Artificial ants for active routing

Ant colonies in nature provide a good model for a distributed, robust and adaptive routing algorithm. This paper proposes the adoption of the same strategy for the routing of packets in an Active Network. Traditional store-and-forward routers are replaced by active intermediate systems, which are able to perform computations on transient packets, in a way that results very helpful for developing and dynamically deploying new protocols. The adoption of the Active Networks paradigm associated with a cooperative learning environment produces a robust, decentralized routing algorithm capable of adapting to network traffic conditions.

Adaptive routing in active networks

New conceptual ideas on network architectures have been proposed in the recent past. Current store-andforward routers are replaced by active intermediate systems, which are able to perform computations on transient packets, in a way that results very helpful for developing and deploying new protocols in a short time. This paper introduces a new routing algorithm, based on a congestion metric, and inspired by the behavior of ants in nature. The use of the Active Networks paradigm associated with a cooperative learning environment produces a robust, decentralized algorithm capable of adapting quickly to changing conditions.

An oblivious shortest-path routing algorithm for fully connected cubic networks

Fully connected cubic networks (FCCNs) are a class of newly proposed hierarchical interconnection networks for multicomputer systems, which enjoy the strengths of constant node degree and good expandability. The shortest path routing in FCCNs is an open problem. In this paper, we present an oblivious routing algorithm for n-level FCCN with N = 8(n) nodes, and prove that this algorithm creates a shortest path from the source to the destination. At the costs of both an O(N)-parallel-step off-line preprocessing phase and a list of size N stored at each node, the proposed algorithm is carried out at each related node in O(n) time. In some cases the proposed algorithm is superior to the one proposed by Chang and Wang in terms of the length of the routing path. This justifies the utility of our routing strategy. (C) 2006 Elsevier Inc. All rights reserved.

Characterising North Atlantic weather patterns for climate-optimal aircraft routing

Daily weather patterns over the North Atlantic are classified into relevant types: typical weather patterns that may characterize the range of climate impacts from aviation in this region, for both summer and winter. The motivation is to provide a set of weather types to facilitate an investigation of climate-optimal aircraft routing of trans-Atlantic flights (minimizing the climate impact on a flight-by-flight basis). Using the New York to London route as an example, the time-optimal route times are shown to vary by over 60 min, to take advantage of strong tailwinds or avoid headwinds, and for eastbound routes latitude correlates well with the latitude of the jet stream. The weather patterns are classified by their similarity to the North Atlantic Oscillation and East Atlantic teleconnection patterns. For winter, five types are defined; in summer, when there is less variation in jet latitude, only three types are defined. The types can be characterized by the jet strength and position, and therefore the location of the time-optimal routes varies by type. Simple proxies for the climate impact of carbon dioxide, ozone, water vapour and contrails are defined, which depend on parameters such as the route time, latitude and season, the time spent flying in the stratosphere, and the distance over which the air is supersaturated with respect to ice. These proxies are then shown to vary between weather types and between eastbound and westbound routes.

Fibrils and nanotubes assembled from a modified amyloid-β peptide fragment differ in the packing of the same β-sheet building blocks

The peptide AAKLVFF assembles into fibrils in water and nanotubes in methanol. Solid-state NMR data are consistent with fibrils constructed from β-sheet bilayers and nanotubes bounded by a wall of offset β-sheet monolayers. Remarkably distinct morphologies are thus traced to subtle differences in the arrangement of the same fundamental building blocks.

Simple and effective technical procedures for the packing and application of nanospray PicoFrit HPLC columns for proteomic analyses

A simple procedure was developed for packing PicoFrit HPLC columns with chromatographic stationary phase using a reservoir fabricated from standard laboratory HPLC fittings. Packed columns were mounted onto a stainless steel ultra-low volume precolumn filter assembly containing a 0.5-mu m pore size steel frit. This format provided a conduit for the application of the nanospray voltage and protected the column from obstruction by sample material. The system was characterised and operational performance assessed by analysis of a range of peptide standards (n = 9).

Effect of a methyl group on the spontaneous resolution of a square-pyramidal coordination compound: crystal packing and conglomerate formation

Reaction of [Cu(pic)2]·2H2O (where pic stands for 2-picolinato) with 2-({[2-(dimethylamino)ethyl]amino}methyl)phenol (HL1) produces the square-pyramidal complex [CuL1(pic)] (1), which crystallizes as a conglomerate (namely a mixture of optically pure crystals) in the Sohncke space group P212121. The use of the methylated ligand at the benzylic position, i.e. (±)-2-(1-{[2-(dimethylamino)ethyl]amino}ethyl)phenol (HL2), yields the analogous five-coordinate complex [CuL2(pic)] (2) that crystallizes as a true racemate (namely the crystals contain both enantiomers) in the centrosymmetric space group P21/c. Density functional theory (DFT) calculations indicate that the presence of the methyl group indeed leads to a distinct crystallization behaviour, not only by intramolecular steric effects, but also because its involvement in non-covalent C–H···π and hydrophobic intermolecular contacts appears to be an important factor contributing to the crystal-lattice (stabilizing) energy of 2

Global runoff routing with the hydrological component of the ECMWF NWP system

A global river routing scheme coupled to the ECMWF land surface model is implemented and tested within the framework of the Global Soil Wetness Project II, to evaluate the feasibility of modelling global river runoff at a daily time scale. The exercise is designed to provide benchmark river runoff predictions needed to verify the land surface model. Ten years of daily runoff produced by the HTESSEL land surface scheme is input into the TRIP2 river routing scheme in order to generate daily river runoff. These are then compared to river runoff observations from the Global Runoff Data Centre (GRDC) in order to evaluate the potential and the limitations. A notable source of inaccuracy is bias between observed and modelled discharges which is not primarily due to the modelling system but instead of to the forcing and quality of observations and seems uncorrelated to the river catchment size. A global sensitivity analysis and Generalised Likelihood Uncertainty Estimation (GLUE) uncertainty analysis are applied to the global routing model. The ground water delay parameter is identified as being the most sensitive calibration parameter. Significant uncertainties are found in results, and those due to parameterisation of the routing model are quantified. The difficulty involved in parameterising global river discharge models is discussed. Detailed river runoff simulations are shown for the river Danube, which match well observed river runoff in upstream river transects. Results show that although there are errors in runoff predictions, model results are encouraging and certainly indicative of useful runoff predictions, particularly for the purpose of verifying the land surface scheme hydrologicly. Potential of this modelling system on future applications such as river runoff forecasting and climate impact studies is highlighted. Copyright © 2009 Royal Meteorological Society.

Quantitative ventilation assessments of idealized urban canopy layers with various urban layouts and the same building packing density

This paper investigates urban canopy layers (UCL) ventilation under neutral atmospheric condition with the same building area density (λp=0.25) and frontal area density (λf=0.25) but various urban sizes, building height variations, overall urban forms and wind directions. Turbulent airflows are first predicted by CFD simulations with standard k-ε model evaluated by wind tunnel data. Then air change rates per hour (ACH) and canopy purging flow rate (PFR) are numerically analyzed to quantify the rate of air exchange and the net ventilation capacity induced by mean flows and turbulence. With a parallel approaching wind (θ=0o), the velocity ratio first decreases in the adjustment region, followed by the fully-developed region where the flow reaches a balance. Although the flow quantities macroscopically keep constant, however ACH decreases and overall UCL ventilation becomes worse if urban size rises from 390m to 5km. Theoretically if urban size is infinite, ACH may reach a minimum value depending on local roof ventilation, and it rises from 1.7 to 7.5 if the standard deviation of building height variations increases (0% to 83.3%). Overall UCL ventilation capacity (PFR) with a square overall urban form (Lx=Ly=390m) is better as θ=0o than oblique winds (θ=15o, 30o, 45o), and it exceeds that of a staggered urban form under all wind directions (θ=0o to 45o), but is less than that of a rectangular urban form (Lx=570m, Ly=270m) under most wind directions (θ=30o to 90o). Further investigations are still required to quantify the net ventilation efficiency induced by mean flows and turbulence.

Aircraft routing with minimal climate impact: the REACT4C climate cost function modelling approach (V1.0)

In addition to CO2, the climate impact of aviation is strongly influenced by non-CO2 emissions, such as nitrogen oxides, influencing ozone and methane, and water vapour, which can lead to the formation of persistent contrails in ice-supersaturated regions. Because these non-CO2 emission effects are characterised by a short lifetime, their climate impact largely depends on emission location and time; that is to say, emissions in certain locations (or times) can lead to a greater climate impact (even on the global average) than the same emission in other locations (or times). Avoiding these climate-sensitive regions might thus be beneficial to climate. Here, we describe a modelling chain for investigating this climate impact mitigation option. This modelling chain forms a multi-step modelling approach, starting with the simulation of the fate of emissions released at a certain location and time (time-region grid points). This is performed with the chemistry–climate model EMAC, extended via the two submodels AIRTRAC (V1.0) and CONTRAIL (V1.0), which describe the contribution of emissions to the composition of the atmosphere and to contrail formation, respectively. The impact of emissions from the large number of time-region grid points is efficiently calculated by applying a Lagrangian scheme. EMAC also includes the calculation of radiative impacts, which are, in a second step, the input to climate metric formulas describing the global climate impact of the emission at each time-region grid point. The result of the modelling chain comprises a four-dimensional data set in space and time, which we call climate cost functions and which describes the global climate impact of an emission at each grid point and each point in time. In a third step, these climate cost functions are used in an air traffic simulator (SAAM) coupled to an emission tool (AEM) to optimise aircraft trajectories for the North Atlantic region. Here, we describe the details of this new modelling approach and show some example results. A number of sensitivity analyses are performed to motivate the settings of individual parameters. A stepwise sanity check of the results of the modelling chain is undertaken to demonstrate the plausibility of the climate cost functions.

Obstacle avoidance routing scheme through optimal sink movement for home monitoring and mobile robotic consumer devices

In recent years, ZigBee has been proven to be an excellent solution to create scalable and flexible home automation networks. In a home automation network, consumer devices typically collect data from a home monitoring environment and then transmit the data to an end user through multi-hop communication without the need for any human intervention. However, due to the presence of typical obstacles in a home environment, error-free reception may not be possible, particularly for power constrained devices. A mobile sink based data transmission scheme can be one solution but obstacles create significant complexities for the sink movement path determination process. Therefore, an obstacle avoidance data routing scheme is of vital importance to the design of an efficient home automation system. This paper presents a mobile sink based obstacle avoidance routing scheme for a home monitoring system. The mobile sink collects data by traversing through the obstacle avoidance path. Through ZigBee based hardware implementation and verification, the proposed scheme successfully transmits data through the obstacle avoidance path to improve network performance in terms of life span, energy consumption and reliability. The application of this work can be applied to a wide range of intelligent pervasive consumer products and services including robotic vacuum cleaners and personal security robots1.