Article · Wikipedia archive · Last revised Jun 16, 2026

Bandwidth-sharing game

A bandwidth-sharing game is a type of resource allocation game designed to model the real-world allocation of bandwidth to many users in a network. The game is popular in game theory because the conclusions can be applied to real-life networks.

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Jun 16, 2026
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A bandwidth-sharing game is a type of resource allocation game designed to model the real-world allocation of bandwidth to many users in a network. The game is popular in game theory because the conclusions can be applied to real-life networks.

The game

The game involves n {\displaystyle n} players. Each player i {\displaystyle i} has utility U i ( x ) {\displaystyle U_{i}(x)} for x {\displaystyle x} units of bandwidth. Player i {\displaystyle i} pays w i {\displaystyle w_{i}} for x {\displaystyle x} units of bandwidth and receives net utility of U i ( x ) w i {\displaystyle U_{i}(x)-w_{i}} . The total amount of bandwidth available is B {\displaystyle B} .

Regarding U i ( x ) {\displaystyle U_{i}(x)} , we assume

  • U i ( x ) 0 ; {\displaystyle U_{i}(x)\geq 0;}
  • U i ( x ) {\displaystyle U_{i}(x)} is increasing and concave;
  • U ( x ) {\displaystyle U(x)} is continuous.

The game arises from trying to find a price p {\displaystyle p} so that every player individually optimizes their own welfare. This implies every player must individually find a r g m a x x U i ( x ) p x {\displaystyle {\underset {x}{\operatorname {arg\,max} }}\,U_{i}(x)-px} . Solving for the maximum yields U i ( x ) = p {\displaystyle U_{i}^{'}(x)=p} .

Problem

With this maximum condition, the game then becomes a matter of finding a price that satisfies an equilibrium. Such a price is called a market clearing price.

Possible solution

A popular idea to find the price is a method called fair sharing.1 In this game, every player i {\displaystyle i} is asked for the amount they are willing to pay for the given resource denoted by w i {\displaystyle w_{i}} . The resource is then distributed in x i {\displaystyle x_{i}} amounts by the formula x i = w i B j w j {\displaystyle x_{i}={\frac {w_{i}B}{\sum _{j}w_{j}}}} . This method yields an effective price p = j w j B {\displaystyle p={\frac {\sum _{j}w_{j}}{B}}} . This price can proven to be market clearing; thus, the distribution x 1 , . . . , x n {\displaystyle x_{1},...,x_{n}} is optimal. The proof is as so:

Proof

We have a r g m a x x i U i ( x i ) w i {\displaystyle {\underset {x_{i}}{\operatorname {arg\,max} }}\,U_{i}(x_{i})-w_{i}} = a r g m a x w i U i ( w i B j w j ) w i {\displaystyle ={\underset {w_{i}}{\operatorname {arg\,max} }}\,U_{i}\left({\frac {w_{i}B}{\sum _{j}w_{j}}}\right)-w_{i}} . Hence,

U i ( w i B j w j ) ( B j w j w i B ( j w j ) 2 ) 1 = 0 {\displaystyle U_{i}^{'}\left({\frac {w_{i}B}{\sum _{j}w_{j}}}\right)\left({\frac {B}{\sum _{j}w_{j}}}-{\frac {w_{i}B}{(\sum _{j}w_{j})^{2}}}\right)-1=0}

from which we conclude

U i ( x i ) ( 1 p 1 p ( x i B ) ) 1 = 0 {\displaystyle U_{i}^{'}(x_{i})\left({\frac {1}{p}}-{\frac {1}{p}}\left({\frac {x_{i}}{B}}\right)\right)-1=0}

and thus U i ( x i ) ( 1 x i B ) = p . {\displaystyle U_{i}^{'}(x_{i})\left(1-{\frac {x_{i}}{B}}\right)=p.}

Comparing this result to the equilibrium condition above, we see that when x i B {\displaystyle {\frac {x_{i}}{B}}} is very small, the two conditions equal each other and thus, the fair sharing game is almost optimal.

References

References

  1. Shah, D.; Tsitsiklis, J. N.; Zhong, Y. (2014). "Qualitative properties of α-fair policies in bandwidth-sharing networks". The Annals of Applied Probability. 24 (1): 76–113. arXiv:1104.2340. doi:10.1214/12-AAP915. ISSN 1050-5164. S2CID 3731511.