臺灣博碩士論文加值系統

最近幾年來，無線感測器網路已經變成熱門研究之一。各式各樣的應用也逐漸被開發出來。而為了能夠更有效率的開發各種程式，需要一種適合無線感測器網路的程式模型。在這篇論文裡，我們設計了針對無線感測器網路的一種程式開發環境(SPE- sensor programming environment)。此SPE 裡包含著一個中介軟體，用來管理底層硬體並提供各種應用程式介面；除此之外，還包含者一個我們提出的以角色為主的程式設計模型，以提供高階抽象程式設計概念。使用者可以針對不同的應用，依據我們的程式模型，設計出各種角色圖表。藉由分析此圖表，可以更了解程式的執行流程，因而減少邏輯錯誤的可能性。在這篇論文之後，我們會秀出一個簡單的範例程式，結果可以指出SPE 和角色為主的程式模型的確能更有效率的設計各種無線感應器網路程式。

In recent years, the wireless sensor network has been one of the hottest research topics. Many different applications for different challenges have been developed. In order to reduce the efforts in programming, it is necessary to develop a new programming model suitable for the wireless sensor network. In this paper, we present a sensor programming environment (SPE) for users to write application programs for wireless sensor networks. The SPE includes a middleware, for hiding low-level operations and providing high level APIs for application programs, and a role-based programming library, for abstraction of programming design. A user can build up a role graph for his/her application program based on the role-based programming model. From the role graph of an application program, a user can write codes for each role and analyze the execution flow of the application program. We have shown a design example by using the proposed SPE. The simulation results indicate that the proposed SPE is easy to use and the role-based programming model can reduce the design efforts of a WSN program.

Contents
Chapter 1 Introduction..................................1
Chapter 2 Related Work..................................4
Chapter 3 The Middleware of SPE.........................6
3.1 The System Architecture of Middleware ..............6
3.2 The Behavior of SPE Middleware .....................9
3.3 An example of the usage of the Middleware APIs.....11
Chapter 4 The Role-Based Programming Model.............16
4.1 Programming Model .................................16
4.2 The Role-Based Programming Library.................18
Chapter 5 Design Example...............................20
5.1 Model the Problem..................................20
5.2 Algorithm .........................................21
5.3 Simulation Results ................................22
Chapter 6 Conclusions..................................25
References ............................................26

[1] Alan Mainwaring, David Culler, Joseph Polastre, Robert Szewczyk, John Anderson, “Wireless sensor networks for habitat monitoring”, Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications, September 2002.
[2] Ana Paula R. da Silva, Marcelo H. T. Martins, Bruno P. S. Rocha, Antonio A. F. Loureiro, Linnyer B. Ruiz, Hao Chi Wong, “Decentralized intrusion detection in wireless sensor networks”, Proceedings of the 1st ACM international workshop on Quality of service & security in wireless and mobile networks, October 2005.
[3] Chalermek Intanagonwiwat, Ramesh Govindan, Deborah Estrin, John Heidemann, Fabio Silva, “Directed diffusion for wireless sensor networking”, IEEE/ACM Transactions on Networking, February 2003.
[4] David Gay, Philip Levis, Robert von Behren, Matt Welsh, Eric Brewer, David Culler, “The nesC language: A holistic approach to networked embedded systems”, Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation.
[5] Jason Hill, Mike Horton, Ralph Kling, Lakshman Krishnamurthy, “The platforms enabling wireless sensor networks”, in Communications of the ACM, Volume 47, Issue 6 (June 2004). Wireless sensor networks SPECIAL ISSUE: Wireless sensor networks table of contents, Pages: 41 – 46.
[6] J. Liu, M. Chu, J. Liu, J. Reich, and F. Zhao in Palo Alto Research Center, “State-centric programming for sensor-actuator network systems” published by the IEEE CS and IEEE ConSoc, 2003.
[7] Matt Welsh and Geoff Mainland, “Programming Sensor Networks Using Abstract Regions”, In Proceedings of the First USENIX/ACM Symposium on Networked Systems Design and Implementation (NSDI '04), March 2004.
[8] Matt Welsh, Geoff Werner-Allen, Konrad Lorincz, Omar Marcillo, Jeff Johnson, Mario Ruiz, Jonathan Lees, “Sensor networks for high-resolution monitoring of volcanic activity”, Proceedings of the twentieth ACM symposium on Operating systems principles, October 2005.
[9] Ryan Newton and Matt Welsh, “Region Streams: Functional Macroprogramming for Sensor Networks”, To appear in Proceedings of the First International Workshop on Data Management for Sensor Networks (DMSN), Toronto, Canada, August 2004.
[10] “Macroprogramming Myriads of Sensors”. This project is proposed from EECS, Harvard University, and supported by the National Science Foundation. For more information, see http://www.eecs.harvard.edu/~mdw/proj/mp/
[11] “TinyOS” is an open-source operating system designed for wireless embedded sensor networks. It was initially developed by the U.C. Berkeley EECS Department. For more information, see http://www.tinyos.net/