DOS | EPFL Graph Search

On appelle généralement DOS (disk operating system) le système d'exploitation PC-DOS, ainsi que la variante MS-DOS vendue par Microsoft pour les compatibles PC. Il en existe des clones postérieurs, tels DR-DOS de Digital Research et FreeDOS. Jusqu'au début des années 1990, DOS était le type de système le plus utilisé sur compatibles PC. Ce système en ligne de commande était rudimentaire : pas de multitâche, pas de mémoire virtuelle, gestion du seul mode segmenté du microprocesseur x86. Il existe d'autres systèmes sans relation directe qui contiennent le mot DOS (AMSDOS, AmigaDOS, Apple DOS, ProDOS, DOS sur mainframe), mais leur nom est éclipsé. Histoire L'origine de DOS remonte à , lors du lancement de l'IBM PC (Personal Computer) par IBM. La société avait demandé à Digital Research, créateur de CP/M qui dominait le marché à l'époque, de porter son système sur le PC, mais devant le peu d'empressement de son directeur Gary Kildall, elle s'était adressée également à Bill G

Denial-of-service resilience in peer-to-peer file sharing systems

Dan Mihai Dumitriu, Willy Zwaenepoel

Peer-to-peer (p2p) file sharing systems are characterized by highly replicated content distributed among nodes with enormous aggregate resources for storage and communication. These properties alone are not sufficient, however, to render p2p networks immune to denial-of-service (DoS) attack. In this paper, we study, by means of analytical modeling and simulation, the resilience of p2p file sharing systems against DoS attacks, in which malicious nodes respond to queries with erroneous responses. We consider the filetargeted attacks in current use in the Internet, and we introduce a new class of p2p-network-targeted attacks. In file-targeted attacks, the attacker puts a large number of corrupted versions of a single file on the network. We demonstrate that the effectiveness of these attacks is highly dependent on the clients’ behavior. For the attacks to succeed over the long term, clients must be unwilling to share files, slow in removing corrupted files from their machines, and quick to give up downloading when the system is under attack. In network-targeted attacks, attackers respond to queries for any file with erroneous information. Our results indicate that these attacks are highly scalable: increasing the number of malicious nodes yields a hyperexponential decrease in system goodput, and a moderate number of attackers suffices to cause a near-collapse of the entire system. The key factors inducing this vulnerability are (i) hierarchical topologies with misbehaving “supernodes,” (ii) high path-length networks in which attackers have increased opportunity to falsify control information, and (iii) power-law networks in which attackers insert themselves into high-degree points in the graph. Finally, we consider the effects of client counter-strategies such as randomized reply selection, redundant and parallel download, and reputation systems. Some counter-strategies (e.g., randomized reply selection) provide considerable immunity to attack (reducing the scaling from hyperexponential to linear), yet significantly hurt performance in the absence of an attack. Other counter-strategies yield little benefit (or penalty). In particular, reputation systems show little impact unless they operate with near perfection.

2005

Learning the electronic density of states in condensed matter

Andrea Anelli, Chiheb Ben Mahmoud, Michele Ceriotti

The electronic density of states (DOS) quantifies the distribution of the energy levels that can be occupied by electrons in a quasiparticle picture and is central to modern electronic structure theory. It also underpins the computation and interpretation of experimentally observable material properties such as optical absorption and electrical conductivity. We discuss the challenges inherent in the construction of a machine-learning (ML) framework aimed at predicting the DOS as a combination of local contributions that depend in turn on the geometric configuration of neighbors around each atom, using quasiparticle energy levels from density functional theory as training data. We present a challenging case study that includes configurations of silicon spanning a broad set of thermodynamic conditions, ranging from bulk structures to clusters and from semiconducting to metallic behavior. We compare different approaches to represent the DOS, and the accuracy of predicting quantities such as the Fermi level, the electron density at the Fermi level, or the band energy, either directly or as a side product of the evaluation of the DOS. We find that the performance of the model depends crucially on the resolution chosen to smooth the DOS and that there is a tradeoff to be made between the systematic error associated with the smoothing and the error in the ML model for a specific structure. We find however that the errors are not strongly correlated among similar structures, and so the average DOS over an ensemble of configurations is in very good agreement with the reference electronic structure calculations, despite the large nominal error on individual configurations. We demonstrate the usefulness of this approach by computing the density of states of a large amorphous silicon sample, for which it would be prohibitively expensive to compute the DOS by direct electronic structure calculations and show how the atom-centered decomposition of the DOS that is obtained through our model can be used to extract physical insights into the connections between structural and electronic features.

AMER PHYSICAL SOC2020

Anomalous double peak structure in superconductor/ferromagnet tunneling density of states

Paul Sangiorgio

We have experimentally investigated the density of states (DOS) in Nb/Ni (S/F) bilayers as a function of Ni thickness, d(F). Our thinnest samples show the usual DOS peak at +/-Delta(0), whereas intermediate-thickness samples have an anomalous "double-peak" structure. For thicker samples (d(F)>= 3.5 nm), we see an inverted DOS, which has previously only been reported in superconductor or weak-ferromagnet structures. We analyze the data using the self-consistent nonlinear Usadel equation and find that we are able to quantitatively fit the features at +/-Delta(0)-in particular the thickness at which the inversion occurs-only if we include a large amount of spin-orbit scattering in the model. Interestingly, we are unable to reproduce the subgap structure through the addition of any parameter(s). Therefore, the observed anomalous subgap structure represents new physics beyond that contained in the present Usadel theory.