Selfish behavior and stability of the internet:

Author:

Akella Aditya1,Seshan Srinivasan1,Karp Richard2,Shenker Scott2,Papadimitriou Christos2

Affiliation:

1. CMU

2. ICSI/UC Berkeley

Abstract

For years, the conventional wisdom [7, 22] has been that the continued stability of the Internet depends on the widespread deployment of "socially responsible" congestion control. In this paper, we seek to answer the following fundamental question: If network end-points behaved in a selfish manner, would the stability of the Internet be endangered?.We evaluate the impact of greedy end-point behavior through a game-theoretic analysis of TCP. In this "TCP Game" each flowattempts to maximize the throughput it achieves by modifying its congestion control behavior. We use a combination of analysis and simulation to determine the Nash Equilibrium of this game. Our question then reduces to whether the network operates efficiently at these Nash equilibria.Our findings are twofold. First, in more traditional environments -- where end-points use TCP Reno-style loss recovery and routers use drop-tail queues -- the Nash Equilibria are reasonably efficient. However, when endpoints use more recent variations of TCP (e.g., SACK) and routers employ either RED or drop-tail queues, the Nash equilibria are very inefficient. This suggests that the Internet of the past could remain stable in the face of greedy end-user behavior, but the Internet of today is vulnerable to such behavior. Second, we find that restoring the efficiency of the Nash equilibria in these settings does not require heavy-weight packet scheduling techniques (e.g., Fair Queuing) but instead can be done with a very simple stateless mechanism based on CHOKe [21].

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Software

Reference21 articles.

1. The network simulator - ns-2. http://isi.edu/nsnam/ns/. The network simulator - ns-2. http://isi.edu/nsnam/ns/.

2. Z. Bar-Yossef. Private Communication May 2002. Z. Bar-Yossef. Private Communication May 2002.

3. Analysis of the increase and decrease algorithms for congestion avoidance in computer networks

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