| 研究生: |
謝政佑 Hsieh, Cheng-Yu |
|---|---|
| 論文名稱: |
結合社群網路輔助邀請之群播廣播服務多重費率計費方法 Multi-tariff Charging for Multicast and Broadcast Services with Social-assisted Invitation |
| 指導教授: |
蘇淑茵
Sou, Sok-Ian |
| 學位類別: |
碩士 Master |
| 系所名稱: |
電機資訊學院 - 電腦與通信工程研究所 Institute of Computer & Communication Engineering |
| 論文出版年: | 2012 |
| 畢業學年度: | 100 |
| 語文別: | 英文 |
| 論文頁數: | 52 |
| 中文關鍵詞: | 群播廣播服務 、小世界網路 、線上社群網路 、社群影響 |
| 外文關鍵詞: | MBS, small-world network, online social network, social influence |
| 相關次數: | 點閱:96 下載:1 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
次世代群播廣播服務可以經由共同連線傳向多重目的地的方式減少網路成本耗費。當一群線上使用者收到相同的群播廣播服務內容時,每個線上使用者的平均網路耗費成本可以大量減少。近來由於線上社群網路的興起,使得資訊可以經由大量人際間的聯絡溝通而傳遞出去。本篇論文主要在研究如何經由人與人之間的感染力來影響每個人對於使用群播廣播服務的態度與看法。我們提出了一個社群網路輔助邀請機制來模擬朋友間對於群播廣播服務內容看法的形成。在文章最後,我們以數據上的結果來說明我們的社群網路輔助邀請機制可以應用在分析群播廣播服務的多重費率計費方法上。
The next generation MBS could reduce the network cost through common access links towards multiple destinations. When a group of online users receive the same MBS content, the average MBS network cost per user can be significantly reduced. Recently, Online Social Network (OSN) provides new means of disseminating information through group of people via interpersonal communications. This thesis studies how the interpersonal influence that affects one's attitudes and opinions in MBS. We propose a social-assisted scheme to formulate the opinion on MBS content with friends. Numerical results demonstrate that the trend prediction from the social-assisted scheme about MBS user arrival can be used to analyze multi-tariff charging method for MBS.
[1] N. E. Friedkin and E. C. Johnsen, “Social influence networks and opinion change,” Advances in Group Processes, vol. 16, pp.1-29, 1999.
[2] P. Adams, “The Real Life Social Network,” Voices That Matter Web Design Conference, San Francisco, USA, 2010. http://www.slideshare.net/padday/the-real-life-social-network-v2, 2012.
[3] P. Erdös and A. Rényi, “On random graphs, I,” Publicationes Mathematicae (Debrecen), vol. 6, pp. 290-297, 1959.
[4] S. Milgram, “The Small World Problem,” Psychology Today, vol. 1, no. 1, pp. 61-67, 1967.
[5] D. J. Watts, and S. H. Strogatz, “Collective dynamics of ‘small-world’ networks,” Nature, vol. 393, pp. 440-442, 1998.
[6] A.-L. Barabási and R. Albert, “Emergence of Scaling in Random Networks,” Science, vol. 286, no. 5439, pp. 509-512, 1999.
[7] S. Qin and G.-Z. Dai, “A new local-world evolving network model,” Chinese Physics B, vol. 18, No. 2, pp.383-390, 2009.
[8] J. S. Andrade, Jr., H. J. Herrmann1, R. F. S. Andrade, and L. R. da Silva, “Apollonian Networks: Simultaneously Scale-Free, Small World, Euclidean, Space Filling, and with Matching Graphs,” Physical Review Letters, vol. 94, pp. 018702, 2005.
[9] R. Kumar, P. Raghavan, S. Rajagopalan, D. Sivakumar, A. Tomkins, and E. Upfal, “Stochastic models for the Web graph,” Proceeding of the 41st Annual Symposium on Foundations of Computer Science, pp.57-656, 2000.
[10] S. Ree, “Power-law distributions from additive preferential redistributions,” Physical Review E, vol. 73, 026115, 2006.
[11] D. Makowiec, “Evolving network - simulation study: From regular lattice to scale free network,” The European Physical Journal B, vol. 48, no. 4, pp. 547-555, 2005.
[12] M. E. J. Newman, “The Structure and Function of Complex Networks,” Society for Industrial and Applied Mathematics Review, vol. 45, no. 2, pp. 167-256, 2003.
[13] M. Newman, A.-L. Barabási, and D. J. Watts, The Structure and Dynamics of Networks, Princeton: Princeton University Press, 2006. ISBN: 978-0691113579 (624 pages) April 2006.
[14] A. Barrat, and M. Weigt, “On the properties of small-world network models,” The European Physical Journal B, vol. 13, no. 3, pp. 547-560, 2000.
[15] J. Pfeffer, K. M. Carley, “Modeling and calibrating real world interpersonal networks,” IEEE Network Science Workshop, pp.9-16, 2011.
[16] G. K. Zipf, Human Behavior and the Principle of Least Effort: An Introduction to Human Ecology, Addison-Wesley Press, 1949.
[17] P. Jaccard, “Étude comparative de la distribution florale dans une portion des Alpes et des Jura,” Bulletin del la Société Vaudoise des Sciences Naturelles, vol. 37, pp. 547-579, 1901.
[18] S.-I. Sou, C.-Y. Hsieh, F.-Y. Lee, Y.-F. Lin, J.-Y. Jeng, and C.-W. Cheng, “Design and Implementation of Dynamic Charging Plan for IMS-based Multicast Services,” The 13th Asia-Pacific Network Operations and Management Symposium, Taipei, Taiwan, 2011.
[19] S.-I. Sou, P. Lin, S.-S. Chen, and J.-Y Jeng, “A Novel Multi-tariff Charging Method for Next Generation Multicast and Broadcast Service.” The 31st International Conference on Computer Communications, Orlando, USA, 2012.
[20] P.-Y. Chen and K.-C. Chen, “Information Epidemics in Complex Network with Opportunistic Links and Dynamic Topology,” Global Telecommunications Conference, 2010.
[21] S.-M. Cheng, W.-C. Ao, P.-Y. Chen, and K.-C. Chen, “On Modeling Malware Propagation in Generalized Social Networks,” IEEE Communications Letters, vol. 15, no. 1, pp. 25-27, 2011.
[22] A. Goyal, F. Bonchi, and L. V. S. Lakshmanan, “Learning Influence Probabilities in Social Networks,” In Proceedings of the third ACM international conference on Web search and data mining, pp. 241–250, 2010.
[23] M. Fire, L. Tenenboim, O. Lesser, R. Puzis, L. Rokach, and Y. Elovici, “Link Prediction in Social Networks Using Computationally Efficient Topological Features,” IEEE The 3rd International Conference on Privacy, Security, Risk, and Trust, and IEEE The 3rd Conference on Social Computing, pp. 73-80, 2011.
[24] P. Hui, and S. Buchegger, “Groupthink and Peer Pressure: Social Influence in Online Social Network Groups,” International Conference on Advances in Social Network Analysis and Mining, pp. 53-59, 2009.
[25] S. Shang, P. Hui, S. R. Kulkarni, and P. W. Cuff, "Wisdom of the Crowd: Incorporating Social Influence in Recommendation Models," IEEE The 17th International Conference Parallel and Distributed Systems, pp. 835-840, 2011.
[26] G. K. Zipf, “Relative Frequency as a Determinant of Phonetic Change,” Reprinted from the Harvard Studies in Classical Philiology, vol. XL, 1929.
[27] L. Breslau, P. Cao, L. Fan, G. Phillips, and S. Shenker, “Web Caching and Zipf-like Distributions: Evidence and Implications,” The 18th International Conference on Computer Communications, vol. 1, pp.126-134, Mar. 1999.
[28] Y.-B. Lin, W.-R. Lai, J.-J. Chen, “Effects of Cache Mechanism on Wireless Data Access,” IEEE Transactions on Wireless Communications, vol. 2, no. 6, pp. 1247-1258, 2003.