3,393 research outputs found
Natural computing for vehicular networks
La presente tesis aborda el diseño inteligente de soluciones para el despliegue de redes vehiculares ad-hoc (vehicular ad hoc networks, VANETs). Estas son redes de comunicaciĂłn inalĂĄmbrica formada principalmente por vehĂculos y elementos de infraestructura vial. Las VANETs ofrecen la oportunidad para desarrollar aplicaciones revolucionarias en el ĂĄmbito de la seguridad y eficiencia vial. Al ser un dominio tan novedoso, existe una serie de cuestiones abiertas, como el diseño de la infraestructura de estaciones base necesaria y el encaminamiento (routing) y difusiĂłn (broadcasting) de paquetes de datos, que todavĂa no han podido resolverse empleando estrategias clĂĄsicas. Es por tanto necesario crear y estudiar nuevas tĂ©cnicas que permitan de forma eficiente, eficaz, robusta y flexible resolver dichos problemas.
Este trabajo de tesis doctoral propone el uso de computaciĂłn inspirada en la naturaleza o ComputaciĂłn Natural (CN) para tratar algunos de los problemas mĂĄs importantes en el ĂĄmbito de las VANETs, porque representan una serie de algoritmos versĂĄtiles, flexibles y eficientes para resolver problemas complejos. AdemĂĄs de resolver los problemas VANET en los que nos enfocamos, se han realizado avances en el uso de estas tĂ©cnicas para que traten estos problemas de forma mĂĄs eficiente y eficaz. Por Ășltimo, se han llevado a cabo pruebas reales de concepto empleando vehĂculos y dispositivos de comunicaciĂłn reales en la ciudad de MĂĄlaga (España).
La tesis se ha estructurado en cuatro grandes fases. En la primera fase, se han estudiado los principales fundamentos en los que se basa esta tesis. Para ello se hizo un estudio exhaustivo sobre las tecnologĂas que emplean las redes vehiculares, para asĂ, identificar sus principales debilidades. A su vez, se ha profundizado en el anĂĄlisis de la CN como herramienta eficiente para resolver problemas de optimizaciĂłn complejos, y de cĂłmo utilizarla en la resoluciĂłn de los problemas en VANETs. En la segunda fase, se han abordado cuatro problemas de optimizaciĂłn en redes vehiculares: la transferencia de archivos, el encaminamiento (routing) de paquetes, la difusiĂłn (broadcasting) de mensajes y el diseño de la infraestructura de estaciones base necesaria para desplegar redes vehiculares. Para la resoluciĂłn de dichos problemas se han propuesto diferentes algoritmos CN que se clasifican en algoritmos evolutivos (evolutionary algorithms, EAs), mĂ©todos de inteligencia de enjambre (swarm intelligence, SI) y enfriamiento simulado (simulated annealing, SA). Los resultados obtenidos han proporcionado protocolos de han mejorado de forma significativa las comunicaciones en VANETs. En la tercera y Ășltima fase, se han realizado experimentos empleando vehĂculos reales circulando por las carreteras de MĂĄlaga y que se comunicaban entre sĂ. El principal objetivo de estas pruebas ha sido el validar las mejoras que presentan los protocolos que se han optimizado empleando CN. Los resultados obtenidos de las fases segunda y tercera confirman la hipĂłtesis de trabajo, que la CN es una herramienta eficiente para tratar el diseño inteligente en redes vehiculares
Agent-based simulation of electricity markets: a literature review
Liberalisation, climate policy and promotion of renewable energy are challenges to players of the electricity sector in many countries. Policy makers have to consider issues like market power, bounded rationality of players and the appearance of fluctuating energy sources in order to provide adequate legislation. Furthermore the interactions between markets and environmental policy instruments become an issue of increasing importance. A promising approach for the scientific analysis of these developments is the field of agent-based simulation. The goal of this article is to provide an overview of the current work applying this methodology to the analysis of electricity markets. --
Recent Advances in Graph Partitioning
We survey recent trends in practical algorithms for balanced graph
partitioning together with applications and future research directions
Recommended from our members
The congested multicommodity network design problem
This paper studies a version of the fixed-charge multicommodity network design problem where in addition to the traditional costs of flow and design, congestion at nodes is explicitly considered. The problem is initially modeled as a nonlinear integer programming formulation and two solution approaches are proposed: (i) a reformulation of the problem as a mixed integer second order cone program to optimally solve the problem for small to medium scale problem instances, and (ii) an evolutionary algorithm using elements of iterated local search and scatter search to provide upper bounds. Extensive computational results on new benchmark problem instances and on real case data are presented
A smart market for passenger road transport (SMPRT) congestion: an application of computational mechanism design
To control and price negative externalities in passenger road transport, we develop an innovative and integrated computational agent based economics (ACE) model to simulate a market oriented "cap" and trade system. (i) First, there is a computational assessment of a digitized road network model of the real world congestion hot spot to determine the "cap" of the system in terms of vehicle volumes at which traffic efficiency deteriorates and the environmental externalities take off exponentially. (ii) Road users submit bids with the market clearing price at the fixed "cap" supply of travel slots in a given time slice (peak hour) being determined by an electronic sealed bid uniform price Dutch auction. (iii) Cross-sectional demand data on car users who traverse the cordon area is used to model and calibrate the heterogeneous bid submission behaviour in order to construct the inverse demand function and demand elasticities. (iv) The willingness to pay approach with heterogeneous value of time is contrasted with the generalized cost approach to pricing congestion with homogeneous value of travel time.
The Beginnings and Prospective Ending of âEnd-to-Endâ: An Evolutionary Perspective On the Internetâs Architecture
The technology of âthe Internetâ is not static. Although its âend-to- endâ architecture has made this âconnection-lessâ communications system readily âextensible,â and highly encouraging to innovation both in hardware and software applications, there are strong pressures for engineering changes. Some of these are wanted to support novel transport services (e.g. voice telephony, real-time video); others would address drawbacks that appeared with opening of the Internet to public and commercial traffic - e.g., the difficulties of blocking delivery of offensive content, suppressing malicious actions (e.g. âdenial of serviceâ attacks), pricing bandwidth usage to reduce congestion. The expected gains from making âimprovementsâ in the core of the network should be weighed against the loss of the social and economic benefits that derive from the âend-to-endâ architectural design. Even where technological âfixesâ can be placed at the networksâ edges, the option remains to search for alternative, institutional mechanisms of governing conduct in cyberspace.
Systems approaches and algorithms for discovery of combinatorial therapies
Effective therapy of complex diseases requires control of highly non-linear
complex networks that remain incompletely characterized. In particular, drug
intervention can be seen as control of signaling in cellular networks.
Identification of control parameters presents an extreme challenge due to the
combinatorial explosion of control possibilities in combination therapy and to
the incomplete knowledge of the systems biology of cells. In this review paper
we describe the main current and proposed approaches to the design of
combinatorial therapies, including the empirical methods used now by clinicians
and alternative approaches suggested recently by several authors. New
approaches for designing combinations arising from systems biology are
described. We discuss in special detail the design of algorithms that identify
optimal control parameters in cellular networks based on a quantitative
characterization of control landscapes, maximizing utilization of incomplete
knowledge of the state and structure of intracellular networks. The use of new
technology for high-throughput measurements is key to these new approaches to
combination therapy and essential for the characterization of control
landscapes and implementation of the algorithms. Combinatorial optimization in
medical therapy is also compared with the combinatorial optimization of
engineering and materials science and similarities and differences are
delineated.Comment: 25 page
- âŠ