23,710 research outputs found
Performance evaluation of an open distributed platform for realistic traffic generation
Network researchers have dedicated a notable part of their efforts
to the area of modeling traffic and to the implementation of efficient traffic
generators. We feel that there is a strong demand for traffic generators
capable to reproduce realistic traffic patterns according to theoretical
models and at the same time with high performance. This work presents an open
distributed platform for traffic generation that we called distributed
internet traffic generator (D-ITG), capable of producing traffic (network,
transport and application layer) at packet level and of accurately replicating
appropriate stochastic processes for both inter departure time (IDT) and
packet size (PS) random variables. We implemented two different versions of
our distributed generator. In the first one, a log server is in charge of
recording the information transmitted by senders and receivers and these
communications are based either on TCP or UDP. In the other one, senders and
receivers make use of the MPI library. In this work a complete performance
comparison among the centralized version and the two distributed versions of
D-ITG is presented
Hybrid deterministic stochastic systems with microscopic look-ahead dynamics
We study the impact of stochastic mechanisms on a coupled hybrid system consisting of a general advection-diffusion-reaction partial differential equation and a spatially distributed stochastic lattice noise model. The stochastic dynamics include both spin-flip and spin-exchange type interparticle interactions. Furthermore, we consider a new, asymmetric, single exclusion pro- cess, studied elsewhere in the context of traffic flow modeling, with an one-sided interaction potential which imposes advective trends on the stochastic dynamics. This look-ahead stochastic mechanism is responsible for rich nonlinear behavior in solutions. Our approach relies heavily on first deriving approximate differential mesoscopic equations. These approximations become exact either in the long range, Kac interaction partial differential equation case, or, given sufficient time separation con- ditions, between the partial differential equation and the stochastic model giving rise to a stochastic averaging partial differential equation. Although these approximations can in some cases be crude, they can still give a first indication, via linearized stability analysis, of the interesting regimes for the stochastic model. Motivated by this linearized stability analysis we choose particular regimes where interacting nonlinear stochastic waves are responsible for phenomena such as random switching, convective instability, and metastability, all driven by stochasticity. Numerical kinetic Monte Carlo simulations of the coarse grained hybrid system are implemented to assist in producing solutions and understanding their behavior
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