37,752 research outputs found
Exact-Differential Large-Scale Traffic Simulation
Analyzing large-scale traffics by simulation needs repeating execution many times with various patterns of scenarios or parameters. Such repeating execution brings about big redundancy because the change from a prior scenario to a later scenario is very minor in most cases, for example, blocking only one of roads or changing the speed limit of several roads. In this paper, we propose a new redundancy reduction technique, called exact-differential simulation, which enables to simulate only changing scenarios in later execution while keeping exactly same results as in the case of whole simulation. The paper consists of two main efforts: (i) a key idea and algorithm of the exact-differential simulation, (ii) a method to build large-scale traffic simulation on the top of the exact-differential simulation. In experiments of Tokyo traffic simulation, the exact-differential simulation shows 7.26 times as much elapsed time improvement in average and 2.26 times improvement even in the worst case as the whole simulation
Towards large-scale what-if traffic simulation with exact-differential simulation
To analyze and predict a behavior of large-scale traffics with what-if simulation, it needs to repeat many times with various patterns of what-if scenarios. In this paper, we propose new techniques to efficiently repeat what-if simulation tasks with exact-differential simulation. The paper consists of two main efforts: what-if scenario filtering and exact-differential cloning. The what-if scenario filtering enables to pick up meaningful what-if scenarios and reduces the number of what-if scenarios, which directly decreases total execution time of repeating. The exact-differential cloning enables to execute exact-differential simulation tasks in parallel to improve its total execution time. In our preliminary evaluation in Tokyo bay area's traffic simulation, we show potential of our proposals by estimating how the what-if scenarios filtering reduces the number of meaningless scenarios and also by estimating a performance improvement from our previous works with the exact-differential cloning
Implicit Methods for Equation-Free Analysis: Convergence Results and Analysis of Emergent Waves in Microscopic Traffic Models
We introduce a general formulation for an implicit equation-free method in
the setting of slow-fast systems. First, we give a rigorous convergence result
for equation-free analysis showing that the implicitly defined coarse-level
time stepper converges to the true dynamics on the slow manifold within an
error that is exponentially small with respect to the small parameter measuring
time scale separation. Second, we apply this result to the idealized traffic
modeling problem of phantom jams generated by cars with uniform behavior on a
circular road. The traffic jams are waves that travel slowly against the
direction of traffic. Equation-free analysis enables us to investigate the
behavior of the microscopic traffic model on a macroscopic level. The standard
deviation of cars' headways is chosen as the macroscopic measure of the
underlying dynamics such that traveling wave solutions correspond to equilibria
on the macroscopic level in the equation-free setup. The collapse of the
traffic jam to the free flow then corresponds to a saddle-node bifurcation of
this macroscopic equilibrium. We continue this bifurcation in two parameters
using equation-free analysis.Comment: 35 page
Optimisation of Mobile Communication Networks - OMCO NET
The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University.
The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing
An exact particle method for scalar conservation laws and its application to stiff reaction kinetics
An "exact" method for scalar one-dimensional hyperbolic conservation laws is
presented. The approach is based on the evolution of shock particles, separated
by local similarity solutions. The numerical solution is defined everywhere,
and is as accurate as the applied ODE solver. Furthermore, the method is
extended to stiff balance laws. A special correction approach yields a method
that evolves detonation waves at correct velocities, without resolving their
internal dynamics. The particle approach is compared to a classical finite
volume method in terms of numerical accuracy, both for conservation laws and
for an application in reaction kinetics.Comment: 14 page, 7 figures, presented in the Fifth International Workshop on
Meshfree Methods for Partial Differential Equation
Elastic calls in an integrated services network: the greater the call size variability the better the QoS
We study a telecommunications network integrating prioritized stream calls and delay tolerant elastic calls that are served with the remaining (varying) service capacity according to a processor sharing discipline. The remarkable observation is presented and analytically supported that the expected elastic call holding time is decreasing in the variability of the elastic call size distribution. As a consequence, network planning guidelines or admission control schemes that are developed based on deterministic or lightly variable elastic call sizes are likely to be conservative and inefficient, given the commonly acknowledged property of e.g.\ \textsc{www}\ documents to be heavy tailed. Application areas of the model and results include fixed \textsc{ip} or \textsc{atm} networks and mobile cellular \textsc{gsm}/\textsc{gprs} and \textsc{umts} networks. \u
A characteristic particle method for traffic flow simulations on highway networks
A characteristic particle method for the simulation of first order
macroscopic traffic models on road networks is presented. The approach is based
on the method "particleclaw", which solves scalar one dimensional hyperbolic
conservations laws exactly, except for a small error right around shocks. The
method is generalized to nonlinear network flows, where particle approximations
on the edges are suitably coupled together at the network nodes. It is
demonstrated in numerical examples that the resulting particle method can
approximate traffic jams accurately, while only devoting a few degrees of
freedom to each edge of the network.Comment: 15 pages, 5 figures. Accepted to the proceedings of the Sixth
International Workshop Meshfree Methods for PDE 201
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