Estimating the number of distinct flows, also called the cardinality, is an important issue in many network applications, such as traffic measurement, anomaly detection, etc. The challenging problem is that a high acc...
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ISBN:
(纸本)9781538636503
Estimating the number of distinct flows, also called the cardinality, is an important issue in many network applications, such as traffic measurement, anomaly detection, etc. The challenging problem is that a high accuracy should be achieved with line speed and small auxiliary memory. The state-of-the-art, LogLog algorithm, uses loglogN max memory, where N max is the priori upper bound for cardinality, and achieves an accuracy of the order of 1/√d, where d is the number of counters. In this paper, we propose a refined version of LogLog algorithm, namely Refined LogLog. It achieves a much better accuracy than the original LogLog algorithm by using more fine-grained common ratios. The algorithm is validated by a detailed analysis. A self-adaptive version, Self-Adaptive LogLog, is also proposed based on Refined LogLog, to adapt to cardinalities of different scales automatically. Our experimental results show that Refined LogLog outperforms LogLog in accuracy by up to 67.0%, and reduces the standard deviation by up to 60.8%.
Disk drive failure related data lost remains a major threat to storage system reliability. Current counter-measurement all focused on reactive data protection, such as using RAID or erasure coding to reconstruct data ...
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ISBN:
(纸本)9781538675199
Disk drive failure related data lost remains a major threat to storage system reliability. Current counter-measurement all focused on reactive data protection, such as using RAID or erasure coding to reconstruct data after failure occurs. We argue that post-failure recovery will not scalable when the storage demand keep increase. In this paper, we present a proactive data protection (PDP) framework within the ZFS file system to rescue data from disks before actual failure onset. By reducing the risk of data loss and mitigating the prolonged disk rebuilds caused by disk failures, PDP is designed to enhance the overall storage reliability. We extensively evaluate the recovery performance of ZFS with diverse configurations, and further explore disk failure prediction techniques to develop a proactive data protection mechanism in ZFS. We further compare the performance of different data protection strategies, including post-failure disk recovery, proactive disk cloning, and proactive data recovery. We propose an analytic model that uses storage utilization and contextual system information to select the best data protection strategy that can save up to 70% of data rescue time.
In quantum mechanics, geometry has been demonstrated as a useful tool for inferring nonclassical behaviors and exotic properties of quantum systems. One standard approach to illustrate the geometry of quantum systems ...
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In quantum mechanics, geometry has been demonstrated as a useful tool for inferring nonclassical behaviors and exotic properties of quantum systems. One standard approach to illustrate the geometry of quantum systems is to project the quantum state space onto the Euclidean space via measurements of observables on the system. Despite the great success of this method in studying two-level quantum systems (qubits) with the celebrated Bloch sphere representation, it is still difficult to reveal the geometry of multidimensional quantum systems. Here we report the first experiment measuring the geometry of such projections beyond the qubit. Specifically, we observe the joint numerical ranges of a triple of observables in a three-level photonic system, providing a complete classification of these ranges. We further show that the geometry of different classes reveals ground-state degeneracies of a Hamiltonian as a linear combination of the observables, which is related to quantum phases in the thermodynamic limit. Our results offer a versatile geometric approach for exploring the properties of higher-dimensional quantum systems.
Skyrmions are localized solitonic spin textures with protected topology, which are promising as information carriers in ultra-dense and energy-efficient logics and memories. Magnetic skyrmions have been recently obser...
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The problem of item selling with the objective of maximizing the revenue is studied. Given a seller with k types of items and n single-minded buyers, i.e., each buyer is only interested in a particular bundle of items...
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We compute the nucleon axial and induced pseudoscalar form factors using three ensembles of gauge configurations, generated with dynamical light quarks with mass tuned to approximately their physical value. One of the...
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We compute the nucleon axial and induced pseudoscalar form factors using three ensembles of gauge configurations, generated with dynamical light quarks with mass tuned to approximately their physical value. One of the ensembles also includes the strange and charm quarks with their mass close to physical. The latter ensemble has large statistics and finer lattice spacing and it is used to obtain final results, while the other two are used for assessing volume effects. The pseudoscalar form factor is also computed using these ensembles. We examine the momentum dependence of these form factors as well as relations based on pion pole dominance and the partially conserved axial-vector current hypothesis.
Container-based highperformancecomputing (HPC) has started gaining popularity due to its almost negligible performance penalty compared to the BareMetal hardware. Although HPC hardware architectures and programming ...
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Memristive technology has been widely explored, due to its distinctive properties, such as nonvolatility, high density,versatility, and CMOS compatibility. For memristive devices, a general compact model is highly fav...
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Memristive technology has been widely explored, due to its distinctive properties, such as nonvolatility, high density,versatility, and CMOS compatibility. For memristive devices, a general compact model is highly favorable for the realization of its circuits and applications. In this paper, we propose a novel memristive model of TiOx-based devices, which considers the negative differential resistance（NDR） behavior. This model is physics-oriented and passes Linn＇s criteria. It not only exhibits sufficient accuracy（IV characteristics within 1.5% RMS）, lower latency（below half the VTEAM model）,and preferable generality compared to previous models, but also yields more precise predictions of long-term potentiation/depression（LTP/LTD）. Finally, novel methods based on memristive models are proposed for gray sketching and edge detection applications. These methods avoid complex nonlinear functions required by their original counterparts. When the proposed model is utilized in these methods, they achieve increased contrast ratio and accuracy（for gray sketching and edge detection, respectively） compared to the Simmons model. Our results suggest a memristor-based network is a promising candidate to tackle the existing inefficiencies in traditional image processing methods.
Background: In current approaches to vision screening in the community, a simple and efficient process is needed to identify individuals who should be referred to tertiary eye care centres for vision loss related to e...
Background: In current approaches to vision screening in the community, a simple and efficient process is needed to identify individuals who should be referred to tertiary eye care centres for vision loss related to eye diseases. The emergence of deep learning technology offers new opportunities to revolutionise this clinical referral pathway. We aimed to assess the performance of a newly developed deep learning algorithm for detection of disease-related visual impairment. Methods: In this proof-of-concept study, using retinal fundus images from 15 175 eyes with complete data related to best-corrected visual acuity or pinhole visual acuity from the Singapore Epidemiology of Eye Diseases Study, we first developed a single-modality deep learning algorithm based on retinal photographs alone for detection of any disease-related visual impairment (defined as eyes from patients with major eye diseases and best-corrected visual acuity of <20/40), and moderate or worse disease-related visual impairment (eyes with disease and best-corrected visual acuity of <20/60). After development of the algorithm, we tested it internally, using a new set of 3803 eyes from the Singapore Epidemiology of Eye Diseases Study. We then tested it externally using three population-based studies (the Beijing Eye study [6239 eyes], Central India Eye and Medical study [6526 eyes], and Blue Mountains Eye Study [2002 eyes]), and two clinical studies (the Chinese University of Hong Kong's Sight Threatening Diabetic Retinopathy study [971 eyes] and the Outram Polyclinic Study [1225 eyes]). The algorithm's performance in each dataset was assessed on the basis of the area under the receiver operating characteristic curve (AUC). Findings: In the internal test dataset, the AUC for detection of any disease-related visual impairment was 94·2% (95% CI 93·0–95·3;sensitivity 90·7% [87·0–93·6];specificity 86·8% [85·6–87·9]). The AUC for moderate or worse disease-related visual impairment was 93·9% (95% CI 92·2–95
Next-generation neutrino telescopes with significantly improved sensitivity are required to pinpoint the sources of the diffuse astrophysical neutrino flux detected by IceCube and uncover the century-old puzzle of cos...
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