拥塞控制和流量控制-1.ppt

Convergence to Efficiency Fairness Decrease: ad = 0, 0 = bd 1 xH Efficiency Line Fairness Line User 1’s Allocation x1 User 2’s Allocation x2 xH’ Convergence to Efficiency Fairness Increase : ai 0 and bi = 1 Efficiency Line Fairness Line User 1’s Allocation x1 User 2’s Allocation x2 xL Constraints Distributed efficiency I.e., Window(t+1) Window(t) during increase (each user) ai 0 and bi = 1 Similarly, ad = 0 and bd 1 Must never decrease fairness a b’s must be = 0 ai/bi 0 and ad/bd = 0 Full constraints ai 0 and bi = 1 ad = 0 and 0 = bd 1 What is the Right Choice? Constraints limit us to AIMD (Additive Increase + Muliplicative Decrease) AIMD moves towards optimal point x0 x1 x2 Efficiency Line Fairness Line User 1’s Allocation x1 User 2’s Allocation x2 Modeling [CJ89] provides theoretical basis for congestion avoidance mechanism Good science for understanding why it works so well Great engineering built useful protocol: TCP Reno etc. Critical to understanding complex systems [CJ89] model relevant after 15 years, 106 increase of bandwidth, 1000x increase in number of users Criteria for good models Two conflicting goals: reality and simplicity Realistic, complex model ? too hard to understand, too limited in applicability Unrealistic, simple model ? can be misleading Overview Congestion sources and collapse Congestion control basics TCP congestion control A Little Bit of History Until 1988 TCP with fixed window (serious problems with loss and retransmissions!!) In 1988, adaptive TCP window was introduced (Van Jacobsen) Various “improved” versions: Tahoe, Reno, Vegas, New Reno, Snoop, Westwood, Peach etc (---- 2004) Recently, the strict “end to end” TCP paradigm has been relaxed Active Queue Management (AQM) Explicit Congestion Notification (ECN) - explicit network feedback; eXplicit Control Protocol (XCP) Hybrid end to end and network feedback model Flow Control vs Congestion Control TCP Flow Control (not same with flow ctl in K-13) Make s