovic, Tarek Abdelzaher, “Range-Free Localization Schemes for Large Scale Sensor Networks”, Proceedings of the 9th annual international conference on Mobile computing and networking, 2003.
[19] Neal Patwari, Alfred Hero, “Manifold Learning Algorithms for Localization in Wireless Sensor Networks”, IEEE. ICASSP 2004, vol. 3, pp. 857–860, May 2004.