EECS 228a – Review. Jean Walrand www.eecs.berkeley.edu/~wlr. Fall 2002. Topics. Overview Economics of Networks Games Mechanism Design Routing Congestion Control Traffic Models. Overview. Big Picture:. Peering. Core Backbone. Users. Access Regional Metro. Enterprise
Nash Bargaining Eq.
Convex games Existence of Nash Equilibrium Suff. Condition for uniqueness (SDD)Technique: KT conditions
2. Orda, R. Rom, and N. Shimkin. “Competitive Routing in Multiuser Communication Networks,” IEEE/ACM Trans on Networking, Vol. 1, pp. 510-521, October 1993.
Users choose among parallel links
3. Y. A. Korilis, A. Lazar, and A. Orda. “Achieving Network Optima Using Stackelberg Routing Strategies,” IEEE/ACM Transactions on Networking, Vol. 5, No. 1, February 1997, pp. 161-173.
Network manager controls some of the flow and drives the Nash equilibrium to a socially efficient equilibrium
4. S. Shenker. "Making Greedy Work in Networks: A Game-Theoretic Analysis of Switch Service Disciplines," IEEE/ACM Trans on Networking, vol. 3, No. 6, Dec. 1995.
Exponential server shared by different queues. Explores impact of service discipline on equilibrium point (users adjust their rate).
FCFS is not efficient; Fair share is.
5. Z. Dziong and L.G. Mason. “Fair–Efficient Call Admission Control Policies for Broadband Networks – a Game Theoretic Framework,” IEEE/ACM Trans. On Networking, vol.4, Feb. 1996.
Admission control as a cooperative game. Compare different notions of cooperative equilibrium.
6. Allan Gibbard, “Manipulation of Voting Schemes: A General Result.” Econometrica, 41(4):587-601, Jul. 1973.
Any nondictatorial voting scheme with at least three possible outcomes is subject to individual manipulation. (One voter getting a preferable outcome to the honest one by misrepresenting his preferences.)
7. Roger Myerson, “Incentive Compatibility and the Bargaining Problem.” Econometrica, 47:61-73, 1979
Study of set of feasible expected utility allocations under incentive-compatible mechanisms.
8.Roger Myerson, “Optimal Auction Design.” Mathematics of Operations Research, 6:58-73, 1981
9. Wiliam Vickery, “Counterspeculation, Auctions, and Competitive Sealed Tenders,” Journal of Finance, 16(1):8-37, Mar.1961
(Highest bidder; 2nd highest price) is incentive-compatible
Loss rate = f(packet rate); Packet rate = f(loss rate)
2. G. de Veciana, T.-J. Lee and T. Konstantopoulos.Stability and Performance of Networks Supporting Rate Control. Could the Internet be Unstable?In Proc. IEEE INFOCOM , 1999.
Network load increases -> service rate decreases
3. Chiu and R. Jain, Analysis of the Increase and Decrease Algorithms for Congestion Avoidance in Computer Networks, Journal of Computer Networks and ISDN, Vol. 17, No. 1, June 1989, pp. 1-14.
AIMD should converge to fair efficient equilibrium
4. Frank Kelly, A.K. Maulloo and D.K.H. Tan, Rate control in communication networks: shadow prices, proportional fairness and stability, Journal of the Operational Research Society 49 (1998), 237-252.
Primal/Dual; Implementation of dual with router indications (WPF)
5. S. Low and D. Lapsley. Optimization Flow Control, I: Basic Algorithm and Convergence, IEEE/ACM Trans on Networking, December 1999.
Generalize Primal/Dual; Study of stability with delays.
6. S. Kunniyur and R. Srikant.End-to-end congestion control: utility functions, random losses and ECN marks, Infocom 2000.
Virtual queue for AQM; Adjust rate of VQ to increase utilization.
7. J. Mo and J. Walrand, Fair End-to-End Window-based Congestion Control, September 1998.
8. C. Hollot, V. Misra, D. Towsley and W. Gong. A Control Theoretic Analysis of RED, INFOCOMM 2001
Linearize RED dynamics. Show stability if gain x delay < K.