article

A survey on networking games in telecommunications

Authors:

L. WynterAuthors Info & Claims

Computers and Operations Research, Volume 33, Issue 2

Pages 286 - 311

https://doi.org/10.1016/j.cor.2004.06.005

Published: 01 February 2006 Publication History

Abstract

In this survey, we summarize different modeling and solution concepts of networking games, as well as a number of different applications in telecommunications that make use of or can make use of networking games. We identify some of the mathematical challenges and methodologies that are involved in these problems. We include here work that has relevance to networking games in telecommunications from other areas, in particular from transportation planning.

References

[1]

Wardrop, J.G., Some theoretical aspects of road traffic research communication networks. Proceedings of the Institution of Civil Engineers, Part 2. v1. 325-378.

[2]

Altman, E., Flow control using the theory of zero-sum Markov games. IEEE Transactions on Automatic Control. v39. 814-818.

[3]

Altman, E., Monotonicity of optimal policies in a zero sum game: a flow control model. . Advances of Dynamic Games and Applications. v1. 269-286.

[4]

Altman, E. and Başar, T., Optimal rate control for high speed telecommunication networks. In: Proceedings of the 34th IEEE Conference on Decision and Control,

[5]

Altman, E. and Başar, T., Multi-user rate-based flow control. IEEE Transactions on Communications. 940-949.

[6]

Altman, E., Başar, T. and Hovakimian, N., Worst-case rate-based flow control with an ARMA model of the available bandwidth. Annals of Dynamic Games. v6. 3-29.

[7]

Altman, E., Başar, T. and Srikant, R., Multi-user rate-based flow control with action delays: a team-theoretic approach. . In: Proceedings of the 36th IEEE Conference on Decision and Control,

[8]

Altman, E., Başar, T. and Srikant, R., Robust rate control for ABR sources. In: IEEE INFOCOM,

[9]

Altman E, Başar T, Srikant R. Congestion control as a stochastic control problem with action delays. Automatica, Special issue on control methods for communication networks. 1999;35(12):1937-50.

[10]

Goel, A., Dutta, D. and Heidemann, J., Oblivious AQM and Nash equilibria. In: IEEE INFOCOM,

[11]

Garg R, Kamra A, Khurana V. Eliciting cooperation from selfish users: a game-theoretic approach towards congestion control in communication networks. Technical Report RI01001, IBM Research, April 2001. Available at http://www.research.ibm.com/resources/paper_search.html.

[12]

Garg, R., Kamra, A. and Khurana, V., A game-theoretic approach towards congestion control in communication networks. Computer Communications Review. v32 i3. 47-61.

[13]

Hsiao, M.T. and Lazar, A.A., Optimal decentralized flow control of Markovian queueing networks with multiple controllers. Performance Evaluation. v13. 181-204.

[14]

Korilis, Y.A. and Lazar, A., On the existence of equilibria in noncooperative optimal flow control. Journal of the ACM. v42 i3. 584-613.

[15]

Korilis YA, Lazar A. Why is flow control hard: optimality, fairness, partial and delayed information. CTR Technical Report 332-93-11, Center for Telecommunications Research, Columbia University, New York, 1992.

[16]

Altman, E., A Markov game approach for optimal routing into a queueing network. In: Annals of dynamic games, Birkhauser, Berlin. pp. 359-376.

[17]

Altman, E., Başar, T., Jimenez, T. and Shimkin, N., Competitive routing in networks with polynomial cost. IEEE Transactions on Automatic Control. v47. 92-96.

[18]

Altman, E., Başar, T., Jimenez, T. and Shimkin, N., Routing into two parallel links: game-theoretic distributed algorithms. . Journal of Parallel and Distributed Computing. v61 i9. 1367-1381.

[19]

Altman, E. and Kameda, H., Equilibria for multiclass routing problems in multi-agent networks. In: 40th IEEE Conference on Decision and Control,

[20]

Beans, N.G., Kelly, F.P. and Taylor, P.G., Braess's paradox in a loss network. Journal of Applied Probability. v34. 155-159.

[21]

Boulogne, T., Altman, E., Kameda, H. and Pourtallier, O., Mixed equilibrium in multiclass routing games. IEEE Transactions on Automatic Control. v47 i6. 903-916.

[22]

Boulogne, T., Altman, E. and Pourtallier, O., Load balancing in distributed computers problem. Annals of Operation Research. v109 i1. 279-291.

[23]

Calvert, B., Solomon, W. and Ziedins, I., Braess's paradox in a queueing network with state-dependent routing. Journal of Applied Probability. v34. 134-154.

[24]

Cohen, J.E. and Jeffries, C., Congestion resulting from increased capacity in single-server queueing networks. IEEE/ACM Transactions on Networking. v5 i2. 1220-1225.

[25]

Cohen, J.E. and Kelly, F.P., A paradox of congestion in a queuing network. Journal of Applied Probability. v27. 730-734.

[26]

Economides, A.A. and Silvester, J.A., Multi-objective routing in integrated services networks a: game theory approach. In: IEEE INFOCOMM, pp. 1220-1225.

[27]

Kameda, H. and Zhang, Y., Uniqueness of the solution for optimal static routing in open BCMP queueing networks. Mathematical and Computer Modelling. v22. 119-130.

[28]

Jin, Y. and Kesidis, G., Nash equilibria of a generic networking game with applications to circuit-switched networks. In: Proceedings of IEEE INFOCOM,

[29]

Korilis, Y.A., Lazar, A.A. and Orda, A., Architecting noncooperative networks. Journal on Selected Areas in Communications. v13 i7. 1241-1251.

[30]

Korilis, Y.A., Lazar, A.A. and Orda, A., Achieving network optima using Stackelberg routing strategies. IEEE/ACM Transactions on Networking. v5. 161-173.

[31]

Korilis, Y.A., Lazar, A.A. and Orda, A., Capacity allocation under non-cooperative routing. IEEE Transactions on Automatic Control. v42 i3. 309-325.

[32]

Korilis, Y.A., Lazar, A.A. and Orda, A., Avoiding the Braess paradox in non-cooperative networks. Journal of Applied Probability. v36. 211-222.

[33]

La, R.J. and Anantharam, V., Optimal routing control: game theoretic approach. . In: Proceedings of the 36th IEEE Conference on Decision and Control,

[34]

Orda, A., Rom, N. and Shimkin, N., Competitive routing in multi-user communication networks. IEEE/ACM Transactions on Networking. v1. 614-627.

[35]

Patriksson, M., The traffic assignment problem: models and methods. . 1994. VSPBV, The Netherlands.

[36]

Rosenthal, R.W., A class of games possessing pure strategy Nash equilibria. International Journal of Game Theory. v2. 65-67.

[37]

Rosenthal, R.W., The network equilibrium problem in integers. Networks. v3. 53-59.

[38]

Koutsoupias, E. and Papadimitriou, C., Worst-case equilibria. In: 16th Annual Symposium on Theoretical Aspects of Computer Science, pp. 404-413.

[39]

Kameda, H., Altman, E. and Kozawa, T., A case where a paradox like Braess's occurs in the Nash equilibrium but does not occur in the Wardrop equilibrium-a situation of load balancing in distributed computer systems. In: Proceedings of IEEE CDC'99,

[40]

Kameda, H., Altman, E., Kozawa, T. and Hosokawa, Y., Braess-like paradoxes in distributed computer systems. IEEE Transactions on Automatic Control. v45 i9. 1687-1691.

[41]

Kameda, H., Altman, E. and Pourtallier, O., Analytic study of mixed optima in symmetric distributed computer systems. In: Proceedings of the Ninth International Symposium on Dynamic Games and Applications,

[42]

Kameda, H., Altman, E., Pourtallier, O., Li, J. and Hosokawa, Y., Paradoxes in performance optimization of distributed systems. In: Proceedings of SSGRR 2000 Computer and e-Business Conference,

[43]

Kameda, H., Li, J., Kim, C. and Zhang, Y., Optimal load balancing in distributed computer systems. 1997. Springer, Berlin.

[44]

Wellman, M.P., A market-oriented programming environment and its application to distributed multicommodity flow problems. Journal of Artificial Intelligence Research. v1. 1-23.

[45]

Wellman, M.P., Market-oriented programming: some early lessons. . In: Clearwater, S (Ed.), Market-based control: A paradigm for distributed resource allocation, World Scientific Publishers, Hong-Kong.

[46]

Altman, E., Galtier, J. and Touati, C., Utility based fair bandwidth allocation. In: Proceedings of the IASTED International Conference on Networks, Parallel and Distributed Processing and Applications (NPDPA 2002),

[47]

Cao, X.R. and Shen, U.X., Internet pricing: comparison and examples. . In: Proceedings of IEEE Conference on Decision and Control,

[48]

Haviv, M., The Aumann-Shapely pricing mechanism for allocating congestion costs. Operations Research Letters. v29 i5. 211-215.

[49]

Lazar, A.A., Orda, A. and Pendarakis, D.E., Virtual path bandwidth allocation in multi-user networks. IEEE/ACM Transactions on Networking. v5 i6. 861-871.

[50]

Yaiche, H., Mazumdar, R. and Rosenberg, C., A game theoretic framework for bandwidth allocation and pricing of elastic connections in broadband networks: theory and algorithms. . IEEE/ACM Transactions on Networking. v8 i5. 667-678.

[51]

El-Azouzi, R. and Altman, E., Constrained traffic equilibrium in routing. IEEE Transactions on Automatic Control. v48 i9. 1656-1660.

[52]

Altman, E., Non zero-sum stochastic games in admission, service and routing control in queueing systems. Queueing Systems. v23. 259-279.

[53]

Altman, E. and Hordijk, A., Zero-sum Markov games and worst-case optimal control of queueing systems. Queueing Systems. v21. 415-447.

[54]

Altman, E. and Koole, G.M., Stochastic scheduling games and Markov decision arrival processes. Computers and Mathematics with Applications. v26 i6. 141-148.

[55]

Altman, E., El Azouzi, R., Başar, T. and Srikant, R., Combined competitive flow control and routing games. In: Workshop on Networking Games and Resource Allocation, Petrozavodsk,

[56]

Altman, E., Başar, T. and Srikant, R., Nash equilibria for combined flow control and routing in networks: asymptotic behavior for a large number of users. . IEEE Transactions on Automatic Control. v47 i6. 917-930.

[57]

El-Azouzi, R., Altman, E. and Wynter, L., Telecommunications network equilibrium with price and quality-of-service characteristics. In: Proceedings of the International Teletraffic Conference (ITC),

[58]

Haurie, A. and Marcotte, P., On the relationship between Nash-Cournot and Wardrop equilibria. Networks. v15. 295-308.

[59]

Masuda, Y., Capacity management in decentralized networks. Management Science. v48. 1628-1634.

[60]

Rhee, S.H. and Konstantopoulos, T., Optimal flow control and capacity allocation in multi-service networks. In: IEEE Conference on Decision and Control,

[61]

Lakshman, T.V. and Kodialam, M., Detecting network intrusions via sampling: a game theoretic approach. . In: IEEE INFOCOM,

[62]

Michiardi P, Molva R. Game theoretic analysis of security in mobile ad hoc networks. Technical Report rr-02-070, Institut Eurecom, France, April 2002.

[63]

Alpcan, T. and Başar, T., A hybrid systems model for power control in a multicell wireless data network. In: Proceedings of WiOpt'03,

[64]

Alpcan, T., Başar, T., Srikant, R. and Altman, E., CDMA uplink power control as a noncooperative game. Wireless Networks. v8. 659-670.

[65]

Altman, E. and Altman, Z., S-modular games and power control in wireless networks. IEEE Transactions on Automatic Control. v48 i5. 839-842.

[66]

Falomari, D., Mandayam, N. and Goodman, D., A new framework for power control in wireless data networks: games utility and pricing. . In: Proceedings of the Allerton Conference on Communication, Control and Computing, pp. 546-555.

[67]

Heikkinen T. A minimax game of power control in a wireless network under incomplete information. DIMACS Technical Report 99-43, August 1999.

[68]

Ji, H. and Huang, C., Non-cooperative uplink power control in cellular radio systems. Wireless Networks. v4 i3. 233-240.

[69]

Saraydar, C.U., Mandayam, N. and Goodman, D., Pricing and power control in a multicell wireless network. IEEE Journal on Selective Areas in Communications. 1883-1892.

[70]

Saraydar, C.U., Mandayam, N.B. and Goodman, D., Efficient power control via pricing in wireless data networks. IEEE Transactions on Communications. v50 i2. 291-303.

[71]

Sung, C.W. and Wong, W.S., Mathematical aspects of the power control problem in mobile communication systems. In: Guo, L., Stephen Yau, S.-T (Eds.), Lectures at the Morningside Center of Mathematics, ACM/International Press, New York.

[72]

Battiti, R., Conti, M. and Gregori, E., Price-based congestion-control in Wi-Fi hot spots. In: Proceedings of WiOpt'03,

[73]

Crowcroft, J., Gibbens, R., Kelly, F. and Ostring, S., Modelling incentives for collaboration in mobile ad hoc networks. In: Proceedings of WiOpt'03,

[74]

Michiardi, P. and Molva, R., A game theoretical approach to evaluate co-operation enforcement mechanisms in mobile ad hoc networks. In: Proceedings of WiOpt'03,

[75]

Urpi, A., Bonuccelli, M. and Giordano, S., Modeling cooperation in mobile ad hoc networks: a formal description of selfishness. . In: Proceedings of WiOpt'03,

[76]

Altman, E., El Azouzi, R. and Jimenez, T., Slotted ALOHA as a stochastic game with partial information. In: Proceedings of WiOpt'03,

[77]

Jin, Y. and Kesidis, G., Equilibiria of a noncooperative game for heterogeneous users of an ALOHA network. IEEE Communication Letters. v6 i7. 282-284.

[78]

MacKenzie, A.B. and Wicker, S.B., Selfish users in ALOHA: a game theoretic approach. . In: Proceedings of the Fall 2001 IEEE Vehicular Technology Conference,

[79]

Dramitinos, M., Courcoubetis, C. and Stamoulis, G., Auction-based resource reservation in 2.5/3G networks. In: Proceedings of WiOpt'03,

[80]

van den Nouweland, A., Borm, P. and Van Golstein Brouwers, W., A game theoretic approach to problems in telecommunications. Management Science. v42 i2. 294-303.

[81]

Rosen, J.B., Existence and uniqueness of equilibrium points for concave N-person games. Econometrica. v33. 153-163.

[82]

Fudenberg, D. and Tirole, J., Game theory. 1991. MIT Press, Cambridge, MA.

[83]

Stackelberg, H.V., Marktform und Gleichgewicht. 1934. Julius Springer, Vienna, Austria.

[84]

Bard, J.F., Practical bilevel optimization. 1998. Kluwer Academic Publishers, Dordrecht.

[85]

Patriksson, M. and Wynter, L., Stochastic mathematical programs with equilibrium constraints. Operations Research Letters. v25. 159-167.

[86]

Loridan, P. and Morgan, J., Weak via strong Stackelberg problem: new results. . Journal of Global Optimization. v8. 263-287.

[87]

Monderer, D. and Shapley, L.S., Potential games. Games and Economic Behavior. v14. 124-143.

[88]

Sandholm WH. Evolutionary justification of Nash equilibrium. PhD thesis, Northwestern University, 1998.

[89]

Sandholm, W.H., Potential games with continuous player sets. Journal of Economic Theory. v97. 81-108.

[90]

Altman E, Wynter L. Equilibrium, games, and pricing in transportation and telecommunication networks. In: Altman E, Wynter L, guest editors. Networks and Spatial Economics, Special Issue on Crossovers Between Transportation and Telecommunication Modelling, 2004;4(1):7-21.

[91]

Wie, B.W. and Tobin, R.L., On the relationship between dynamic Nash and instantaneous user equilibria. Networks. v28. 141-163.

[92]

Larsson, T. and Patriksson, M., Side constrained traffic equilibrium models-analysis, computation and applications. Transportation Research. v33B. 233-264.

[93]

Dafermos, S., The traffic assignment problem for multiclass-user transportation networks. Transportation Science. v6. 73-87.

[94]

Dafermos, S., Toll patterns for multiclass-user transportation networks. Transportation Science. v7. 211-223.

[95]

Sheffi, Y., Urban transportation networks. 1985. Prentice-Hall, NJ, USA.

[96]

Gupta, P. and Kumar, P.R., A system and traffic dependent adaptive routing algorithm for ad hoc networks. In: Proceedings of the 36th IEEE Conference on Decision and Control, pp. 2375-2380.

[97]

Pigou, A.C., The economics of welfare. 1920. McMillan&Co., London.

[98]

Harker, P.T., Multiple equilibrium behaviors on networks. Transportation Science. v22. 39-46.

[99]

Wie, B.W., A differential game approach to the dynamic mixed behavior traffic network equilibrium problem. European Journal of Operational Research. v83. 117-136.

[100]

The ATM Forum Technical Committee. Traffic Management Specification, Version 4.0, af-tm-0056, April 1996.

[101]

El-Azouzi R, El Kamili M, Altman E, Abbad M, Başar T. Combined competitive flow control and routing in multi-user communication network with hard side-constraints. In: Boukas EK, Malhame R., editors. Analysis, Control and Optimization of Complex Dynamic Systems; 2004, to appear.

[102]

Fishburn, P.C. and Odlyzko, A.M., Competitive pricing of information goods: subscription pricing versus pay-per-use. . Economic Theory. v13. 447-470.

[103]

Gibbens, R., Mason, R. and Steinberg, R., Internet service classes under competition. IEEE Journal on Selected Areas in Communications. v18. 2490-2498.

[104]

Liu, Z., Wynter, L. and Xia, C., Usage-based versus flat pricing for e-business services with differentiated qos. In: Proceedings of the IEEE Conference on Electronic Commerce,

[105]

Park, K., Sitharam, M. and Chen, S., Quality of service provision in nonco-operative networks with diverse user requirements. Decision Support Systems. v28. 101-122.

[106]

Altman, E. and Shwartz, A., Constrained Markov games: Nash equilibria. . Annals of the International Society of Dynamic Games. v5. 213-221.

[107]

Ran, B. and Boyce, D., Modeling dynamic transportation networks. 1996. Springer, Berlin.

[108]

Neyman, A., . Correlated equilibrium and potential games. International Journal of Game Theory. v26. 223-227.

[109]

Cominetti, R. and Correa, J., The common-line problem in congested transit networks. Transportation Science. v35 i3. 250-267.

[110]

Marcotte P, Wynter L. A new look at the multi-class network equilibrium problem. Transportation Science 2004;38, to appear.

[111]

Topkis, D., Equilibrium points in nonzero-sum n-person submodular games. SIAM Journal of Control and Optimization. v17. 773-787.

[112]

Yao, D.D., S-modular games with queueing applications. Queueing Systems. v21. 449-475.

[113]

Cohen, G. and Chaplais, F., Nested monotony for variational inequalities over product of spaces and convergence of iterative algorithms. Journal of Optimization Theory and Applications. v59. 369-390.

[114]

Patriksson, M., Nonlinear programming and variational inequalities: a unified approach. . 1999. Kluwer Academic Publishers, Dordrecht.

[115]

Shenker, S., Making greed work in networks: a game-theoretic analysis of switch service disciplines. . In: Proceedings of ACM SIGCOMM, pp. 47-57.

[116]

Kurose, J. and Simha, R., A microeconomic approach to optimal resource allocation in distributed computer systems. IEEE Transactions on Computers. v38 i5. 705-717.

[117]

Kobayashi, H., Modeling and analysis: an introduction to system performance evaluation methodology. . 1978. Addison Wesley, Reading, MA.

[118]

Braess, D., Uber ein paradoxen der werkehrsplannung. Unternehmenforschung. v12. 256-268.

[119]

Dafermos, S. and Nagurney, A., On some traffic equilibrium theory paradoxes. Transportation Research B. v18. 101-110.

[120]

Smith, M.J., In a road network, increasing delay locally can reduce delay globally. Transportation Research. v12. 419-422.

[121]

Kameda, H., How harmful the paradox can be in braess/cohen-kelly-jeffries networks. In: IEEE INFOCOM,

[122]

Kameda, H. and Pourtallier, O., Paradoxes in distributed decisions on optimal load balancing for networks of homogeneous computers. Journal of the ACM. v49 i3. 407-433.

[123]

Roughgarden, T. and Tardos, E., How bad is selfish routing?. Journal of the ACM. v49. 236-259.

[124]

Friedman E. Selfish routing on data networks isn't too bad: genericity, TCP and OSPF. 2002.

[125]

Altman, E., El Azouzi, R. and Pourtallier, O., Avoiding paradoxes in routing games. Computer Networks. v43 i2. 133-146.

[126]

El-Azouzi, R., Altman, E. and Pourtallier, O., Properties of equilibria in routing problems in networks with several types. In: Proceedings of 41st IEEE Conference on Decision&Control,

[127]

Kelly, F.P., Network routing. Philosophical Transactions of the Royal Society, Series A. v337. 343-367.

[128]

Masuda, Y. and Whang, S., Dynamic pricing for network service: equilibrium and stability. . Management Science. v45. 867-869.

[129]

Korilis YA, Varvarigou TA, Ahuja SR. Pricing noncooperative networks. Bell Laboratories Technical Memorandum, IEEE/ACM Transactions on Networking, May 1997, submitted for publication.

[130]

Orda, A. and Shimkin, N., Incentive pricing in multi-class communication networks. In: Proceedings of the IEEE INFOCOM,

[131]

Low, S.H. and Lapsley, D.E., Optimization flow control-I: basic algorithm and convergence. . IEEE/ACM Transactions on Networking. v7 i6. 861-874.

[132]

Kelly, F., Maulloo, A. and Tan, D., Rate control in communication networks: shadow prices, proportional fairness and stability. . Journal of the Operational Research Society. v49. 237-252.

[133]

Wynter L. Optimizing proportionally fair prices. Technical Report 4311, INRIA Rocquencourt, 2001.

[134]

Bouhtou, M., Diallo, M. and Wynter, L., A numerical sutdy of Lagrange multiplier-based pricing schemes. In: Pardalos, P.M., Tsevendorj, I., Enkhbat, R (Eds.), Optimization and Optimal Control, World Scientific Publishers, Singapore.

[135]

Low, S.H., Equilibrium bandwidth and buffer allocations for elastic traffics. IEEE/ACM Transactions on Networking. v8 i3. 373-383.

[136]

Chen, S. and Park, K., An architecture for noncooperative QoS provision in many-switch systems. In: IEEE INFOCOM, pp. 864-872.

[137]

Dewan, S. and Mendelson, H., User delay costs and internal pricing for a service facility. Management Science. v36. 1502-1517.

[138]

Mendelson, H., Pricing computer services: queueing effects. . Communications of the ACM. v28. 312-321.

[139]

Naor, P., On the regulation of queueing size by levying tolls. Econometrica. v37. 15-24.

[140]

Edel, R.J., McKeown, N. and Varaiya, P.P., Billing users and pricing for TCP. IEEE Journal on Selected Areas in Communications. v13. 1162-1175.

[141]

Kelly, F.P., Tariffs and effective bandwidth in multiservice networks. In: Proceedings of the International Teletraffic Conference (ITC), pp. 401-410.

[142]

La, R.J. and Anantharam, V., Window-based congestion control with heterogeneous users. In: IEEE INFOCOM,

[143]

Low, S. and Varaiya, P., A new approach to service provisioning in ATM networks. IEEE/ACM Transactions on Networking. v1 i5. 547-553.

[144]

Low, S. and Varaiya, P., An algorithm for optimal service provisioning using resource pricing. In: IEEE INFOCOM, pp. 363-373.

[145]

MacKie-Mason, J.K. and Varian, H.R., Pricing congestible network resources. IEEE Journal on Selected Areas in Communications. v13. 1141-1149.

[146]

Mendelson H, Whang S. Pricing for communication network services. PhD thesis, Graduate School of Business, Stanford University, 1994.

[147]

Agneiv, C.E., The theory of congestion tolls. Journal of Regional Science. v17. 381-393.

[148]

Altman, E., Barman, D., El Azouzi, R., Ros, D. and Tuffin, B., Differentiated services: a game-theoretic approach. . In: Proceedings of Networking 2004,

[149]

Bergendorff, P., Hearn, D.W. and Ramana, M.V., Congestion toll pricing of traffic networks, network optimization, lecture notes in economics and mathematical systems. 1997. Springer, Berlin.

[150]

Carey, M. and Srinivasan, A., Externalities, average and marginal costs and tolls on congested networks with time-varying flows. Operations Research. v41. 217-231.

[151]

Cocchi, R., Shenker, S., Estrin, D. and Zhang, L., Pricing in computer networks: motivation, formulation and example. . IEEE/ACM Transactions on Networking. v1. 617-627.

[152]

Courcoubetis, C. and Weber, R., Pricing communication networks-economics, technology and modelling. 2003. Wiley, New York.

[153]

DaSilva, L.A., Pricing of QoS-enabled networks: a survey. . IEEE Communications Surveys&Tutorials. v3 i2.

[154]

Falkner, M., Devetsikiotis, M. and Lambadaris, I., An overview of pricing concepts for broadband IP networks. IEEE Communications Surveys&Tutorials. v3 i2.

[155]

Henderson, J.V., Road congestion: a reconsideration of pricing theory. . Journal of Urban Economics. v1. 346-365.

[156]

Huang, H.J. and Yang, H., Optimal variable road-use pricing on a congested network of parallel routes with elastic demand. In: Proceedings of the 13th International Symposium on the Theory of Traffic Flow and Transportation, pp. 479-500.

[157]

Korilis, Y.A. and Orda, A., Incentive-compatible pricing strategies for QoS routing. In: Proceedings of IEEE INFOCOM'99,

[158]

Lederer, P.J., A competitive network design problem with pricing. Transportation Science. v27 i1. 25-38.

[159]

Mandjes, M., Pricing strategies under heterogeneous service requirements. Computer Networks. v42. 231-249.

[160]

Marbach P. Priority service and max-min fairness. IEEE/ACM Transactions on Networking (TON) 2003;11(5):733-46.

[161]

Marbach, P. and Berry, R., Downlink resource allocation and pricing for wireless networks. In: IEEE INFOCOM,

[162]

Smith, M.J., The marginal cost taxation of a transportation network. Transportation Research-B. v13. 237-242.

[163]

Tuffin B. Charging the Internet without bandwidth reservation: an overview and bibliography of mathematical approaches. Journal of Information Science and Engineering, 2004, to appear.

[164]

Wie, B.W. and Tobin, R.L., Dynamic congestion pricing models for general traffic models. Transportation Research B. v32 i5. 313-327.

[165]

Başar, T. and Srikant, R., A stackelberg network game with a large number of followers. Journal of Optimization Theory and Applications. v115 i3. 479-490.

[166]

Larsson, T. and Patriksson, M., Side constrained traffic equilibrium models-traffic management through link tolls. In: Marcotte, P., Nguyen, S (Eds.), Equilibrium and advanced transportation modelling, Kluwer Academic Publishers, Dordrecht. pp. 125-151.

[167]

Granot, D. and Huberman, G., Minimum cost spanning tree games. Mathematical Programming. v21. 1-18.

[168]

Granot, D. and Maschler, M., Spanning network games. International Journal of Game Theory. v27 i4. 467-500.

[169]

Herzog, S., Shenker, S. and Estrin, D., Sharing the cost of multicast trees: an axiomatic analysis. . IEEE/ACM Transactions on Networking. v5 i6. 847-860.

[170]

Megido, N., Cost allocation for Steiner trees. Networks. v8.

[171]

N. Preux, Pricing, cooperation and competition in telecommunication networks. PhD thesis, University of Blaise Pascal, Ecole Doctorale Science pour l'Ingénieur Clermont-Ferrand, France, December 1998 {in French}.

[172]

Zakharov, V., Game theory approach in communication networks. In: Resenstiel, W., Patel, A., Petrosian, L. (Eds.), OASIS: distributed search system in the internet, St. Petersburg State University Press.

[173]

Muthoo, A., Bargaining theory with applications. 1999. Cambridge University Press, Cambridge.

[174]

Nash, J., The bargaining problem. Econometrica. v18. 155-162.

[175]

Kelly, F.P., Charging and rate control for elastic traffic. European Transactions on Telecommunications, special issue on Elastic Services over ATM networks. v8 i1.

[176]

Rump C. A Nash bargaining approach to resource allocation in a congested service system. Operations Research Letters, 2001, under review.

[177]

Cao, X.R., Preference functions and bargaining solutions. In: Proceedings of IEEE Conference on Decision and Control, pp. 164-171.

[178]

Dziong, Z., ATM network resource management. 1997. McGraw-Hill, Columbus, OH, USA.

[179]

Cao, X.R., Shen, H., Milito, R. and Wirth, P., Internet pricing with a game theoretical approach: concepts and examples. . IEEE/ACM Transactions on Networking. v10. 208-216.

[180]

Feigenbaum, J., Papadimitriou, C. and Shenker, S., Sharing the cost of multicast transmissions. Journal of Computer and System Sciences. v63. 21-41.

[181]

Nisan, N. and Ronen, A., Algorithmic mechanism design. Games and Economic Behavior. v35. 166-196.

[182]

Douligeris, C. and Mazumdar, R., Multi-level flow control in telecommunication networks. Journal of the Franklin Institute. v331B i4. 417-433.

[183]

Douligeris, C. and Mazumdar, R., A game theoretic perspective to flow control in telecommunication networks. Journal of the Franklin Institute. v329 i2. 383-402.

[184]

Mazumdar, R., Mason, L. and Douligeris, C., Fairness in network optimal flow control: optimality of product forms. . IEEE Transactions on Communications. v39 i5. 775-782.

[185]

Douligeris C. Optimal flow control and fairness in communication networks - a game theoretic perspective. PhD Dissertation, Electrical Engineering, Columbia University, New York, USA; 1989.

[186]

Chink, W.K., On convergence of asynchronous greedy algorithm with relaxation in multiclass queuing environment. IEEE Communication Letters. v3. 34-36.

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cover image Computers and Operations Research

Computers and Operations Research Volume 33, Issue 2

February 2006

320 pages

ISSN:0305-0548

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Copyright © Elsevier Ltd © 2004.

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Elsevier Science Ltd.

United Kingdom

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Published: 01 February 2006

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Irfan MChan HSoundy JKiyavash NMooij J(2024)Equilibrium computation in multidimensional congestion gamesProceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence10.5555/3702676.3702758(1751-1779)Online publication date: 15-Jul-2024
https://dl.acm.org/doi/10.5555/3702676.3702758
Alatur PRamponi GHe NKrause ADastani MSichman JAlechina NDignum V(2024)Provably Learning Nash Policies in Constrained Markov Potential GamesProceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems10.5555/3635637.3662849(31-39)Online publication date: 6-May-2024
https://dl.acm.org/doi/10.5555/3635637.3662849
Boysen NBriskorn DRupp JSchwerdfeger S(2024)Jam in the TunnelService Science10.1287/serv.2023.000516:3(184-201)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1287/serv.2023.0005
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Ribeiro A(2021)Social media as author-audience gamesData Mining and Knowledge Discovery10.1007/s10618-021-00783-335:6(2251-2281)Online publication date: 10-Aug-2021
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