Numerical modelling of high bit-rate dispersion managing systems

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Patterning effects in WDM RZ-DBPSK SMF/DCF optical transmission at 40 Gbit/s channel rate

Summary form only given. In this paper an important new example of a system with strong and nontrivial patterning effects is presented. There has been much interest lately in the implementation of the differential phase shift-keying (PSK) modulation format for long-haul and ultra long-haul fibre communications and, in particular, the differential binary PSK (DBPSK) modulation format, where data is encoded into the optical phase. The results of a direct computation of the error statistics for an SMF/DCF RZ-DBPSK 5-channel WDM RZ-DBPSK link with hybrid Raman/EDFA amplification at 40 Gbit/s per channel, with a channel separation of 100 GHz are presented. The statistics of bit triplets and quantify strong pattern-dependent ISI are obtained.

Long-range, high bit-rate secure key distribution link utilizing Raman Ultra-long fiber laser (UFL)

The distribution of the secret key is the weakest link of many data encryption systems. Quantum key distribution (QKD) schemes provide attractive solutions [1], however their implementation remains challenging and their range and bit-rate are limited. Moreover, practical QKD systems, employ real-life components and are, therefore, vulnerable to diverse attack schemes [2]. Ultra-Long fiber lasers (UFLs) have been drawing much attention recently because of their fundamentally different properties compared to conventional lasers as well as their unique applications [3]. Here, we demonstrate a 100Bps, practically secure key distribution, over a 500km link, employing Raman gain UFL. Fig. 1(a) depicts a schematic of the UFL system. Each user has an identical set of two wavelength selective mirrors centered at l0 and l 1. In order to exchange a key-bit, each user independently choose one of these mirrors and introduces it as a laser reflector at their end. If both users choose identical mirrors, a clear signal develops and the bits in these cases are discarded. However if they choose complementary mirrors, (1, 0 or 0, 1 states), the UFL remains below lasing threshold and no signal evolves. In these cases, an eavesdropper can only detect noise and is unable to determine the mirror choice of the users, where the choice of mirrors represent a single key bit (e.g. Alice's choice of mirror is the key-bit). These bits are kept and added to the key. The absence of signal in the secure states faxilitates fast measurements to distinguish between the non-secure and the secure states and to determine the key-bit in the later case, Sequentially reapeating the single bit exchange protocol generate the entire keys of any desirable length. © 2013 IEEE.

Error tolerance of topological codes with independent bit-flip and measurement errors

Topological quantum error correction codes are currently among the most promising candidates for efficiently dealing with the decoherence effects inherently present in quantum devices. Numerically, their theoretical error threshold can be calculated by mapping the underlying quantum problem to a related classical statistical-mechanical spin system with quenched disorder. Here, we present results for the general fault-tolerant regime, where we consider both qubit and measurement errors. However, unlike in previous studies, here we vary the strength of the different error sources independently. Our results highlight peculiar differences between toric and color codes. This study complements previous results published in New J. Phys. 13, 083006 (2011).

Sea surface temperature (TEX86), marine GDGTs and BIT index from ODP Hole 161-977A

The TEX86H temperature proxy is a relatively new proxy based on crenarchaeotal lipids and has rarely been applied together with other temperature proxies. In this study, we applied the TEX86H on a sediment core from the Alboran Sea (western Mediterranean, core ODP-977A) covering the penultimate climate cycle, that is, from 244 to 130 ka, and compared this with previously published sea surface temperatures derived from the Uk'37 of alkenones of haptophyta and Mg/Ca records of planktonic foraminifera. The TEX86H temperature record shows remarkably similar stadial-interstadial patterns and abrupt temperature changes to those observed with the Uk'37 palaeothermometer. Absolute TEX86H temperature estimates are generally higher than those of Uk'37, though this difference (<3°C in 81% of the data points) is mainly within the temperature calibration error for both proxies, suggesting that crenarchaeota and haptophyta experienced similar temperature variations. During occasional events (<5% of the analyzed time span), however, the TEX86H exhibits considerably higher absolute temperature estimates than the Uk'37. Comparison with Mg/Ca records of planktonic foraminifera as well as other Mediterranean TEX86 and Uk'37 records suggests that part of this divergence may be attributed to seasonal differences, that is, with TEX86H reflecting mainly the warm summer season while Uk'37 would show annual mean. Biases in the global calibration of both proxies or specific biases in the Mediterranean are an alternative, though less likely, explanation. Despite differences between absolute TEX86H and Uk'37 temperatures, the correlation between the two proxies (r**2 = 0.59, 95% significance) provides support for the occurrence of abrupt temperature variations in the western Mediterranean during the penultimate interglacial-to-glacial cycle.

Poster abstract : Energy-efficient rate adaptive MAC Protocol (RA-MAC) for long-lived sensor networks

This paper introduces an energy-efficient Rate Adaptive MAC (RA-MAC) protocol for long-lived Wireless Sensor Networks (WSN). Previous research shows that the dynamic and lossy nature of wireless communication is one of the major challenges to reliable data delivery in a WSN. RA-MAC achieves high link reliability in such situations by dynamically trading off radio bit rate for signal processing gain. This extra gain reduces the packet loss rate which results in lower energy expenditure by reducing the number of retransmissions. RA-MAC selects the optimal data rate based on channel conditions with the aim of minimizing energy consumption. We have implemented RA-MAC in TinyOS on an off-the-shelf sensor platform (TinyNode), and evaluated its performance by comparing RA-MAC with state-ofthe- art WSN MAC protocol (SCP-MAC) by experiments.

Use of IP addresses for high rate flooding attack detection

High-rate flooding attacks (aka Distributed Denial of Service or DDoS attacks) continue to constitute a pernicious threat within the Internet domain. In this work we demonstrate how using packet source IP addresses coupled with a change-point analysis of the rate of arrival of new IP addresses may be sufficient to detect the onset of a high-rate flooding attack. Importantly, minimizing the number of features to be examined, directly addresses the issue of scalability of the detection process to higher network speeds. Using a proof of concept implementation we have shown how pre-onset IP addresses can be efficiently represented using a bit vector and used to modify a “white list” filter in a firewall as part of the mitigation strategy.

A study of the generalised max–min fair rate allocation for ABR control in ATM

In the rate-based flow control for ATM Available Bit Rate service, fairness is an important requirement, i.e. each flow should be allocated a fair share of the available bandwidth in the network. Max–min fairness, which is widely adopted in ATM, is appropriate only when the minimum cell rates (MCRs) of the flows are zero or neglected. Generalised max–min (GMM) fairness extends the principle of the max–min fairness to accommodate MCR. In this paper, we will discuss the formulation of the GMM fair rate allocation, propose a centralised algorithm, analyse its bottleneck structure and develop an efficient distributed explicit rate allocation algorithm to achieve the GMM fairness in an ATM network. The study in this paper addresses certain theoretical and practical issues of the GMM fair rate allocation.

Weighted fairness with MCR guarantee and a general-purpose explicit rate allocation algorithm for ATM ABR service

In this paper, weighted fair rate allocation for ATM available bit rate (ABR) service is discussed with the concern of the minimum cell rate (MCR). Weighted fairness with MCR guarantee has been discussed recently in the literature. In those studies, each ABR virtual connection (VC) is first allocated its MCR, then the remaining available bandwidth is further shared among ABR VCs according to their weights. For the weighted fairness defined in this paper, the bandwidth is first allocated according to each VC's weight; if a VC's weighted share is less than its MCR, it should be allocated its MCR instead of the weighted share. This weighted fairness with MCR guarantee is referred to as extended weighted (EXW) fairness. Certain theoretical issues related to EXW, such as its global solution and bottleneck structure, are first discussed in the paper. A distributed explicit rate allocation algorithm is then proposed to achieve EXW fairness in ATM networks. The algorithm is a general-purpose explicit rate algorithm in the sense that it can realise almost all the fairness principles proposed for ABR so far whilst only minor modifications may be needed.

An enhanced explicit rate algorithm for ABR traffic control in ATM networks

A high performance, low computational complexity rate-based flow control algorithm which can avoid congestion and achieve fairness is important to ATM available bit rate service. The explicit rate allocation algorithm proposed by Kalampoukas et al. is designed to achieve max–min fairness in ATM networks. It has several attractive features, such as a fixed computational complexity of O(1) and the guaranteed convergence to max–min fairness. In this paper, certain drawbacks of the algorithm, such as the severe overload of an outgoing link during transient period and the non-conforming use of the current cell rate field in a resource management cell, have been identified and analysed; a new algorithm which overcomes these drawbacks is proposed. The proposed algorithm simplifies the rate computation as well. Compared with Kalampoukas's algorithm, it has better performance in terms of congestion avoidance and smoothness of rate allocation.

Bitrate modeling of scalable videos using quantization parameter, frame rate and spatial resolution

The quality and bitrate modeling is essential to effectively adapt the bitrate and quality of videos when delivered to multiplatform devices over resource constraint heterogeneous networks. The recent model proposed by Wang et al. estimates the bitrate and quality of videos in terms of the frame rate and quantization parameter. However, to build an effective video adaptation framework, it is crucial to incorporate the spatial resolution in the analytical model for bitrate and perceptual quality adaptation. Hence, this paper proposes an analytical model to estimate the bitrate of videos in terms of quantization parameter, frame rate, and spatial resolution. The model can fit the measured data accurately which is evident from the high Pearson correlation. The proposed model is based on the observation that the relative reduction in bitrate due to decreasing spatial resolution is independent of the quantization parameter and frame rate. This modeling can be used for rate-constrained bit-stream adaptation scheme which selects the scalability parameters to optimize the perceptual quality for a given bandwidth constraint.

Fast rates for estimation error and oracle inequalities for model section

We consider complexity penalization methods for model selection. These methods aim to choose a model to optimally trade off estimation and approximation errors by minimizing the sum of an empirical risk term and a complexity penalty. It is well known that if we use a bound on the maximal deviation between empirical and true risks as a complexity penalty, then the risk of our choice is no more than the approximation error plus twice the complexity penalty. There are many cases, however, where complexity penalties like this give loose upper bounds on the estimation error. In particular, if we choose a function from a suitably simple convex function class with a strictly convex loss function, then the estimation error (the difference between the risk of the empirical risk minimizer and the minimal risk in the class) approaches zero at a faster rate than the maximal deviation between empirical and true risks. In this paper, we address the question of whether it is possible to design a complexity penalized model selection method for these situations. We show that, provided the sequence of models is ordered by inclusion, in these cases we can use tight upper bounds on estimation error as a complexity penalty. Surprisingly, this is the case even in situations when the difference between the empirical risk and true risk (and indeed the error of any estimate of the approximation error) decreases much more slowly than the complexity penalty. We give an oracle inequality showing that the resulting model selection method chooses a function with risk no more than the approximation error plus a constant times the complexity penalty.

The effect of simulated astigmatic refractive error on reading performance

Background: Few studies have specifically investigated the functional effects of uncorrected astigmatism on measures of reading fluency. This information is important to provide evidence for the development of clinical guidelines for the correction of astigmatism. Methods: Participants included 30 visually normal, young adults (mean age 21.7 ± 3.4 years). Distance and near visual acuity and reading fluency were assessed with optimal spectacle correction (baseline) and for two levels of astigmatism, 1.00DC and 2.00DC, at two axes (90° and 180°) to induce both against-the-rule (ATR) and with-the-rule (WTR) astigmatism. Reading and eye movement fluency were assessed using standardized clinical measures including the test of Discrete Reading Rate (DRR), the Developmental Eye Movement (DEM) test and by recording eye movement patterns with the Visagraph (III) during reading for comprehension. Results: Both distance and near acuity were significantly decreased compared to baseline for all of the astigmatic lens conditions (p < 0.001). Reading speed with the DRR for N16 print size was significantly reduced for the 2.00DC ATR condition (a reduction of 10%), while for smaller text sizes reading speed was reduced by up to 24% for the 1.00DC ATR and 2.00DC condition in both axis directions (p<0.05). For the DEM, sub-test completion speeds were significantly impaired, with the 2.00DC condition affecting both vertical and horizontal times and the 1.00DC ATR condition affecting only horizontal times (p<0.05). Visagraph reading eye movements were not significantly affected by the induced astigmatism. Conclusions: Induced astigmatism impaired performance on selected tests of reading fluency, with ATR astigmatism having significantly greater effects on performance than did WTR, even for relatively small amounts of astigmatic blur of 1.00DC. These findings have implications for the minimal prescribing criteria for astigmatic refractive errors.

GNSS ambiguity resolution with controllable failure rate for long baseline network RTK

Many large-scale GNSS CORS networks have been deployed around the world to support various commercial and scientific applications. To make use of these networks for real-time kinematic positioning services, one of the major challenges is the ambiguity resolution (AR) over long inter-station baselines in the presence of considerable atmosphere biases. Usually, the widelane ambiguities are fixed first, followed by the procedure of determination of the narrowlane ambiguity integers based on the ionosphere-free model in which the widelane integers are introduced as known quantities. This paper seeks to improve the AR performance over long baseline through efficient procedures for improved float solutions and ambiguity fixing. The contribution is threefold: (1) instead of using the ionosphere-free measurements, the absolute and/or relative ionospheric constraints are introduced in the ionosphere-constrained model to enhance the model strength, thus resulting in the better float solutions; (2) the realistic widelane ambiguity precision is estimated by capturing the multipath effects due to the observation complexity, leading to improvement of reliability of widelane AR; (3) for the narrowlane AR, the partial AR for a subset of ambiguities selected according to the successively increased elevation is applied. For fixing the scalar ambiguity, an error probability controllable rounding method is proposed. The established ionosphere-constrained model can be efficiently solved based on the sequential Kalman filter. It can be either reduced to some special models simply by adjusting the variances of ionospheric constraints, or extended with more parameters and constraints. The presented methodology is tested over seven baselines of around 100 km from USA CORS network. The results show that the new widelane AR scheme can obtain the 99.4 % successful fixing rate with 0.6 % failure rate; while the new rounding method of narrowlane AR can obtain the fix rate of 89 % with failure rate of 0.8 %. In summary, the AR reliability can be efficiently improved with rigorous controllable probability of incorrectly fixed ambiguities.