由於耐延遲網路其節點間建立連線具有偶然性，無法保証來源端與目的端之間持續存在完整的點對點路由路徑，因此資料訊息的傳播有賴於節點移動間的相遇，在短暫的相遇期間訊速地傳送攜帶的資料訊息。而在群播的環境下，如果考量到必須多個目的端收到訊息之成功率(群播傳遞成功率)，整個群播目的端收到訊息的延遲時間即是最後收到訊息之目的端的延遲時間，那麼單一目的端的worst-case delay 即需要加以考量，而根據文獻顯示，訊息編碼機制即可減少worst-case delay 的問題。因此為了能夠改善耐延遲網路資訊傳播的效率和可靠性，本論文深入研究訊息編碼機制應用在耐延遲網路群播環境下的適用性，研究內容首先探討訊息編碼機制的基本型-來源編碼機制在訊息單播與群播環境下的特性，透過數學分析得到來源編碼隨著目的端數之增加，其延遲時間的效能比使用訊息複制機制還來得佳，並以實驗佐証此一性質。接著透過此性質，進一步研究訊息編碼機制中較複雜的網路編碼機制，雖然網路編碼機制可改善來源編碼機制的延遲時間效能，但同時亦因為執行編碼重組而需較多的傳輸花費，因此本論文亦提出利用訊息編碼重組條件之資料傳播機制，透過編碼重組條件減少傳輸花費的機制，使得不僅維持較佳的延遲時間效能，亦可降低傳輸訊息量。最後，本研究透過模擬來驗証不同參數對於網路編碼機制的影響，觀察其在延遲時間和傳輸花費這兩項效能指標上的表現，可以得到其在多目的端的環境下，有著較佳的延遲時間。雖然網路編碼機制其傳輸花費略高，但是所占用系統的儲存空間較小，使其在儲存空間有限的環境下，亦擁有較佳的效能表現。

Delay tolerant networks (DTNs) are a type of challenged networks with property of intermittent connectivity because of nodes’occasional contacts during movement in networks. It is very difficult for DTN systems to guarantee any persistent end-to-end routing path between a source and a destination node. Thus the data dissemination in DTNs exploits the nodal mobility to assist the data transferring. In the multicasting scenario, as regards multicasting for many destination nodes, the delay is counted till the last destination gets the message. So it is necessary to consider the worst-case delay problem for last destination. According to the previous studies, the message coding scheme significantly improves the worst case delay. To improve the efficient data dissemination in DTNs, this study seeks to exploit the essence of the message coding scheme for multicasting in DTN environments. First, with the order statistic principle, this study derives the mathematic formulations of deliver delay distribution for message multicasting using the basic message coding approach-source coding. As the number of destination nodes increase, the performance gain can become better in terms of delivery delay. Second, this study investigates the functions of complex message coding approach-network coding for message delivery in DTN. Although network coding approach has better delivery latency than source coding approach, it cause more transmitting traffic by “remix” scheme. The remix scheme is used to overcome the dependence of code blocks. Then this study proposed a novel remix qualification algorithm to reduce the transmitting traffic when using the remix scheme. Finally, this study conducts simulations to evaluate the performance sensitivities to the metrics of message delivery latency and transmitting traffic under a variety of coding parameters. The results demonstrate that proposed network coding based data dissemination has lower delivery latency than message replication based in multicasting scenario. Although network coding based cause more transmitting traffic, it occupies little buffer than others. Therefore network coding based data dissemination has considerable improvement while the buffer is constrained.

[1] G. Zussman and A. Segall, “Energy efficient routing in ad hoc disaster recovery networks,”in Proc. of IEEE INFOCOM, vol. 1, 2003, pp. 682–691.
[2] P. Jacquet, P. Muhlethaler, T. Clausen, A. Laouiti, A. Qayyum, and L. Viennot, “Optimized link state routing protocol for ad hoc networks,” in Proc. of IEEE International Multitopic Conference, 2001, pp. 62–68.
[3] C. E. Perkins and E. M. Royer, “Ad-hoc on-demand distance vector routing,” in Proc. Of IEEE Workshop on Mobile Computing Systems and Applications, 1999, pp. 90–100.
[4] D. B. Johnson and D. A. Maltz, “Dynamic source routing in ad hoc wireless networks,” in Mobile Computing, ser. The Kluwer International Series in Engineering and Computer Science. Springer US, 1996, vol. 353, pp. 153–181.
[5] Z. Zhang, “Routing in intermittently connected mobile ad hoc networks and delay tolerant networks: Overview and challenges,” IEEE Communications Surveys Tutorials, vol. 8, no. 1, pp. 24–37, 2006.
[6] T. Spyropoulos, R. N. B. Rais, T. Turletti, K. Obraczka, and A. Vasilakos, “Routing for
disruption tolerant networks: Taxonomy and design,” Wireless Networks, vol. 16, no. 8, pp. 2349–2370, 2010.
[7] Y. Wang, S. Jain, M. Martonosi, and K. Fall, “Erasure-coding based routing for opportunistic networks,” in Proc. of ACM SIGCOMM Workshop on Delay-Tolerant Networking, 2005, pp. 229–236.
[8] W. Zhao, M. Ammar, and E. Zegura, “Multicasting in delay tolerant networks: semantic models and routing algorithms,” in Proc. of ACM SIGCOMM Workshop on Delay-Tolerant Networking, 2005, pp. 268–275.
[9] Y. Xi and M. C. Chuah, “An encounter-based multicast scheme for disruption tolerant networks,” Elsevier Comput. Commun., vol. 32, no. 16, pp. 1742–1756, 2009.
[10] Y. Wang, X. Li, and J. Wu, “Multicasting in delay tolerant networks: Delegation forwarding,” in Proc. of IEEE GLOBECOM, Dec. 2010.
[11] W. Gao, Q. Li, B. Zhao, and G. Cao, “Multicasting in delay tolerant networks: a social network perspective,” in Proc. of ACM MobiHoc, 2009, pp. 299–308.
[12] J. Santiago, A. Casaca, and P. R. Pereira, “Multicast in delay tolerant networks using probabilities and mobility information,” Ad Hoc & Sensor Wireless Networks, An International Journal, vol. 7, no. 1-2, pp. 51–68, 2009.
[13] M. Grossglauser and D. N. C. Tse, “Mobility increases the capacity of ad hoc wireless networks,” IEEE/ACM Transactions on Networking, vol. 10, no. 4, pp. 477–486, Aug.2002.
[14] A. Vahdat and D. Becker, “Epidemic routing for partially connected ad hoc networks,” Duke University, Tech. Rep. CS-200006, 2000.
[15] T. Spyropoulos, K. Psounis, and C. S. Raghavendra, “Spray and wait: An efficient routing scheme for intermittently connected mobile networks,” in Proc. of ACM SIGCOMM Workshop on Delay-Tolerant Networking, 2005, pp. 252–259.
[16] U. Lee, S. Y. Oh, K.-W. Lee, and M. Gerla, “Relaycast: Scalable multicast routing in delay tolerant networks,” in Proc. of IEEE ICNP, Oct. 2008, pp. 218–227.
[17] A. Lindgren, A. Doria, and O. Schelen, “Probabilistic routing in intermittently connected networks,” ACM SIGMOBILE Mobile Computing and Communications Review, vol. 7, no. 3, pp. 19–20, Jul. 2003.
[18] V. Erramilli, M. Crovella, A. Chaintreau, and C. Diot, “Delegation forwarding,” in Proc. of ACM MobiHoc, 2008, pp. 251–260.
[19] M. Ma, Z. Zhang, X. An, C. Li, and Y. Cao, “Probability and receiver list based multicast routing in dtns,” in Proc. of IEEE International Conference on Advanced Communication Technology, vol. 1, Feb. 2010, pp. 23–26.
[20] L.-J. Chen, C.-H. Yu, T. Sun, Y.-C. Chen, and H. hua Chu, “A hybrid routing approach for opportunistic networks,” in Proc. of ACM Workshop on Challenged Networks, 2006, pp. 213–220.
[21] S. Jain, M. Demmer, R. Patra, and K. Fall, “Using redundancy to cope with failures in a delay tolerant network,” in Proc. of ACM SIGCOMM, 2005, pp. 109–120.
[22] Y. Liao, K. Tan, Z. Zhang, and L. Gao, “Estimation based erasure-coding routing in delay tolerant networks,” in Proc. of ACM International Conference on Wireless Communications and Mobile Computing, 2006, pp. 557–562.
[23] Y. Liao, Z. Zhang, B. Ryu, and L. Gao, “Cooperative robust forwarding scheme in dtns using erasure coding,” in Proc. of IEEE Military Communications Conference, 2007.
[24] E. Bulut, Z. Wang, and B. K. Szymanski, “Cost efficient erasure coding based routing in delay tolerant networks,” in Proc. of IEEE ICC, 2010.
[25] R. Ahlswede, N. Cai, S.-Y. R. Li, and R. W. Yeung, “Network information flow,” IEEE Transactions on Information Theory, vol. 46, no. 4, pp. 1204–1216, Jul. 2000.
[26] S. Katti, H. Rahul, W. Hu, D. Katabi, M. Medard, and J. Crowcroft, “Xors in the air: Practical wireless network coding,” IEEE/ACM Transactions on Networking, vol. 16, no. 3, pp. 497–510, Jun. 2008.
[27] T. Ho, R. Koetter, M. Mkdard, D. R. Karger, and M. Effros, “The benefits of coding over routing in a randomized setting,” in Proc. of IEEE International Symposium on Information Theory, Jun. 2003, p. 442.
[28] J. Widmer and J.-Y. L. Boudec, “Network coding for efficient communication in extreme networks,” in Proc. of ACM SIGCOMM Workshop on Delay-Tolerant Networking, 2005, pp. 284–291.
[29] X. Zhang, G. N. J. Kurose, and D. Towsley, “On the benefits of random linear coding for unicast applications in disruption tolerant networks,” in Proc. of IEEE Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, 2006, pp. 1 – 7.
[30] Y. Lin, B. Liang, and B. Li, “Performance modeling of network coding in epidemic routing,” in Proc. of ACM international MobiSys workshop on Mobile opportunistic networking, 2007, pp. 67–74.
[31] Y. Lin, B. Li, and B. Liang, “Efficient network coded data transmissions in disruption tolerant networks,” in Proc. of IEEE INFOCOM, 2008, pp. 1508–1516.
[32] S. Ahmed and S. S. Kanhere, “Hubcode: message forwarding using hub-based network coding in delay tolerant networks,” in Proc. of ACM international conference on Modeling, analysis and simulation of wireless and mobile systems, 2009, pp. 288–296.
[33] Z. Narmawala and S. Srivastava, “Midtone: Multicast in delay tolerant networks,” in Proc. of IEEE International Conference on Communications and Networking in China, Aug. 2009, pp. 1 –8.
[34] A. Keranen, J. Ott, and T. Karkkainen, “The one simulator for dtn protocol evaluation,” in Proc. of International Conference on Simulation Tools and Techniques, 2009.
[35] K. Lee, S. Hong, S. J. Kim, I. Rhee, and S. Chong, “Slaw: A new mobility model for human walks,” in Proc. of IEEE INFOCOM, 2009, pp. 855–863.