Experimental evaluation of the usage of ad hoc networks as stubs for multiservice networks

This paper describes an experimental evaluation of a multiservice ad hoc network, aimed to be interconnected with an infrastructure, operator-managed network. This network supports the efficient delivery of services, unicast and multicast, legacy and multimedia, to users connected in the ad hoc network. It contains the following functionalities: routing and delivery of unicast and multicast services; distributed QoS mechanisms to support service differentiation and resource control responsive to node mobility; security, charging, and rewarding mechanisms to ensure the correct behaviour of the users in the ad hoc network. This paper experimentally evaluates the performance of multiple mechanisms, and the influence and performance penalty introduced in the network, with the incremental inclusion of new functionalities. The performance results obtained in the different real scenarios may question the real usage of ad-hoc networks for more than a minimal number of hops with such a large number of functionalities deployed

Isotopic exchange processes in cold plasmas of H2/D2 mixtures

12 páginas, 3 tablas, 10 figuras.-Isotope exchange in low pressure cold plasmas of H2/D2 mixtures has been investigated by means of mass spectrometric measurements of neutrals and ions, and kinetic model calculations. The measurements, which include also electron temperatures and densities, were performed in a stainless steel hollow cathode reactor for three discharge pressures: 1, 2 and 8 Pa, and for mixture compositions ranging from 100% H2 to 100% D2. The data are analyzed in the light of the model calculations, which are in good global agreement with the experiments. Isotope selective effects are found both in the surface recombination and in the gas-phase ionic chemistry. The dissociation of the fuel gas molecules is followed by wall recycling, which regenerates H2 and D2 and produces HD. Atomic recombination at the wall is found to proceed through an Eley–Rideal mechanism, with a preference for reaction of the adsorbed atoms with gas phase D atoms. The best fit probabilities for Eley–Rideal abstraction with H and D are:gER H = 1.5 x 10-3, gER D = 2.0 x 10-3. Concerning ions, at 1 Pa the diatomic species H2+,D2+ and HD+, formed directly by electron impact, prevail in the distributions, and at 8 Pa, the triatomic ions H3+, H2D+, HD2+ and D3+, produced primarily in reactions of diatomic ions with molecules, dominate the plasma composition. In this higher pressure regime, the formation of the mixed ions H2D+ and HD2 + is favoured in comparison with that of H3 + and D3+, as expected on statistical grounds. The model results predict a very small preference, undetectable within the precision of the measurements, for the generation of triatomic ions with a higher degree of deuteration, which is probably a residual influence at room temperature of the marked zero point energy effects (ZPE), relevant for deuterium fractionation in interstellar space. In contrast,ZPE effects are found to be decisive for the observed distribution of monoatomic ions H+ and D+, even at room temperature. The final H+/D+ ratio is determined to a great extent by proton (and deuteron) exchange, which favours the enhancement of H+ and the concomitant decrease of D+.This work has been funded by the MICINN of Spain under projects FIS 2007-61686, FIS2010-16455 and CSD2009-00038. EC acknowledges also funding from the JdC program of the MICINN.Peer reviewe

AMI threats, intrusion detection requirements and deployment recommendations

Abstract—Advanced Metering Infrastructures (AMI) facilitate bidirectional communication between smart meters and utilities, allowing information about consumption, outages, and electricity rates to be shared reliably and efficiently. However, the numerous smart meters being connected through mesh networks open new opportunities for attackers to interfere with communications and compromise utilities ’ assets or steal customers ’ private information. The goal of this paper is to survey the various threats facing AMIs and the common attack techniques used to realize them in order to identify and understand the requirements for a comprehensive intrusion detection solution. The threat analysis leads to an extensive “attack tree ” that captures the attackers’ key objectives (e.g., energy theft) and the individual attack steps (e.g., eavesdropping on the network) that would be involved in achieving them. With reference to the attack tree, we show the type of information that would be required to effectively detect attacks. We also suggest that the widest coverage in monitoring the attacks can be provided by a hybrid sensing infrastructure that uses both a centralized intrusion detection system and embedded meter sensors. I

Comparison between Ribosomal Assembly and Machine Learning Tools for Microbial Identification of Organisms with Different Characteristics

Background: Genome assembly tools are used to reconstruct genomic sequences from raw sequencing data, which are then used for identifying the organisms present in a metagenomic sample. Methodology: More recently, machine learning approaches have been applied to a variety of bioinformatics problems, and in this paper, we explore their use for organism identification. We start by evaluating several commonly used metagenomic assembly tools, including PhyloFlash, MEGAHIT, MetaSPAdes, Kraken2, Mothur, UniCycler, and PathRacer, and compare them against state-of-the-art deep learning-based machine learning classification approaches represented by DNABERT and DeLUCS, in the context of two synthetic mock community datasets. Results: Our analysis focuses on determining whether ensembling metagenome assembly tools with machine learning tools have the potential to improve identification performance relative to using the tools individually. Conclusion: We find that this is indeed the case, and analyze the level of effectiveness of potential tool ensembling for organisms with different characteristics (based on factors such as repetitiveness, genome size, and GC content)