5 research outputs found
Wardrop Equilibrium in Discrete-Time Selfish Routing with Time-Varying Bounded Delays
This paper presents a multi-commodity, discrete-
time, distributed and non-cooperative routing algorithm, which is
proved to converge to an equilibrium in the presence of
heterogeneous, unknown, time-varying but bounded delays.
Under mild assumptions on the latency functions which describe
the cost associated to the network paths, two algorithms are
proposed: the former assumes that each commodity relies only on
measurements of the latencies associated to its own paths; the
latter assumes that each commodity has (at least indirectly) access
to the measures of the latencies of all the network paths. Both
algorithms are proven to drive the system state to an invariant set
which approximates and contains the Wardrop equilibrium,
defined as a network state in which no traffic flow over the
network paths can improve its routing unilaterally, with the latter
achieving a better reconstruction of the Wardrop equilibrium.
Numerical simulations show the effectiveness of the proposed
approach
Approximating Wardrop Equilibria with Finitely Many Agents
We present efficient algorithms for computing approximate Wardrop equilibria in a distributed and concurrent fashion. Our algorithms are exexuted by a finite number of agents each of which controls the flow of one commodity striving to balance the induced latency over all utilised paths. The set of allowed paths is represented by a DAG. Our algorithms are based on previous work on policies for infinite populations of agents. These policies achieve a convergence time which is independent of the underlying network and depends mildly on the latency functions. These policies can neither be applied to a finite set of agents nor can they be simulated directly due to the exponential number of paths. Our algorithms circumvent these problems by computing a randomised path decomposition in every communication round. Based on this decomposition, flow is shifted from overloaded to underloaded paths. This way, our algorithm can handle exponentially large path collections in polynomial time. Our algorithms are stateless, and the number of communication rounds depends polynomially on the approximation quality and is independent of the topology and size of the network
Approximating Wardrop Equilibria with Finitely Many Agents
1 Introduction We consider routing problems in the Wardrop model. We are given a networkequipped with non-decreasing latency functions mapping flow on the edges to latency. For each of several commodities a fixed flow rate has to be routed from asource to a sink via a collection of paths. A flow vector is said to be at Wardrop equilibrium if for all commodities the latencies of all used paths are minimalwith respect to this commodity. Whereas such equilibria can be formulated as? Supported by DFG grant Vo889/1-3 and by DFG through German excellence cluste