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Competitive Routing in MultiUser Communication Networks

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Title: Competitive Routing in MultiUser Communication Networks


1
Competitive Routing in Multi-User Communication
Networks
  • Presentation By Yuval Lifshitz
  • In Seminar Computational Issues in Game Theory
    (2002/3)
  • By Prof. Yishay Mansour
  • Original Paper A. Orda, R. Rom and N. Shimkin,
    Competitive Routing in Multi-User Communication
    Networks, pp. 964-971 in Proceedings of IEEE
    INFOCOM'93

2
Introduction
  • Single Entity Single Control Objective
  • Either centralized or distributed control
  • Optimization of average network delay
  • Passive Users
  • Resource shared by a group of active users
  • Different measures of satisfaction
  • Optimizing subjective demands
  • Dynamic system

3
Introduction
  • Questions
  • Does an equilibrium point exists?
  • Is it unique?
  • Does the dynamic system converge to it?

4
Introduction
  • What was done so far (1993)
  • Economic tools for flow control and resource
    allocation
  • Routing two nodes connected with parallel
    identical links (M/M/c queues)
  • Rosen (1965) conditions for existence, uniqueness
    and stability

5
Introduction
  • Goals of This Paper
  • The uniqueness problem of a convex game (convex
    but not common objective functions)
  • Use specificities of the problem (results cannot
    be derived directly from Rosen)
  • Two nodes connected by a set of parallel links,
    not necessarily queues
  • General networks

6
Model and Formulation
  • Set of m users
  • Set of n parallel communication links
  • Users throughput demand stochastic process
    with average
  • Fractional assignment
  • Expected flow of user on link
  • Users flows fulfill the demand constraint
  • Total flow on link

7
Model and Formulation
  • Link flow vector
  • User flow configuration
  • System flow configuration
  • Feasible user flow obey the demand constraint
  • Set of all feasible user flows
  • Feasible system flow all users flows are
    feasible
  • Set of feasible system flows

8
Model and Formulation
  • User cost as a function of the systems flow
    configuration
  • Nash Equilibrium Point (NEP)
  • System flow configuration such that no user finds
    it beneficial to change its flow on any link
  • A configuration
  • that for each i holds

9
Model and Formulation
  • Assumptions of the cost function
  • G1 It is a sum of user-link cost function
  • G2 might be infinite
  • G3 is convex
  • G4 Whenever finite is continuously differentiable
  • G5 At least one user with infinite flow (if
    exists) can change its flow configuration to make
    it finite

10
Model and Formulation
  • Convex Game Rosen guarantees the existence of
    NEP
  • Kuhn-Tucker conditions for a feasible
    configuration to be a NEP
  • We will investigate uniqueness and convergence of
    a system

11
Model and Formulation
  • Type-A cost functions
  • is a function of the users flow on the link
    and the total flow on the link
  • The functions in increasing in both its arguments
  • The functions partial derivatives are increasing
    in both arguments

12
Model and Formulation
  • Type-B cost functions
  • Performance function of a link measures its cost
    per unit
  • Multiplicative form
  • cannot be zero, but might be infinite
  • is strictly increasing and convex
  • is continuously differentiable

13
Model and Formulation
  • Type-C cost functions
  • Based on M/M/1 model of a link
  • They are Type-B functions
  • If then
  • else
  • is the capacity of the link

14
Part I Parallel links
Links
Users
15
Uniqueness
  • Theorem In a network of parallel links where the
    cost function of each user is of type-A the NEP
    is unique.
  • Kuhn-Tucker conditions
  • for each user i there exists (Lagrange
    multiplier), such that for every link l, if
  • then else
  • when

16
Monotonicity
  • Theorem In a network of parallel links with
    identical type-A cost functions. For any pair of
    users i and j, if then
  • for each link l.
  • Lemma Suppose that holds for some link l and
    users i and j. Then, for each link l

17
Monotonicity
  • If all users has the same demand then
  • If then
  • Monotonic partition among users
  • User with higher demands uses more links, and
    more of each link

18
Monotonicity
  • Theorem In a network of parallel links with
    type-C cost functions. For any pair of links l
    and l, if then
  • for each user i.
  • Lemma Assume that for links l and l the
    following holds
  • Then for each user j.

19
Convergence
  • Two users sharing two links
  • ESS Elementary Stepwise System
  • Start at non-equilibrium point
  • Exact minimization is achieved at each stage
  • All operations are done instantly
  • Users i flow on link l at the end of step n

20
Convergence
  • Odd stage 2n-1 User 1 find its optimum when the
    other users 2n-2 step is known.
  • Even stage 2n User 2 find its optimum when the
    others user 2n-1 step is known.

User 2
Steps
User 1
21
Convergence
  • Theorem Let an ESS be initialized with a
    feasible configuration, Then the system
    configuration converges over time to the NEP,
    meaning
  • Lemma Let be two feasible flows for user 1.
    And optimal flows for user 2 against the above.
    If then

22
Part II General Topology
Network
Users
23
Non-uniqueness NEP1
10 ,12
User 1
40
22 ,18
14 ,2
1
2
3
40
8 ,16
User 2
8 ,10
24 ,14
4
24
Non-uniqueness NEP2
18 ,5
User 1
40
20 ,23
4 ,13
1
2
3
40
8 ,16
User 2
2 ,12
22 ,18
4
25
Non-monotonous
T(3 ,1)20
User 1
7
T(1 ,2)1
T(4 ,3)4
1
2
3
4
User 2
T(3 ,1)21
T(4 ,3)5
4
26
Diagonal Strict Convexity
  • Weighted sum of a configuration
  • Pseudo-Gradient

27
Diagonal Strict Convexity
  • Theorem (Rosen) If there exists a vector
  • for which the system is DSC. Then the NEP is
    unique
  • Pseudo-Jacobian
  • Corollary If the Pseudo-Jacobian matrix is
    positive definite then the NEP is unique

28
Symmetrical Users
  • All users has the same demand (same source and
    destination)
  • Lemma
  • Theorem A network with symmetrical users has a
    unique NEP

29
All-Positive Flows
  • All users must have the same source and
    destination
  • Type-B cost functions
  • For a subclass of links, on which the flows are
    strictly positive, the NEP is unique.

30
Further Research
  • General network uniqueness for type-B functions
  • Stability (convergence)
  • Restrictions on users (non non-cooperative games)
  • Delay in measurements real dynamic system
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