Journal of the ACM (JACM)
Stackelberg Scheduling Strategies
SIAM Journal on Computing
Selfish Routing in Capacitated Networks
Mathematics of Operations Research
Equilibria for networks with malicious users
Mathematical Programming: Series A and B
STACS'99 Proceedings of the 16th annual conference on Theoretical aspects of computer science
When Ignorance Helps: Graphical Multicast Cost Sharing Games
MFCS '08 Proceedings of the 33rd international symposium on Mathematical Foundations of Computer Science
When ignorance helps: Graphical multicast cost sharing games
Theoretical Computer Science
The Impact of Social Ignorance on Weighted Congestion Games
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
Social context congestion games
SIROCCO'11 Proceedings of the 18th international conference on Structural information and communication complexity
Social context congestion games
Theoretical Computer Science
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We consider the problem of characterizing user equilibria and optimal solutions for selfish routing in a given network. We extend the known models by considering users oblivious to congestion. While in the typical selfish routing setting the users follow a strategy that minimizes their individual cost by taking into account the (dynamic) congestion due to the current routing pattern, an oblivious user ignores congestion altogether. Instead, he decides his routing on the basis of cheapest routes on a network without any flow whatsoever. These cheapest routes can be, for example, the shortest paths in the network without any flow. This model tries to capture the fact that routing tables for at least a fraction of the flow in large scale networks such as the Internet may be based on the physical distances or hops between routers alone. The phenomenon is similar to the case of traffic networks where a certain percentage of travelers base their route simply on the distances they observe on a map, without thinking (or knowing, or caring) about the delays experienced on this route due to their fellow travelers. In this work we study the price of anarchy of such networks, i.e., the ratio of the total latency experienced by the users in this setting over the optimal total latency if all users were centrally coordinated.