A Strategic Game Theory Model Based Social Network Analysis for Multiuser Bandwidth Rate Allocation using Predictive Artificial Neural Network

Nirmalya Mukhopadhyay


In this paper I am going to first explain in detail the role of Game Theory over Social Network Analysis. Then I will look into the Predictive model of Artificial Neural network & will explain in details that how this model will be used to develop a mathematical model which will fairly and efficiently allocate the required rate of bandwidth to all the users in a Multiuser Network System. Afterwards, I will propose some newly designed algorithms which will help me in the implementation of the mathematical model. The testing result of the implementation will compare our proposed architecture with the existing model. Finally, I will end this discussion by self-estimating our proposed model and judging the future scope of the same.

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Lewin AY, Long CP, Carroll TN (1999) The coevolution of new organizational forms. Organ Sci 10(5):535–550.

Bjerknes G, Bratteteig T, Espeseth T (1991) Evolution of finished computer systems. Scand J Inform Syst 3:25–45.

HippelEv (2005) Democratizing innovation: The evolving phenomenon of user innovation. J fürBetriebswirtschaft 55(1):63–78.doi:10.1007/s11301-004-0002-8.

Neumann G, Sobernig S, Aram M (2014) Evolutionary business information systems: Perspectives and challenges of an emerging classof information systems. Bus Inform SystEng 6(1):33–38. doi:10.1007/s12599-013-0305-1.

Strogatz SH (2001) Exploring complex networks. Nature 410(6825):268–276. doi:10.1038/35065725.

Wasserman S, Faust K (1994) Social Network Analysis: Methods and Applications. 1st edn..Cambridge University Press, Cambridge, New York.

Newman MEJ (2001) The structure of scientific collaboration networks. Proc Nat AcadSci 98(2):404–409. doi:10.1073/pnas.021544898.

Moreno JL (1934) Who Shall Survive: A New Approach to the Problem of Human Interrelations. Nervous and Mental Disease Monograph Series, Vol. 58. Nervous and Mental Disease Publishing Co, Washington, DC, USA.

Tichy NM, Tushman ML, Fombrun C (1979) Social network analysis for organizations. AcadManag Rev 4(4):507–519. doi:10.2307/257851.

Lim SL, Quercia D, Finkelstein A (2010) StakeNet: Using social networks to analyse the stakeholders of large-scale software projects. In:Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1. ACM, New York, NY, USA.pp 295–304.doi:10.1145/1806799.1806844.

Freeman LC (1978) Centrality in social networks – conceptual clarification. SocNetw 1(3):215–239. doi:10.1016/0378-8733(78)90021-7.

Scott J (2012) Social Network Analysis. 3rd edn.. Sage Publications Ltd, Los Angeles.

Sommerville I (2010) Software Engineering. 9th revised edition edn, Addison-Wesley Longman, Amsterdam.

Bourque P, Fairley RED (eds) (2014) SWEBOK V3.0 - Guide to the Software Engineering Body of Knowledge. IEEE Computer Society, Piscataway, NJ.

Bryant BR, Gray J, Mernik M (2010) Domain-specific software engineering. In: Proceedings of the FSE/SDP Workshop on Future ofSoftware Engineering Research. ACM, New York, NY, USA.pp 65–68. doi:10.1145/1882362.1882376.

Mernik M, Heering J, Sloane AM (2005) When and how to develop domain-specific languages. ACM ComputSurv 37(4):316–344.doi:10.1145/1118890.1118892.

Ko AJ, Myers B, Rosson MB, Rothermel G, Shaw M, Wiedenbeck S, Abraham R, Beckwith L, Blackwell A, Burnett M, Erwig M, Scaffidi C, Lawrance J, Lieberman H (2011) The state of the art in end-user software engineering. ACM ComputSurv 43(3):1–44. doi:10.1145/1922649.1922658.

Hansen HR, Neumann G (2009) Wirtschaftsinformatik 1. 10edn.. UTB,Stuttgart.

Orlikowski WJ, Iacono CS (2001) Research commentary: Desperatelyseeking the IT in IT research—a call to theorizing the IT artifact. InformSyst Res 12(2):121–134. doi:10.1287/isre.

Conen W, Neumann G (1998) A perspective on technology-assistedcollaboration. In: Conen W, Neumann G (eds). Coordination Technologyfor Collaborative Applications. Lecture Notes in Computer Science.Springer.pp 1–7.

Hevner AR, March ST, Park J, Ram S (2004) Design science in informationsystems research. MIS Quarterly 28(1):75–105.

Lee AS (2010) Retrospect and prospect: information systems research inthe last and next 25 years. J Inform Technol 25(4):336–348.doi:10.1057/jit.2010.24.

Lee A, Thomas M, Baskerville R (2013) Going back to basics in design:From the IT artifact to the IS artifact. In: Proceedings of the 19thAmericas Conf. on Inf. Systems, Chicago, Illinois.

Simon HA (1996) The Sciences of the Artificial. 3rd edn..MIT Press,Cambridge, MA, USA.

Popper K (1980) Three worlds. The Tanner Lecture on Human Values,Vol. 1.Cambridge University Press, Cambridge, UK. http://tannerlectures.utah.edu/lecture-library.php

Vahidov R (2006) Design researcher’s IS artifact: a representationalframework. In: Proceedings of the 1st International Conference onDesign Science Research in Information Systems and Technology,Claremont, USA, Claremont, CA.

McKinney EHJ, Yoos CJI (2010) Information about information: Ataxonomy of views. MIS Quarterly 34(2):329–344.

Germonprez M, Hovorka D, Gal U (2011) Secondary design: A case ofbehavioral design science research. J Assoc Inform Syst12(10):662–683.

March ST, Smith GF (1995) Design and natural science research oninformation technology. Decis Support Syst 15(4):251–266.doi:10.1016/0167-9236(94)00041-2.

Spinellis D (2001) Notable design patterns for domain-specificlanguages. J SystSoftw 56(1):91–99. doi:10.1016/S0164-1212(00)00089-3.

Weinberger A, Ertl B, Fischer F, Mandl H (2005) Epistemic and socialscripts in computer-supported collaborative learning. InstrSci33(1):1–30. doi:10.1007/s11251-004-2322-4. Accessed 2014-06-15.

Strembeck M, Zdun U (2009) An approach for the systematicdevelopment of domain-specific languages. SoftwPracExp39(15):1253–1292. doi:10.1002/spe.936.

Fowler M (2010) Domain-Specific Languages. 1st edn..Addison-WesleyProfessional, Westford, Massachusetts.

Kelleher C, Pausch R (2005) Lowering the barriers to programming: Ataxonomy of programming environments and languages for noviceprogrammers. ACM ComputSurv 37(2):83–137.doi:10.1145/1089733.1089734. Accessed 2015-01-15.

Stocker A, Tochtermann K (2011) Enterprise wikis – types of use, benefitsand obstacles: A multiple-case study. In: Fred A, Dietz JLG, Liu K, Filipe J(eds). Knowledge Discovery, Knowlege Engineering and KnowledgeManagement.Communications in Computer and Information Science.Springer, Berlin Heidelberg.pp 297–309.

Pahlke I, Beck R, Wolf M (2010) Enterprise mashup systems as platformfor situational applications. Bus Inform SystEng 2(5):305–315.doi:10.1007/s12599-010-0121-9.

Germonprez M, Hovorka D, Collopy F (2007) A theory of tailorabletechnology design. J Assoc Inform Syst 8(6):351–367.

Object Management Group (2014) Essence – kernel and language forsoftware engineering methods. beta 2. Technical report, ObjectManagement Group, Inc. (OMG), Needham, MA, USA. http://www.omg.org/spec/Essence/1.0/

Dingsøyr T, Dybå T, Moe NB (eds) (2010) Agile Software Development: Current Research and Future Directions. Springer, Berlin.

Muller MJ, Kuhn S (1993) Participatory design. CommunACM36(4):24–28.


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