53,397 research outputs found

    Service quality measurements for IPv6 inter-networks

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    Measurement-based performance evaluation of network traffic is becoming very important, especially for networks trying to provide differentiated levels of service quality to the different application flows. The non-identical response of flows to the different types of network-imposed performance degradation raises the need for ubiquitous measurement mechanisms, able to measure numerous performance properties, and being equally applicable to different applications and transports. This paper presents a new measurement mechanism, facilitated by the steady introduction of IPv6 in network nodes and hosts, which exploits native features of the protocol to provide support for performance measurements at the network (IP) layer. IPv6 Extension Headers have been used to carry the triggers involving the measurement activity and the measurement data in-line with the payload data itself, providing a high level of probability that the behaviour of the real user traffic flows is observed. End-to-end one-way delay, jitter, loss, and throughput have been measured for applications operating on top of both reliable and unreliable transports, over different-capacity IPv6 network configurations. We conclude that this technique could form the basis for future Internet measurements that can be dynamically deployed where and when required in a multi-service IP environment

    Measuring and mitigating AS-level adversaries against Tor

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    The popularity of Tor as an anonymity system has made it a popular target for a variety of attacks. We focus on traffic correlation attacks, which are no longer solely in the realm of academic research with recent revelations about the NSA and GCHQ actively working to implement them in practice. Our first contribution is an empirical study that allows us to gain a high fidelity snapshot of the threat of traffic correlation attacks in the wild. We find that up to 40% of all circuits created by Tor are vulnerable to attacks by traffic correlation from Autonomous System (AS)-level adversaries, 42% from colluding AS-level adversaries, and 85% from state-level adversaries. In addition, we find that in some regions (notably, China and Iran) there exist many cases where over 95% of all possible circuits are vulnerable to correlation attacks, emphasizing the need for AS-aware relay-selection. To mitigate the threat of such attacks, we build Astoria--an AS-aware Tor client. Astoria leverages recent developments in network measurement to perform path-prediction and intelligent relay selection. Astoria reduces the number of vulnerable circuits to 2% against AS-level adversaries, under 5% against colluding AS-level adversaries, and 25% against state-level adversaries. In addition, Astoria load balances across the Tor network so as to not overload any set of relays.Comment: Appearing at NDSS 201

    Pattern-recalling processes in quantum Hopfield networks far from saturation

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    As a mathematical model of associative memories, the Hopfield model was now well-established and a lot of studies to reveal the pattern-recalling process have been done from various different approaches. As well-known, a single neuron is itself an uncertain, noisy unit with a finite unnegligible error in the input-output relation. To model the situation artificially, a kind of 'heat bath' that surrounds neurons is introduced. The heat bath, which is a source of noise, is specified by the 'temperature'. Several studies concerning the pattern-recalling processes of the Hopfield model governed by the Glauber-dynamics at finite temperature were already reported. However, we might extend the 'thermal noise' to the quantum-mechanical variant. In this paper, in terms of the stochastic process of quantum-mechanical Markov chain Monte Carlo method (the quantum MCMC), we analytically derive macroscopically deterministic equations of order parameters such as 'overlap' in a quantum-mechanical variant of the Hopfield neural networks (let us call "quantum Hopfield model" or "quantum Hopfield networks"). For the case in which non-extensive number pp of patterns are embedded via asymmetric Hebbian connections, namely, p/N→0p/N \to 0 for the number of neuron N→∞N \to \infty ('far from saturation'), we evaluate the recalling processes for one of the built-in patterns under the influence of quantum-mechanical noise.Comment: 10 pages, 3 figures, using jpconf.cls, Proc. of Statphys-Kolkata VI

    Reliable routing scheme for indoor sensor networks

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    Indoor Wireless sensor networks require a highly dynamic, adaptive routing scheme to deal with the high rate of topology changes due to fading of indoor wireless channels. Besides that, energy consumption rate needs to be consistently distributed among sensor nodes and efficient utilization of battery power is essential. If only the link reliability metric is considered in the routing scheme, it may create long hops routes, and the high quality paths will be frequently used. This leads to shorter lifetime of such paths; thereby the entire network's lifetime will be significantly minimized. This paper briefly presents a reliable load-balanced routing (RLBR) scheme for indoor ad hoc wireless sensor networks, which integrates routing information from different layers. The proposed scheme aims to redistribute the relaying workload and the energy usage among relay sensor nodes to achieve balanced energy dissipation; thereby maximizing the functional network lifetime. RLBR scheme was tested and benchmarked against the TinyOS-2.x implementation of MintRoute on an indoor testbed comprising 20 Mica2 motes and low power listening (LPL) link layer provided by CC1000 radio. RLBR scheme consumes less energy for communications while reducing topology repair latency and achieves better connectivity and communication reliability in terms of end-to-end packets delivery performance

    Capital structure of portuguese hotel firms: a structural equation modelling approach

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    This paper addresses capital structure determinants for Portuguese hotel firms between 2006 and 2014. Secondary data from 356 hotel units was analysed using the partial least squares (PLS) statistical technique, a variance-based structural equation modelling (SEM). The results show that the explanatory variables proposed as capital structure determinants have an impact on the financing and debt decisions made by the firms in the sample. Of these, tangibility has the greater explanatory power. Overall, the results support the notion that trade-off theory and pecking-order theory are important in explaining the capital structure of the Portuguese hotel industry, particularly as regards the agency conflicts triggered by growth opportunities and the preference firms have for internal funding. The results also point to the importance of collateral in accessing credit and the lesser impact of asymmetric information pertaining to tangible asset value and firm size. The results suggest small firms find it difficult to contract loans, which can somewhat limit their growth and performance.info:eu-repo/semantics/publishedVersio
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