129,872 research outputs found
Threshold games and cooperation on multiplayer graphs
Objective: The study investigates the effect on cooperation in multiplayer
games, when the population from which all individuals are drawn is structured -
i.e. when a given individual is only competing with a small subset of the
entire population.
Method: To optimize the focus on multiplayer effects, a class of games were
chosen for which the payoff depends nonlinearly on the number of cooperators -
this ensures that the game cannot be represented as a sum of pair-wise
interactions, and increases the likelihood of observing behaviour different
from that seen in two-player games. The chosen class of games are named
"threshold games", and are defined by a threshold, , which describes the
minimal number of cooperators in a given match required for all the
participants to receive a benefit. The model was studied primarily through
numerical simulations of large populations of individuals, each with
interaction neighbourhoods described by various classes of networks.
Results: When comparing the level of cooperation in a structured population
to the mean-field model, we find that most types of structure lead to a
decrease in cooperation. This is both interesting and novel, simply due to the
generality and breadth of relevance of the model - it is likely that any model
with similar payoff structure exhibits related behaviour.
More importantly, we find that the details of the behaviour depends to a
large extent on the size of the immediate neighbourhoods of the individuals, as
dictated by the network structure. In effect, the players behave as if they are
part of a much smaller, fully mixed, population, which we suggest an expression
for.Comment: in PLOS ONE, 4th Feb 201
On Projection-Based Model Reduction of Biochemical Networks-- Part I: The Deterministic Case
This paper addresses the problem of model reduction for dynamical system
models that describe biochemical reaction networks. Inherent in such models are
properties such as stability, positivity and network structure. Ideally these
properties should be preserved by model reduction procedures, although
traditional projection based approaches struggle to do this. We propose a
projection based model reduction algorithm which uses generalised block
diagonal Gramians to preserve structure and positivity. Two algorithms are
presented, one provides more accurate reduced order models, the second provides
easier to simulate reduced order models. The results are illustrated through
numerical examples.Comment: Submitted to 53rd IEEE CD
CliqueStream: an efficient and fault-resilient live streaming network on a clustered peer-to-peer overlay
Several overlay-based live multimedia streaming platforms have been proposed
in the recent peer-to-peer streaming literature. In most of the cases, the
overlay neighbors are chosen randomly for robustness of the overlay. However,
this causes nodes that are distant in terms of proximity in the underlying
physical network to become neighbors, and thus data travels unnecessary
distances before reaching the destination. For efficiency of bulk data
transmission like multimedia streaming, the overlay neighborhood should
resemble the proximity in the underlying network. In this paper, we exploit the
proximity and redundancy properties of a recently proposed clique-based
clustered overlay network, named eQuus, to build efficient as well as robust
overlays for multimedia stream dissemination. To combine the efficiency of
content pushing over tree structured overlays and the robustness of data-driven
mesh overlays, higher capacity stable nodes are organized in tree structure to
carry the long haul traffic and less stable nodes with intermittent presence
are organized in localized meshes. The overlay construction and fault-recovery
procedures are explained in details. Simulation study demonstrates the good
locality properties of the platform. The outage time and control overhead
induced by the failure recovery mechanism are minimal as demonstrated by the
analysis.Comment: 10 page
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