Mecanismes i Teoria de Jocs en Xarxes

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Crèdits
6
Tipus
Obligatòria d'especialitat (Xarxes de Computadors i Sistemes Distribuïts)
Requisits
Aquesta assignatura no té requisits, però té capacitats prèvies
Departament
AC
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The goal of this course is giving the student a background in the methodologies in the advanced design of mechanisms using non-lineal convex optimization and game theory. The program will cover from basic concepts related to convexity, convex optimization problems, Game Theory, Nash Equilibria, to applications of these methodologies to networking such as resource allocation, back-pressure models, power-control models compressive sensing, game theory in wireless networks, pricing models in networks, game theory in routing problems or incentives in P2P systems.

Hores setmanals

Teoria
4
Problemes
0
Laboratori
0
Aprenentatge dirigit
0
Aprenentatge autònom
7

Objectius

  1. Capacity to formulate a convex optimization problem
    Competències relacionades: CEE2.3, CTR6,
  2. Capacity to apply convex optimization to networking problems.
    Competències relacionades: CEE2.2, CEE2.3, CEE2.1, CTR6,
  3. Capacity to understand what game theory is and how a game is solved.
    Competències relacionades: CEE2.3, CTR6,
  4. Capacity to apply game theory to networking problems
    Competències relacionades: CEE2.3, CTR6,

Continguts

  1. Convex Optimization basics
    Convex sets, convex functions, convex optimization problems (COP) and duality (Lagrange dual function, KKT optimality conditions), methods for solving COP's (General Descent Methods, Interior Point Methods)
  2. Convex Optimization Applications to networking
    Exxamples on Resource allocation in networks, back-pressure, Power control, Publish-subscribe in DTN, Compressive Sensing.
  3. Game Theory basics
    Strategic and Extensive Forms of a Game, Non cooperative Games (Nash pure and mixed equilibria, correlated equilibria), Cooperative Games (core of a game, Shapley values, Nash Arbitration scheme), cost-sharing (Braess Paradox, Price of Anarchy and Stability), Auctions.
  4. Game Theory Applications to Networking
    Wireless Networking games, Energy-Efficient Power Control games, pricing, P2P games

Activitats

Activitat Acte avaluatiu


Convex Optimization basics


Objectius: 1
Continguts:
Teoria
10h
Problemes
0h
Laboratori
0h
Aprenentatge dirigit
0h
Aprenentatge autònom
0h

Convex Optimization Applications to Networking


Objectius: 2
Continguts:
Teoria
10h
Problemes
0h
Laboratori
0h
Aprenentatge dirigit
0h
Aprenentatge autònom
0h

Game Theory Basics


Objectius: 3
Continguts:
Teoria
10h
Problemes
0h
Laboratori
0h
Aprenentatge dirigit
0h
Aprenentatge autònom
0h

Game Theory Applications to Networking


Objectius: 4
Teoria
10h
Problemes
0h
Laboratori
0h
Aprenentatge dirigit
0h
Aprenentatge autònom
0h

Evaluations

Evaluations: exam and presentation from students

Teoria
5h
Problemes
0h
Laboratori
0h
Aprenentatge dirigit
0h
Aprenentatge autònom
0h

Estudi del material



Teoria
0h
Problemes
0h
Laboratori
0h
Aprenentatge dirigit
0h
Aprenentatge autònom
0h

Metodologia docent

During the initial sessions of each topic, the main results will be explained in the blackboard. the student will solve some exercises to prove their skills in the topic. Finally, there will be some sessions devoted to discuss in the classroom models taken from research papers that apply the related topics.

Mètode d'avaluació

The evaluation is based on different activities

- Short projects and presentations in which the student has to deliver and defend the obtained results (P)
- A final exam (FE)

Each of the activities will be evaluated (0=
The final mark for the course (FM) will be:

FM= 0.60xP+0.4xFE

Where P=(1/N) x Sum (Pi) with i=1,...N

with Pi the projects and oral presentation mark. There will be a minimum of 2 practical projects and 1 oral presentation.

Bibliografia

Bàsica:

Web links

Capacitats prèvies

None.