Congestion Control and Optimal Maintenance of Communication Networks with Stochastic Cost Functions: A Variational Formulation

Mauro Passacantando () and Fabio Raciti ()
Additional contact information
Mauro Passacantando: University of Pisa
Fabio Raciti: University of Catania

A chapter in Mathematical Analysis in Interdisciplinary Research, 2021, pp 599-617 from Springer

Abstract: Abstract We consider a game theory model of congestion control in communication networks, where each player is a user who wishes to maximize his/her flow over a path in the network. We allow for stochastic fluctuations of the cost function of each player, which consists of two parts: a pricing and a utility term. The solution concept we look for is the mean value of the (unique) variational Nash equilibrium of the game. Furthermore, we assume that it is possible to invest a certain amount of money to improve the network by enhancing the capacity of its links and, because of limited financial resources, an optimal choice of the links to improve has to be made. We model the investment problem as a nonlinear knapsack problem with generalized Nash equilibrium constraints in probabilistic Lebesgue spaces and solve it numerically for some examples.

Keywords: Generalized Nash equilibrium; Stochastic cost function; Congestion control; Investment optimization (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-030-84721-0_27

Ordering information: This item can be ordered from
http://www.springer.com/9783030847210

DOI: 10.1007/978-3-030-84721-0_27

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().