67,886 research outputs found
A time dependent performance model for multihop wireless networks with CBR traffic
In this paper, we develop a performance modeling technique for analyzing the time varying network layer queueing behavior of multihop wireless networks with constant bit rate traffic. Our approach is a hybrid of fluid flow queueing modeling and a time varying connectivity matrix. Network queues are modeled using fluid-flow based differential equation models which are solved using numerical methods, while node mobility is modeled using deterministic or stochastic modeling of adjacency matrix elements. Numerical and simulation experiments show that the new approach can provide reasonably accurate results with significant improvements in the computation time compared to standard simulation tools. © 2010 IEEE
An efficient hybrid model and dynamic performance analysis for multihop wireless networks
Multihop wireless networks can be subjected to nonstationary phenomena due to a dynamic network topology and time varying traffic. However, the simulation techniques used to study multihop wireless networks focus on the steady-state performance even though transient or nonstationary periods will often occur. Moreover, the majority of the simulators suffer from poor scalability. In this paper, we develop an efficient performance modeling technique for analyzing the time varying queueing behavior of multihop wireless networks. The one-hop packet transmission (service) time is assumed to be deterministic, which could be achieved by contention-free transmission, or approximated in sparse or lightly loaded multihop wireless networks. Our model is a hybrid of time varying adjacency matrix and fluid flow based differential equations, which represent dynamic topology changes and nonstationary network queues, respectively. Numerical experiments show that the hybrid fluid based model can provide reasonably accurate results much more efficiently than standard simulators. Also an example application of the modeling technique is given showing the nonstationary network performance as a function of node mobility, traffic load and wireless link quality. © 2013 IEEE
A low-cost parallel implementation of direct numerical simulation of wall turbulence
A numerical method for the direct numerical simulation of incompressible wall
turbulence in rectangular and cylindrical geometries is presented. The
distinctive feature resides in its design being targeted towards an efficient
distributed-memory parallel computing on commodity hardware. The adopted
discretization is spectral in the two homogeneous directions; fourth-order
accurate, compact finite-difference schemes over a variable-spacing mesh in the
wall-normal direction are key to our parallel implementation. The parallel
algorithm is designed in such a way as to minimize data exchange among the
computing machines, and in particular to avoid taking a global transpose of the
data during the pseudo-spectral evaluation of the non-linear terms. The
computing machines can then be connected to each other through low-cost network
devices. The code is optimized for memory requirements, which can moreover be
subdivided among the computing nodes. The layout of a simple, dedicated and
optimized computing system based on commodity hardware is described. The
performance of the numerical method on this computing system is evaluated and
compared with that of other codes described in the literature, as well as with
that of the same code implementing a commonly employed strategy for the
pseudo-spectral calculation.Comment: To be published in J. Comp. Physic
Analyzing and Modeling the Performance of the HemeLB Lattice-Boltzmann Simulation Environment
We investigate the performance of the HemeLB lattice-Boltzmann simulator for
cerebrovascular blood flow, aimed at providing timely and clinically relevant
assistance to neurosurgeons. HemeLB is optimised for sparse geometries,
supports interactive use, and scales well to 32,768 cores for problems with ~81
million lattice sites. We obtain a maximum performance of 29.5 billion site
updates per second, with only an 11% slowdown for highly sparse problems (5%
fluid fraction). We present steering and visualisation performance measurements
and provide a model which allows users to predict the performance, thereby
determining how to run simulations with maximum accuracy within time
constraints.Comment: Accepted by the Journal of Computational Science. 33 pages, 16
figures, 7 table
Optimisation of Mobile Communication Networks - OMCO NET
The mini conference âOptimisation of Mobile Communication Networksâ 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
Applying Mean-field Approximation to Continuous Time Markov Chains
The mean-field analysis technique is used to perform analysis of a systems with a large number of components to determine the emergent deterministic behaviour and how this behaviour modifies when its parameters are perturbed. The computer science performance modelling and analysis community has found the mean-field method useful for modelling large-scale computer and communication networks. Applying mean-field analysis from the computer science perspective requires the following major steps: (1) describing how the agents populations evolve by means of a system of differential equations, (2) finding the emergent
deterministic behaviour of the system by solving such differential equations, and (3) analysing properties of this behaviour either by relying on simulation or by using logics. Depending on the system under analysis, performing these steps may become challenging. Often, modifications
of the general idea are needed. In this tutorial we consider illustrating examples to discuss how the mean-field method is used in different application areas. Starting from the application of the classical technique,
moving to cases where additional steps have to be used, such as systems with local communication. Finally we illustrate the application of the simulation and
uid model checking analysis techniques
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