31,462 research outputs found
A Stackelberg Strategy for Routing Flow over Time
Routing games are used to to understand the impact of individual users'
decisions on network efficiency. Most prior work on routing games uses a
simplified model of network flow where all flow exists simultaneously, and
users care about either their maximum delay or their total delay. Both of these
measures are surrogates for measuring how long it takes to get all of a user's
traffic through the network. We attempt a more direct study of how competition
affects network efficiency by examining routing games in a flow over time
model. We give an efficiently computable Stackelberg strategy for this model
and show that the competitive equilibrium under this strategy is no worse than
a small constant times the optimal, for two natural measures of optimality
Routing Games over Time with FIFO policy
We study atomic routing games where every agent travels both along its
decided edges and through time. The agents arriving on an edge are first lined
up in a \emph{first-in-first-out} queue and may wait: an edge is associated
with a capacity, which defines how many agents-per-time-step can pop from the
queue's head and enter the edge, to transit for a fixed delay. We show that the
best-response optimization problem is not approximable, and that deciding the
existence of a Nash equilibrium is complete for the second level of the
polynomial hierarchy. Then, we drop the rationality assumption, introduce a
behavioral concept based on GPS navigation, and study its worst-case efficiency
ratio to coordination.Comment: Submission to WINE-2017 Deadline was August 2nd AoE, 201
Compact Oblivious Routing
Oblivious routing is an attractive paradigm for large distributed systems in which centralized control and frequent reconfigurations are infeasible or undesired (e.g., costly). Over the last almost 20 years, much progress has been made in devising oblivious routing schemes that guarantee close to optimal load and also algorithms for constructing such schemes efficiently have been designed. However, a common drawback of existing oblivious routing schemes is that they are not compact: they require large routing tables (of polynomial size), which does not scale.
This paper presents the first oblivious routing scheme which guarantees close to optimal load and is compact at the same time - requiring routing tables of polylogarithmic size. Our algorithm maintains the polylogarithmic competitive ratio of existing algorithms, and is hence particularly well-suited for emerging large-scale networks
Modeling Tiered Pricing in the Internet Transit Market
ISPs are increasingly selling "tiered" contracts, which offer Internet
connectivity to wholesale customers in bundles, at rates based on the cost of
the links that the traffic in the bundle is traversing. Although providers have
already begun to implement and deploy tiered pricing contracts, little is known
about how such pricing affects ISPs and their customers. While contracts that
sell connectivity on finer granularities improve market efficiency, they are
also more costly for ISPs to implement and more difficult for customers to
understand. In this work we present two contributions: (1) we develop a novel
way of mapping traffic and topology data to a demand and cost model; and (2) we
fit this model on three large real-world networks: an European transit ISP, a
content distribution network, and an academic research network, and run
counterfactuals to evaluate the effects of different pricing strategies on both
the ISP profit and the consumer surplus. We highlight three core findings.
First, ISPs gain most of the profits with only three or four pricing tiers and
likely have little incentive to increase granularity of pricing even further.
Second, we show that consumer surplus follows closely, if not precisely, the
increases in ISP profit with more pricing tiers. Finally, the common ISP
practice of structuring tiered contracts according to the cost of carrying the
traffic flows (e.g., offering a discount for traffic that is local) can be
suboptimal and that dividing contracts based on both traffic demand and the
cost of carrying it into only three or four tiers yields near-optimal profit
for the ISP
A practical fpt algorithm for Flow Decomposition and transcript assembly
The Flow Decomposition problem, which asks for the smallest set of weighted
paths that "covers" a flow on a DAG, has recently been used as an important
computational step in transcript assembly. We prove the problem is in FPT when
parameterized by the number of paths by giving a practical linear fpt
algorithm. Further, we implement and engineer a Flow Decomposition solver based
on this algorithm, and evaluate its performance on RNA-sequence data.
Crucially, our solver finds exact solutions while achieving runtimes
competitive with a state-of-the-art heuristic. Finally, we contextualize our
design choices with two hardness results related to preprocessing and weight
recovery. Specifically, -Flow Decomposition does not admit polynomial
kernels under standard complexity assumptions, and the related problem of
assigning (known) weights to a given set of paths is NP-hard.Comment: Introduces software package Toboggan: Version 1.0.
http://dx.doi.org/10.5281/zenodo.82163
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