隨著科技與工業技術的進步，許多微小的無線感測裝置被應用在廣泛的領域，從戰場敵我偵測到博物館的導覽系統都可見其蹤跡。而異質性的感測器網路更是近年來被研究的重點。由於感測器通常配置電池以便布置，所以能源成為這種感測器網路的主要限制之一。正因為如此，在提高系統的效能(throughput)的同時，兼顧整個系統的使用壽命(system lifetime)也是我們的目標，這篇論文即在藉由建造一覆疊式網路(overlay network)來探討兩者間的關係以及適當的取捨。
在這篇論文所考慮的異質性網路中包含兩種類型的感測器，其一為配備電池因此能源受限的感測器(powerless sensors)，另一種感測器擁有遠大於前者的電量，例如此種感測器配有供電器。我們希望在後者這些能源多的感測器中(powerful sensors)建立一覆疊式的網路，在此網路中的每一條連結(link)都是以數個能源受限的感測器所組成。利用此基底結構提供資源找尋(resource discovery)或者廣播(broadcast)的服務。我們相信這種覆疊式的架構可有效提升訊息延遲(message latency)以及平衡感測器的能源消耗(energy consumption)。我們首先提出三種集中式建構的覆疊式網路，並經由數學以及程式模擬分析來觀察訊息延遲和能源消耗間的權衡(tradeoff)。藉由以上的比較，我們接著提出一分散式的覆疊網路建構協定(overlay construction protocol)，其目標為建構一短徑(low diameter)且將路由負載平均的散佈在能源受限的感測器上。主要的精神即藉由變動鄰居的數目(neighbor threshold)來改變此覆疊式網路的深度(depth)。
我們經由實驗和前述兩種集中式的方法相比，模擬結果顯示我們的方法不僅可達到較短的訊息延遲，對於負責轉送訊息的感測器(forwarding sensors)而言，且同時減少他們的能源消耗。

Heterogeneous sensor network has received a lot of attention in recent years due to its wide range of applications from battlefield to museum guide. Since wireless sensors are often powered by batteries, energy resource of the nodes is a major constraint of the wireless sensor networks. To prolong the system lifetime, it is important to maximizing the system throughput while still maintaining the node life time. \par In this study we consider a heterogeneous sensor network containing at least two types of sensors: one type of sensors is powered by batteries with limited energy, and the other is more powerful sensors which have much higher energy capacity. The powerful sensors may be used for gateways or controllers in the network. To facilitate the communication of the powerful sensors, it is necessary to build an overlay on top of the sensor network to link the powerful sensors. Given that the powerful sensors are still limited in the communication range and their communications with each other require the less powerful sensors in between for message relaying, the problem of determining the overlay topology becomes critical. This overlay must have low diameter so that it can efficiently support upper layer applications, such as resource discovery. In addition, it must consider the energy consumption of the underlying less-powerful, relaying sensors and spread the routing load evenly among the relaying sensors to prolong the system lifetime. In this thesis, we propose a distributed overlay formation protocol to achieve the above goals. Through simulation, we compare our protocol with two overlay formation protocols, {\it fully connected graph} and {\it minimum spanning tree}. The results show that our proposed protocol can achieve better performance both in message latency and energy consumption.

[1] E. J. Duarte-Melo and R. Albert. Analysis of Energy Consumption and Lifetime of Heterogeneous
Wireless Sensor Networks. In Proceedings of IEEE Global Telecommunications
Conference, 2002.
[2] F. P. Franciscani, M. A. Vasconcelos, R. P. Couto, and A. A. F. Loureiro. Peer-to-peer over
ad-hoc networks: (re)configuration algorithms. In Proceedings of 17th IEEE International
Parallel and Distributed Processing Symposium, April 2003.
[3] Gnutella. http://rfc-gnutella.sourceforge.net/.
[4] Xiaoxing Guo. Broadcasting for network lifetime maximization in wireless sensor network.
In Proceedings of First Annual IEEE Communications Society Conference on Sensor and
Ad Hoc Communications and Networks, pages 352–358, Oct 2004.
[5] J. Hassan and S. Jha. Optimising expanding ring search for multi-hop wireless networks.
In Proceedings of IEEE Global Telecommunications Conference, pages 1061–1065, Dec
2004.
[6] W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan. Energy-efficient communication
protocol for wireless microsensor networks. In Proceedings of the 33rd Annual Hawaii
International Conference on System Sciences, Jan 2000.
[7] S.-C. Huang and R.-H. Jan. Energy-aware, load balanced routing schemes for sensor networks.
In Proceedings of Tenth International Conference on Parallel and Distributed Systems,
pages 419–425, July 2004.
[8] U. C. Kozat and L. Tassiulas. Network layer support for service discovery in mobile ad hoc
networks. In Proceedings of IEEE INFOCOM, pages 1965–1975, April 2003.
38
[9] Y. Ma and J. H. Aylor. System lifetime optimization for heterogeneous sensor networks
with a hub-spoke technology. IEEE Transaction on Mobile Computing, 3(3):286–294, July
2004.
[10] V. Mhatre and C. Rosenberg. Homogeneous vs heterogeneous clustered sensor networks: a
comparative study. In Proceedings of IEEE International Conference on Communications,
pages 3646 –3651, June 2004.
[11] V. P. Mhatre, C. Rosenberg, D. Kofman, R. Mazumdar, and N. Shroff. A minimum cost
heterogeneous sensor network with a lifetime constraint. IEEE Transaction of Mobile Computing,
4(1):4–15, January 2005.
[12] M. J. Miller and N. H. Vaidya. Minimizing energy consumption in sensor network using a
wakeup radio. In Proceedings of IEEE Wireless Communications and Networking Conference,
pages 2335–2340, March 2004.
[13] R. Neapolitan and K. Naimipour. Foundations of Algorithms, using C++ pseudocode, chapter
Computational Complexity and Intractability: An Introduction to the Theory of NP.
Jones and Bartlett, 1998.
[14] Ns2. http://www.isi.edu/nsnam/ns/.
[15] V. D. Park and M. S. Corson. A highly adaptive distributed routing algorithm for mobile
wireless networks. In Proceedings of INFOCOM, pages 1405–1413, April 1997.
[16] C. E. Perkins and E. M. Royer. Ad-hoc on-demand distance vector routing. In Proceedings
of Second IEEE Workshop on Mobile Computing Systems and Applications, pages 90–100,
Feb 1999.
[17] R. C. Shah and J. M. Rabaey. Energy aware routing for low energy ad hoc sensor network.
In Proceedings of Wireless Communications and Networking Conference, pages 350–355,
March 2002.
39
[18] M. Singh and V. K. Prasanna. A Hierarchical Model for Distributed Collaborative Computation
in Wireless Sensor Networks. In Proceedings of International Parallel and Distributed
Processing Symposium, April 2003.
[19] P. Sinha, R. Sivakumar, and V. Bharghava. Cedar: a core-extraction distributed ad hoc
routing algorithm. IEEE Journal on Selected Areas in Communications, 17(8):1454–1465,
Aug 1999.
[20] J.Wu and H. Li. On calculating connected dominating set for efficient routing. In Proceedings
of the Third International Workshop on Discrete Algorithms and Methods for Mobile
Computing and Communications, Aug 1999.
[21] M. A. Youssef, M. F. Younis, and K. A. Arisha. A constrained shortest-path energy-aware
routing algorithm for wireless sensor networks. In Proceedings ofWireless Communications
and Networking Conference, pages 794–799, March 2002.