Skip navigation

DSpace

機構典藏 DSpace 系統致力於保存各式數位資料(如:文字、圖片、PDF)並使其易於取用。

點此認識 DSpace
DSpace logo
English
中文
  • 瀏覽論文
    • 校院系所
    • 出版年
    • 作者
    • 標題
    • 關鍵字
  • 搜尋 TDR
  • 授權 Q&A
    • 我的頁面
    • 接受 E-mail 通知
    • 編輯個人資料
  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 資訊工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/44907
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor呂育道(Yuh-Dauh Lyuu)
dc.contributor.authorChing-Lueh Changen
dc.contributor.author張經略zh_TW
dc.date.accessioned2021-06-15T03:57:58Z-
dc.date.available2015-06-11
dc.date.copyright2010-06-11
dc.date.issued2010
dc.date.submitted2010-05-28
dc.identifier.citation[1] Z. Agur. Resilience and variability in pathogens and hosts. IMA Journal on Mathematical Medicine and Biology, 4(4):295–307, 1987.
[2] Z. Agur. Fixed points of majority rule cellular automata with application to plasticity and precision of the immune system. Complex Systems, 5(3):351–357, 1991.
[3] Z. Agur, A. S. Fraenkel, and S. T. Klein. The number of fixed points of the majority rule. Discrete Mathematics, 70(3):295–302, 1988.
[4] W. Aiello, F. Chung, and L. Lu. Random evolution in massive graphs. In J. Abello, P. M. Pardalos, and M. G. C. Resende, editors, Handbook of Massive Data Sets, pages 97–122. Kluwer Academic Publishers, 2002.
[5] R. Albert and A.-L. Barab’asi. Statistical mechanics of complex networks. Reviews of Modern Physics, 74(1):47–97, 2002.
[6] H. Attiya and J. Welch. Distributed Computing: Fundamentals, Simulations and Advanced Topics. John Wiley & Sons, 2004.
[7] B. Awerbuch and C. Scheideler. Towards a scalable and robust DHT. Theory of Computing Systems, 45(2):234–260, 2009.
[8] Y. Azar, S. Kutten, and B. Patt-Shamir. Distributed error confinement. In Proceedings of the 22nd Symposium on Principles of Distributed Computing, pages 33–42, 2003.
[9] L. Backstrom, D. Huttenlocher, J. Kleinberg, and X. Lan. Group formation in large social networks: membership, growth, and evolution. In Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 44–54, 2006.
[10] A.-L. Barab’asi and R. Albert. Emergence of scaling in random networks. Science, 286(5439):509–512, 1999.
[11] A. Barrat, M. Barth’elemy, and A. Vespignani. Traffic-driven model of the World Wide Web graph. In Proceedings of the 3rd International Workshop on Algorithms and Models for the Web-Graph, pages 56–67, 2004.
[12] E. Berger. Dynamic monopolies of constant size. Journal of Combinatorial Theory Series B, 83(2):191–200, 2001.
[13] J.-C. Bermond, J. Bond, D. Peleg, and S. Perennes. The power of small coalitions in graphs. Discrete Applied Mathematics, 127(3):399–414, 2003.
[14] Y. Birk, L. Liss, A. Schuster, and R. Wolff. A local algorithm for ad hoc majority voting via charge fusion. In Proceedings of the 18th International Symposium on Distributed Computing, pages 275–289, 2004.
[15] D. M. Blough, G. F. Sullivan, and G. M. Masson. Efficient diagnosis of multiprocessor systems under probabilistic models. IEEE Transactions on Computers, 41(9):1126–1136, 1992.
[16] A. Blum, T.-H. H. Chan, and M. R. Rwebangira. A random-surfer web-graph model. In Proceedings of the 8th Workshop on Algorithm Engineering and Experiments, pages 238–246, 2006.
[17] L. E. Blume. The statistical mechanics of strategic interaction. Games and Economic Behavior, 5(3):387–424, 1993.
[18] B. Bollob’as. Random Graphs. Cambridge University Press, 2nd edition, 2001.
[19] B. Bollob’as, O. Riordan, J. Spencer, and G. Tusn’ady. The degree sequence of a scale-free random graph process. Random Structures and Algorithms, 18(3):279–290, 2001.
[20] A. Bonato and J. Janssen. Infinite limits of copying models of the web graph. Internet Mathematics, 1(2):193–213, 2004.
[21] A. Bonato and J. Janssen. Limits and power laws of models for the web graph and other networked information spaces. In A L’opez-Ortiz and A. Hamel, editors, Proceedings of the 1st Workshop on Combinatorial and Algorithmic Aspects of Networking, pages 42–48. Springer-Verlag Berlin Heidelberg, 2004.
[22] A. Bonato and J. Janssen. A survey of models of the web graph. In A L’opez-Ortiz and A. Hamel, editors, Proceedings of the 1st Workshop on Combinatorial and Algorithmic Aspects of Networking, pages 159–172. Springer-Verlag Berlin Heidelberg, 2004.
[23] E. Boros and V. Gurvich. On complexity of algorithms for modeling disease transmission and optimal vaccination strategy. Technical Report 2007-06, NSF Center for Discrete Mathematics and Theoretical Computer Science, Rutgers University, New Jersey, 2007.
[24] G. Bracha. An o(log n) expected rounds randomized Byzantine generals protocol. Journal of the Association for Computing Machinery, 34(4):910–920, 1987.
[25] D. Centola, V. M. Egu’ıluz, and M. W. Macy. Cascade dynamics of complex propagation. Physica A: Statistical Mechanics and its Applications, 374(1):449–456, 2007.
[26] M. Cha, A. Mislove, and K. P. Gummadi. A measurement-driven analysis of information propagation in the Flickr social network. In Proceedings of the 18th International Conference on World Wide Web, pages 721–730, 2009.
[27] C.-L. Chang and Y.-D. Lyuu. Spreading messages. Theoretical Computer Science, 410(27–29):2714–2724, 2009.
[28] C.-L. Chang and Y.-D. Lyuu. Spreading of messages in random graphs. In R. Downey and P. Manyem, editors, Proceedings of the 15th Computing: The Australasian Theory Symposium, volume 94 of CRPIT, pages 3–7, Wellington, New Zealand, 2009. Australian Computer Society.
[29] C.-L. Chang and Y.-D. Lyuu. Bounding the number of tolerable faults in majority-based systems. In T. Calamoneri and J. D’ıaz, editors, Proceedings of the 7th International Conference on Algorithms and Complexity, pages 109–119, Rome, Italy, 2010. Springer-Verlag Berlin Heidelberg.
[30] P. Chebolu and P. Melsted. PageRank and the random surfer model. In Proceedings of the 19th Annual ACM-SIAM Symposium on Discrete Algorithms, pages 1010–1018, 2008.
[31] H. Chernoff. A measure of the asymptotic efficiency of tests of a hypothesis based on the sum of observations. Annals of Mathematical Statistics, 23:493–507, 1952.
[32] F. Chung and L. Lu. Connected components in random graphs with given expected degree sequences. Annals of Combinatorics, 6(2):125–145, 2002.
[33] F. Chung and L. Lu. Coupling online and offline analyses for random power law graphs. Internet Mathematics, 1(4):409–461, 2003.
[34] F. Chung and L. Lu. The average distance in a random graph with given expected degrees. Internet Mathematics, 1(1):91–114, 2004.
[35] F. Chung and L. Lu. The small world phenomenon in hybrid power law graphs. In E. Ben-Naim, H. Frauenfelder, and Z. Toroczkai, editors, Complex Networks, pages 89–104. Springer-Verlag Berlin Heidelberg, 2004.
[36] C. Cooper, A. M. Frieze, and J. Vera. Random deletion in a scale-free random graph process. Internet Mathematics, 1(4):463–483, 2003.
[37] T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein. Introduction to Algorithms. The MIT Press, 2nd edition, 2001.
[38] S. B. Davidson, H. Garcia-Molina, and D. Skeen. Consistency in a partitioned network: a survey. ACM Computing Surveys, 17(3):341–370, 1985.
[39] K. Diks and A. Pelc. System diagnosis with smallest risk of error. Theoretical Computer Science, 203(1):163–173, 1998.
[40] P. S. Dodds and D. J. Watts. Universal behavior in a generalized model of contagion. Physical Review Letters, 92(21):218701–1 to 218701–4, 2004.
[41] P. S. Dodds and D. J. Watts. A generalized model of social and biological contagion. Journal of Theoretical Biology, 232(4):587–604, 2005.
[42] D. Dolev. The Byzantine generals strike again. Journal of Algorithms, 3(1):14–30, 1982.
[43] D. Donato, L. Laura, S. Leonardi, and S. Millozzi. Simulating the Webgraph: A comparative analysis of models. Computing in Science and Engineering, 6(6):84–89, 2004.
[44] P. A. Dreyer and F. S. Roberts. Irreversible k-threshold processes: Graph-theoretical threshold models of the spread of disease and of opinion. Discrete Applied Mathematics, 157(7):1615–1627, 2009.
[45] C. Dwork, D. Peleg, N. Pippenger, and E. Upfal. Fault tolerance in networks of bounded degree. SIAM Journal on Computing, 17(5):975–988, 1988.
[46] G. Ellison. Learning, local interaction, and coordination. Econometrica, 61(5):1047–1071, 1993.
[47] A. Fabrikant, E. Koutsoupias, and C. H. Papadimitriou. Heuristically optimized trade-offs: A new paradigm for power laws in the Internet. In Proceedings of the 29th International Colloquium on Automata, Languages and Programming, pages 110–122, 2002.
[48] U. Feige. A threshold of ln n for approximating set cover. Journal of the Association for Computing Machinery, 45(4):634–652, 1998.
[49] A. D. Flaxman, A. M. Frieze, and J. Vera. Adversarial deletion in a scale-free random graph process. Combinatorics, Probability and Computing, 16(2):261–270, 2007.
[50] P. Flocchini. Contamination and decontamination in majority-based systems. Journal of Cellular Automata, 4(3):183–200, 2009.
[51] P. Flocchini, F. Geurts, and N. Santoro. Optimal irreversible dynamos in chordal rings. Discrete Applied Mathematics, 113(1):23–42, 2001.
[52] P. Flocchini, R. Kr’aloviˇc, P. Ruˇziˇcka, A. Roncato, and N. Santoro. On time versus size for monotone dynamic monopolies in regular topologies. Journal of Discrete Algorithms, 1(2):129–150, 2003.
[53] P. Flocchini, E. Lodi, F. Luccio, L. Pagli, and N. Santoro. Dynamic monopolies in tori. Discrete Applied Mathematics, 137(2):197–212, 2004.
[54] H. Garcia-Molina and D. Barbara. How to assign votes in a distributed system. Journal of the Association for Computing Machinery, 32(4):841–860, 1985.
[55] D. K. Gifford. Weighted voting for replicated data. In Proceedings of the 7th ACM Symposium on Operating Systems Principles, pages 150–162, 1979.
[56] Y. Ginosar and R. Holzman. The majority action on infinite graphs: strings and puppets. Discrete Mathematics, 215(1–3):59–71, 2000.
[57] J. P. Gleeson and D. J. Cahalane. Seed size strongly affects cascades on random networks. Physical Review E, 75(056103), 2007.
[58] E. Goles and J. Olivos. Periodic behavior of generalized threshold functions. Discrete Mathematics, 30(2):187–189, 1980.
[59] E. Goles-Chacc, F. Fogelman-Soulie, and D. Pellegrin. Decreasing energy functions as a tool for studying threshold networks. Discrete Applied Mathematics, 12(3):261–277, 1985.
[60] R. L. Graham, D. E. Knuth, and O. Patashnik. Concrete Mathematics: A Foundation for Computer Science. Addison-Wesley, 1994.
[61] M. Granovetter. Threshold models of collective behavior. The American Journal of Sociology, 83(6):1420–1443, 1978.
[62] A. Granville. On a paper by Agur, Fraenkel and Klein. Discrete Mathematics, 94(2):147–151, 1991.
[63] T. J. Harris. A survey of PRAM simulation techniques. ACM Computing Surveys, 26(2):187–206, 1994.
[64] M. Herlihy. A quorum-consensus replication method for abstract data types. ACM Transactions on Computer Systems, 4(1):32–53, 1986.
[65] D. Kempe, J. Kleinberg, and ’ E. Tardos. Maximizing the spread of influence through a social network. In Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 137–146, 2003.
[66] D. Kempe, J. Kleinberg, and ’ E. Tardos. Influential nodes in a diffusion model for social networks. In Proceedings of the 32nd International Colloquium on Automata, Languages and Programming, pages 1127–1138, 2005.
[67] J. Kleinberg. The small-world phenomenon: An algorithm perspective. In Proceedings of the 32nd Annual ACM Symposium on Theory of Computing, pages 163–170, 2000.
[68] J. Kleinberg, R. Kumar, P. Raghavan, S. Rajagopalan, and A. Tomkins. The web as a graph: Measurements, models, and methods. In Proceedings of the 5th Annual International Computing and Combinatorics Conference, pages 1–17, 1999.
[69] R. Kr’aloviˇc. On majority voting games in trees. In Proceedings of the 28th Conference on Current Trends in Theory and Practice of Informatics Piestany: Theory and Practice of Informatics, pages 282–291, 2001.
[70] R. Kr’aloviˇc and P. Ruˇziˇcka. On immunity and catastrophic indices of graphs. In Proceedings of the 8th International Colloquium on Structural Information and Communication Complexity, pages 231–242, 2001.
[71] R. Kumar, P. Raghavan, S. Rajagopalan, D. Sivakumar, A. Tomkins, and E. Upfal. Stochastic models for the web graph. In Proceedings of the 41st Annual Symposium on Foundations of Computer Science, pages 57–65, 2000.
[72] S. Kutten and D. Peleg. Fault-local distributed mending. Journal of Algorithms, 30(1):144–165, 1999.
[73] S. Kutten and D. Peleg. Tight fault locality. SIAM Journal on Computing, 30(1):247–268, 2000.
[74] J. Kynˇcl, B. Lidick’y, and T. Vyskoˇcil. Irreversible 2-conversion set is NP-complete. Technical Report KAM-DIMATIA Series 2009-933, Department of Applied Mathematics, Charles University, Prague, Czech Republic, 2009.
[75] L. Lamport, R. Shostak, and M. Pease. The Byzantine generals problem. ACM Transactions on Programming Languages and Systems, 4(3):382–401, 1982.
[76] S. Lee and K. G. Shin. Probabilistic diagnosis of multiprocessor systems. ACM Computing Surveys, 26(1):121–139, 1994.
[77] J. Leskovec, L. A. Adamic, and B. A. Huberman. The dynamics of viral marketing. ACM Transactions on the Web, 1(1), 2007. Article 5.
[78] J. Leskovec, M. McGlohon, C. Faloutsos, N. Glance, and M. Hurst. Cascading behavior in large blog graphs. In Proceedings of the 7th SIAM International Conference on Data Mining, pages 551–556, 2007.
[79] J. Leskovec, A. Singh, and J. Kleinberg. Patterns of influence in a recommendation network. In Pacific-Asia Conference on Knowledge Discovery and Data Mining, pages 380–389, 2005.
[80] N. Linial, D. Peleg, Y. Rabinovich, and M. Saks. Sphere packing and local majorities in graphs. In Proceedings of the 2nd Israel Symposium on Theory of Computing Systems, pages 141–149, 1993.
[81] F. Luccio and L. Pagli. Web marshals fighting curly link farms. In Proceedings of the 4th International Conference on Fun with Algorithms, pages 240–248, 2007.
[82] F. Luccio, L. Pagli, and H. Sanossian. Irreversible dynamos in butterflies. In Proceedings of the 6th International Colloquium on Structural Information & Communication Complexity, pages 204–218, 1999.
[83] F. Luccio, L. Pagli, and N. Santoro. Network decontamination in presence of local immunity. International Journal of Foundations of Computer Science, 18(3):457–474, 2007.
[84] N. A. Lynch. Distributed Algorithms. Morgan Kaufmann, 1996.
[85] D. McFadden. Conditional logit analysis of qualitative choice behavior. In P. Zarembka, editor, Frontiers of Econometrics, pages 105–142. Academic Press, New York, 1974.
[86] M. Mitzenmacher and E. Upfal. Probability and Computing: Randomized Algorithms and Probabilistic Analysis. Cambridge University Press, 2005.
[87] A. Montanari and A. Saberi. Convergence to equilibrium in local interaction games. In Proceedings of the 50th Annual IEEE Symposium on Foundations of Computer Science, pages 303–312, 2009.
[88] G. Moran. Parametrization for stationary patterns of the r-majority operators on 0-1 sequences. Discrete Mathematics, 132(1–3):175–195, 1994.
[89] G. Moran. The r-majority vote action on 0-1 sequences. Discrete Mathematics, 132(1–3):145–174, 1994.
[90] G. Moran. On the period-two-property of the majority operator in infinite graphs. Transactions of the American Mathematical Society, 347(5):1649–1667, 1995.
[91] S. Morris. Contagion. Review of Economic Studies, 67(1):57–78, 2000.
[92] E. Mossel and S. Roch. On the submodularity of influence in social networks. In Proceedings of the 39th Annual ACM Symposium on Theory of Computing, pages 128–134, 2007.
[93] R. Motwani and P. Raghavan. Randomized Algorithms. Cambridge University Press, 1995.
[94] R. Motwani and Y. Xu. Evolution of page popularity under random web graph models. In Proceedings of the 25th ACM SIGMOD-SIGACTSIGART Symposium on Principles of Database Systems, pages 134–142, 2006.
[95] N. H. Mustafa and A. Pekeˇc. Majority consensus and the local majority rule. In Proceedings of the 28th International Colloquium on Automata, Languages and Programming, pages 530–542, 2001.
[96] M. Naor and A. Wool. The load, capacity, and availability of quorum systems. SIAM Journal on Computing, 27(2):423–447, 1998.
[97] G. Pandurangan, P. Raghavan, and E. Upfal. Using PageRank to characterize web structure. Internet Mathematics, 3(1):1–20, 2006.
[98] C. H. Papadimitriou. Computational Complexity. Addison Wesley, 1994.
[99] A. Pelc. Efficient fault location with small risk. In Proceedings of the 3rd Colloquium on Structural Information and Communication Complexity, pages 292–300, 1996.
[100] D. Peleg. Graph immunity against local influence. Technical Report CS96-11, Weizmann Science Press of Israel, 1996.
[101] D. Peleg. Size bounds for dynamic monopolies. Discrete Applied Mathematics, 86(2–3):263–273, 1998.
[102] D. Peleg. Local majorities, coalitions and monopolies in graphs: a review. Theoretical Computer Science, 282(2):231–257, 2002.
[103] D. Peleg and A.Wool. The availability of quorum systems. Information and Computation, 123(2):210–223, 1995.
[104] D.M. Pennock, G.W. Flake, S. Lawrence, E. J. Glover, and C. L. Giles. Winners don’t take all: Characterizing the competition for links on the web. Proceedings of the National Academy of Sciences, 99(8):5207–5211, 2002.
[105] A. Pietracaprina and G. Pucci. The complexity of deterministic PRAM simulation on distributed memory machines. Theory of Computing Systems, 30(3):231–247, 1997.
[106] A. Pietracaprina, G. Pucci, and J. F. Sibeyn. Constructive deterministic PRAM simulation on a mesh-connected computer. In Proceedings of the 6th Annual ACM Symposium on Parallel Algorithms and Architectures, pages 248–256, 1994.
[107] D. A. Pike and Y. Zou. Decycling Cartesian products of two cycles. SIAM Journal on Discrete Mathematics, 19(3):651–663, 2005.
[108] S. Poljak and M. Sura. On periodical behavior in societies with symmetric influences. Combinatorica, 3(1):119–121, 1983.
[109] S. Poljak and D. Turzik. On an application of convexity to discrete systems. Discrete Applied Mathematics, 13(1):27–32, 1986.
[110] M. Raynal. Algorithms for mutual exclusion. MIT Press, 1986.
[111] W. Rudin. Principles of Mathematical Analysis. McGraw-Hill, 3rd edition, 1976.
[112] B. Samuelsson and J. E. S. Socolar. Exhaustive percolation on random networks. Physical Review E, 74(036113), 2006.
[113] T. C. Schelling. Hockey helmets, concealed weapons, and daylight saving: A study of binary choices with externalities. Journal of Conflict Resolution, 17(3):381–428, 1973.
[114] M. Spasojevic and P. Berman. Voting as the optimal static pessimistic scheme for managing replicated data. IEEE Transactions on Parallel and Distributed Systems, 5(1):64–73, 1994.
[115] G. F. Sullivan. The Complexity of System-Level Fault Diagnosis and Diagnosability. PhD thesis, Yale University, 1986.
[116] R. H. Thomas. A majority consensus approach to concurrency control for multiple copy databases. ACM Transactions on Database Systems, 4(2):180–209, 1979.
[117] E. Upfal. Tolerating a linear number of faults in networks of bounded degree. Information and Computation, 115(2):312–320, 1994.
[118] E. Upfal and A. Wigderson. How to share memory in a distributed system. Journal of the ACM, 34(1):116–127, 1987.
[119] J. von Neumann. Probabilistic logics and synthesis of reliable organisms from unreliable components. In C. Shannon and J. McCarthy, editors, Automata Studies, pages 43–98, 1956.
[120] D. J. Watts. A simple model of global cascades on random networks. Proceedings of the National Academy of Sciences, 99(9):5766–5771, 2002.
[121] D. J. Watts and S. H. Strogatz. Collective dynamics of ‘small-world’ networks. Nature, 393(6684):440–442, 1998.
[122] D. B. West. Introduction to Graph Theory. Prentice-Hall, 2nd edition, 2001.
[123] Zhen-Jun Yan, editor. A Course on High School Mathematics Competition (in Chinese), chapter 14, pages 112–113. Chiuchang, 1993.
[124] H. P. Young. Individual strategy and social structure. Princeton University Press, Princeton, 1998.
[125] H. P. Young. The diffusion of innovations in social networks. In L. E. Blume and S. N. Durlauf, editors, Economy as an Evolving Complex System, volume 3 of Proceedings volume in the Santa Fe Institute studies in the sciences of complexity, pages 267–282. Oxford University Press, New York, 2006.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/44907-
dc.description.abstract假設G(V,E)為一簡單的有向或無向圖,且每個v∈V都被賦予一值φ(v)≥1。許多文獻不斷探討如下的過程及其變形:一開始,我們啟動若干個被稱為種子的節點,之後,每當指向一節點v之已啟動節點達到φ(v)個或更多時,v就會跟著被啟動,整個過程將一直持續到沒有更多節點能被啟動為止。在下列的幾種情形中,我們探討了啟動δ∈[0,1]比例或更多的節點所需之最少種子數:
˙G為一艾狄胥-倫依隨機圖(Erdos-Renyi random graph)且任何一節點皆會在其有ρ∈(0,1]比例或更多的鄰居被啟動時,也跟著被啟動。
˙G為一無向連通圖且任何一節點皆會在其有嚴格超過一半的鄰居被啟動時,也跟著被啟動。
˙G為一節點入度(indegree)皆非零之有向圖,且對任何一節點而言,當指向該節點之其他所有節點有至少一半被啟動時,該節點也會跟著被啟動。
˙G為一節點入度皆非零之有向圖,且對任何一節點而言,當指向該節點之其他所有節點有嚴格超過一半被啟動時,該節點也會跟著被啟動。
˙G為一有向圖,每個點v被賦予的φ(v)值皆非零且δ=1。
我們也探究了找尋最少種子以啟動所有的節點,究竟需耗費多少計算資源。
zh_TW
dc.description.abstractLet $G(V,E)$ be a simple directed or undirected graph and $phi(v)geq 1$ for each $vin V$. The following process and its variants have been studied extensively in the literature. Initially, only a set of vertices, called the seeds, are active. Thereafter, an inactive vertex $v$ is activated when at least $phi(v)$ of its in-neighbors are active. The process ends when no additional vertices can be activated. We derive bounds on the minimum number of seeds needed to activate at least a $deltain [0,1]$ fraction of the vertices at the end, for the following cases: egin{itemize} item $G$ is an Erd{H{o}}s-R{'e}nyi random graph. An inactive vertex is activated when at least a $
hoin [0,1]$ fraction of its neighbors are active. item $G$ is a connected undirected graph. An inactive vertex is activated when more than half of its neighbors are active. item $G$ is a directed graph with positive indegrees. An inactive vertex is activated when at least half of its in-neighbors are active. item $G$ is a directed graph with positive indegrees. An inactive vertex is activated when more than half of its in-neighbors are active. item $G$ is a directed graph, $phi(v)geq 1$ for all $vin V$ and $delta=1$. end{itemize} We also investigate the computational hardness of finding a minimum set of seeds activating all vertices at the end.
en
dc.description.provenanceMade available in DSpace on 2021-06-15T03:57:58Z (GMT). No. of bitstreams: 1
ntu-99-D95922007-1.pdf: 660930 bytes, checksum: ee8fdf666d4dee9d0acd6b214773c731 (MD5)
Previous issue date: 2010
en
dc.description.tableofcontents1 Introduction 5 1.1 Motivations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.2 Review of literature . . . . . . . . . . . . . . . . . . . . . . . . 6 1.2.1 Fault-tolerant computing . . . . . . . . . . . . . . . . . 7 1.2.2 Graph-theoretical models of infection . . . . . . . . . . 8 1.2.3 Watts’ model of global cascades . . . . . . . . . . . . . 10 1.2.4 Algorithms for maximizing social influence . . . . . . . 11 1.2.5 Models allowing activation and deactivation . . . . . . 12 1.2.6 Game-theoretic models of local interactions . . . . . . 13 1.2.7 Propagation of influence through the Internet . . . . . 14 1.2.8 Control in graphs . . . . . . . . . . . . . . . . . . . . . 15 1.3 Terminology of graph theory . . . . . . . . . . . . . . . . . . . 16 1.4 The activation process . . . . . . . . . . . . . . . . . . . . . . 18 1.5 Contributions and organization of this dissertation . . . . . . . 20 2 Activating vertices of random graphs with the fewest seeds 23 2.1 Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 2.2 A lower bound for Erd{H{o}}s-R{'e}nyi random graphs . . . . . . . . . 26 2.3 An upper bound for Erd{H{o}}s-R{'e}nyi random graphs . . . . . . . . 34 3 Maximum number of faults that can be tolerated 41 3.1 The undirected case . . . . . . . . . . . . . . . . . . . . . . . . 42 3.2 The directed case . . . . . . . . . . . . . . . . . . . . . . . . . 54 4 Bounds with general thresholds 59 4.1 A lower bound with general thresholds . . . . . . . . . . . . . 59 4.2 An upper bound with general thresholds . . . . . . . . . . . . 64 5 Inapproximability 72 6 Conclusions 83 Bibliography 88
dc.language.isoen
dc.title基於門檻值之連鎖啟動程序分析zh_TW
dc.titleAnalysis of Threshold-Based Processes of Cascading Activation in Graphsen
dc.typeThesis
dc.date.schoolyear98-2
dc.description.degree博士
dc.contributor.oralexamcommittee劉長遠(Cheng-Yuan Liou),陳健輝(Gen-Huey Chen),林守德(Shou-De Lin),趙坤茂(Kun-Mao Chao)
dc.subject.keyword不可逆性動態寡佔,全域傾瀉,不可逆性轉換集,無序二元雪崩,社群影響,傳染性,集體行為,zh_TW
dc.subject.keywordIrreversible dynamic monopoly,Global cascade,Irreversible conversion set,Unordered binary avalanche,Social influence,Contagion,Collective behavior,en
dc.relation.page103
dc.rights.note有償授權
dc.date.accepted2010-05-31
dc.contributor.author-college電機資訊學院zh_TW
dc.contributor.author-dept資訊工程學研究所zh_TW
顯示於系所單位:資訊工程學系

文件中的檔案:
檔案 大小格式 
ntu-99-1.pdf
  目前未授權公開取用
645.44 kBAdobe PDF
顯示文件簡單紀錄


系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。

社群連結
聯絡資訊
10617臺北市大安區羅斯福路四段1號
No.1 Sec.4, Roosevelt Rd., Taipei, Taiwan, R.O.C. 106
Tel: (02)33662353
Email: ntuetds@ntu.edu.tw
意見箱
相關連結
館藏目錄
國內圖書館整合查詢 MetaCat
臺大學術典藏 NTU Scholars
臺大圖書館數位典藏館
本站聲明
© NTU Library All Rights Reserved